WO2013120079A1 - System and method of material handling using one or more imaging devices on the transferring vehicle and on the receiving vehicle to control the material distribution into the storage portion of the receiving vehicle - Google Patents

System and method of material handling using one or more imaging devices on the transferring vehicle and on the receiving vehicle to control the material distribution into the storage portion of the receiving vehicle Download PDF

Info

Publication number
WO2013120079A1
WO2013120079A1 PCT/US2013/025588 US2013025588W WO2013120079A1 WO 2013120079 A1 WO2013120079 A1 WO 2013120079A1 US 2013025588 W US2013025588 W US 2013025588W WO 2013120079 A1 WO2013120079 A1 WO 2013120079A1
Authority
WO
WIPO (PCT)
Prior art keywords
image data
imaging device
spout
vehicle
data
Prior art date
Application number
PCT/US2013/025588
Other languages
French (fr)
Inventor
Zachary T. BONEFAS
Darin E. BARTHOLOMEW
Original Assignee
Deere & Company
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Deere & Company filed Critical Deere & Company
Priority to AU2013216776A priority Critical patent/AU2013216776B2/en
Priority to US14/377,413 priority patent/US9522792B2/en
Priority to DE112013000929.3T priority patent/DE112013000929T5/en
Priority to GB1412567.8A priority patent/GB2517292B/en
Publication of WO2013120079A1 publication Critical patent/WO2013120079A1/en

Links

Classifications

    • BPERFORMING OPERATIONS; TRANSPORTING
    • B65CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
    • B65GTRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
    • B65G67/00Loading or unloading vehicles
    • B65G67/02Loading or unloading land vehicles
    • B65G67/24Unloading land vehicles
    • AHUMAN NECESSITIES
    • A01AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01DHARVESTING; MOWING
    • A01D43/00Mowers combined with apparatus performing additional operations while mowing
    • A01D43/08Mowers combined with apparatus performing additional operations while mowing with means for cutting up the mown crop, e.g. forage harvesters
    • A01D43/086Mowers combined with apparatus performing additional operations while mowing with means for cutting up the mown crop, e.g. forage harvesters and means for collecting, gathering or loading mown material
    • A01D43/087Mowers combined with apparatus performing additional operations while mowing with means for cutting up the mown crop, e.g. forage harvesters and means for collecting, gathering or loading mown material with controllable discharge spout
    • AHUMAN NECESSITIES
    • A01AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01BSOIL WORKING IN AGRICULTURE OR FORESTRY; PARTS, DETAILS, OR ACCESSORIES OF AGRICULTURAL MACHINES OR IMPLEMENTS, IN GENERAL
    • A01B69/00Steering of agricultural machines or implements; Guiding agricultural machines or implements on a desired track
    • AHUMAN NECESSITIES
    • A01AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01DHARVESTING; MOWING
    • A01D41/00Combines, i.e. harvesters or mowers combined with threshing devices
    • A01D41/12Details of combines
    • A01D41/127Control or measuring arrangements specially adapted for combines
    • A01D41/1275Control or measuring arrangements specially adapted for combines for the level of grain in grain tanks
    • AHUMAN NECESSITIES
    • A01AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01DHARVESTING; MOWING
    • A01D43/00Mowers combined with apparatus performing additional operations while mowing
    • A01D43/06Mowers combined with apparatus performing additional operations while mowing with means for collecting, gathering or loading mown material
    • AHUMAN NECESSITIES
    • A01AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01DHARVESTING; MOWING
    • A01D43/00Mowers combined with apparatus performing additional operations while mowing
    • A01D43/06Mowers combined with apparatus performing additional operations while mowing with means for collecting, gathering or loading mown material
    • A01D43/07Mowers combined with apparatus performing additional operations while mowing with means for collecting, gathering or loading mown material in or into a trailer
    • AHUMAN NECESSITIES
    • A01AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01DHARVESTING; MOWING
    • A01D75/00Accessories for harvesters or mowers
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60PVEHICLES ADAPTED FOR LOAD TRANSPORTATION OR TO TRANSPORT, TO CARRY, OR TO COMPRISE SPECIAL LOADS OR OBJECTS
    • B60P1/00Vehicles predominantly for transporting loads and modified to facilitate loading, consolidating the load, or unloading
    • B60P1/40Vehicles predominantly for transporting loads and modified to facilitate loading, consolidating the load, or unloading using screw conveyors thereon
    • B60P1/42Vehicles predominantly for transporting loads and modified to facilitate loading, consolidating the load, or unloading using screw conveyors thereon mounted on the load-transporting element
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60RVEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R11/00Arrangements for holding or mounting articles, not otherwise provided for
    • B60R11/04Mounting of cameras operative during drive; Arrangement of controls thereof relative to the vehicle
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B62LAND VEHICLES FOR TRAVELLING OTHERWISE THAN ON RAILS
    • B62DMOTOR VEHICLES; TRAILERS
    • B62D6/00Arrangements for automatically controlling steering depending on driving conditions sensed and responded to, e.g. control circuits
    • B62D6/001Arrangements for automatically controlling steering depending on driving conditions sensed and responded to, e.g. control circuits the torque NOT being among the input parameters
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B65CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
    • B65BMACHINES, APPARATUS OR DEVICES FOR, OR METHODS OF, PACKAGING ARTICLES OR MATERIALS; UNPACKING
    • B65B1/00Packaging fluent solid material, e.g. powders, granular or loose fibrous material, loose masses of small articles, in individual containers or receptacles, e.g. bags, sacks, boxes, cartons, cans, or jars
    • B65B1/30Devices or methods for controlling or determining the quantity or quality or the material fed or filled
    • B65B1/48Checking volume of filled material
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B65CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
    • B65FGATHERING OR REMOVAL OF DOMESTIC OR LIKE REFUSE
    • B65F9/00Transferring of refuse between vehicles or containers with intermediate storage or pressing
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B65CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
    • B65GTRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
    • B65G67/00Loading or unloading vehicles
    • B65G67/02Loading or unloading land vehicles
    • B65G67/04Loading land vehicles
    • B65G67/22Loading moving vehicles
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02Control of position or course in two dimensions
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0231Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
    • G05D1/0246Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0231Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
    • G05D1/0246Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means
    • G05D1/0251Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means extracting 3D information from a plurality of images taken from different locations, e.g. stereo vision
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0287Control of position or course in two dimensions specially adapted to land vehicles involving a plurality of land vehicles, e.g. fleet or convoy travelling
    • G05D1/0291Fleet control
    • G05D1/0293Convoy travelling
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/22Matching criteria, e.g. proximity measures
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F7/00Methods or arrangements for processing data by operating upon the order or content of the data handled
    • G06F7/60Methods or arrangements for performing computations using a digital non-denominational number representation, i.e. number representation without radix; Computing devices using combinations of denominational and non-denominational quantity representations, e.g. using difunction pulse trains, STEELE computers, phase computers
    • G06F7/70Methods or arrangements for performing computations using a digital non-denominational number representation, i.e. number representation without radix; Computing devices using combinations of denominational and non-denominational quantity representations, e.g. using difunction pulse trains, STEELE computers, phase computers using stochastic pulse trains, i.e. randomly occurring pulses the average pulse rates of which represent numbers
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/10Segmentation; Edge detection
    • G06T7/13Edge detection
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/20Analysis of motion
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/50Depth or shape recovery
    • G06T7/55Depth or shape recovery from multiple images
    • G06T7/593Depth or shape recovery from multiple images from stereo images
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/60Analysis of geometric attributes
    • G06T7/62Analysis of geometric attributes of area, perimeter, diameter or volume
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/70Determining position or orientation of objects or cameras
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16ZINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS, NOT OTHERWISE PROVIDED FOR
    • G16Z99/00Subject matter not provided for in other main groups of this subclass
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N13/00Stereoscopic video systems; Multi-view video systems; Details thereof
    • H04N13/10Processing, recording or transmission of stereoscopic or multi-view image signals
    • H04N13/106Processing image signals
    • H04N13/128Adjusting depth or disparity
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N7/00Television systems
    • H04N7/18Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N7/00Television systems
    • H04N7/18Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
    • H04N7/181Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N7/00Television systems
    • H04N7/18Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
    • H04N7/183Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a single remote source
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B65CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
    • B65FGATHERING OR REMOVAL OF DOMESTIC OR LIKE REFUSE
    • B65F2210/00Equipment of refuse receptacles
    • B65F2210/182Volume determining means
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10016Video; Image sequence
    • G06T2207/10021Stereoscopic video; Stereoscopic image sequence
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10028Range image; Depth image; 3D point clouds
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20048Transform domain processing
    • G06T2207/20061Hough transform
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20228Disparity calculation for image-based rendering
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30248Vehicle exterior or interior
    • G06T2207/30252Vehicle exterior; Vicinity of vehicle

Definitions

  • This invention relates to a method and stereo vision system for facilitating the unloading of material from a vehicle.
  • GPS global positioning system
  • Certain prior art systems may attempt to use global positioning system (GPS) receivers to maintain proper spacing between two vehicles during the unloading or transferring of agricultural material or other material, such as coal and other minerals, between the vehicles.
  • GPS global positioning system
  • Such prior art systems are susceptible to misalignment of the proper spacing because of errors or discontinuities in the estimated position of the GPS receivers.
  • one or more of the GPS receivers may misestimate its position because of electromagnetic interference, multipath propagation of the received satellite signals, intermittent reception of the satellite signals or low received signal strength of the satellite signals, among other things.
  • the imaging devices may be subject to transitory sunlight, shading, dust, reflections or other lighting conditions that can temporarily disrupt proper operation of the imaging devices; hence, potentially produce errors in estimated ranges to objects observed by the imaging devices.
  • transitory sunlight, shading, dust, reflections or other lighting conditions that can temporarily disrupt proper operation of the imaging devices; hence, potentially produce errors in estimated ranges to objects observed by the imaging devices.
  • the system and method facilitates the transfer of agricultural material from a transferring vehicle (e.g., harvesting vehicle) to a receiving vehicle (e.g., grain cart).
  • a transferring vehicle e.g., harvesting vehicle
  • a receiving vehicle e.g., grain cart
  • the system and method comprises a receiving vehicle, which has a propelled portion for propelling the receiving vehicle and a storage portion for storing agricultural material and a transferring vehicle for transferring harvested agricultural material into the storage portion of the receiving vehicle.
  • Two embodiments of the present invention include one primary imaging device on the receiving vehicle, and one secondary imaging device on the transferring vehicle, either a combine or a self-propelled forge harvester.
  • a first embodiment mounts one secondary imaging device is on the combine (a transferring vehicle) and one primary imaging device mounted on the receiving vehicle.
  • a second embodiment mounts one secondary imaging device on the self-propelled forge harvester, also a transferring vehicle, and one primary imaging device on the receiving vehicle.
  • Embodiments of the present invention include a first (primary) imaging device that is mounted at a first location on the receiving vehicle facing towards the storage portion of the receiving vehicle.
  • the first imaging device collects first image data.
  • a second (secondary) imaging device is associated with a second location on (e.g., mounted on or movably attached to) the transferring vehicle facing towards the storage portion of the receiving vehicle.
  • the second imaging device collects second image data.
  • the arrangement of the first and second imaging devices is a matter of user choice and not a limiting aspect of the invention, the description of the operation of the present invention will be in terms of the first imaging device being positioned on the receiving vehicle and the second imaging device being positioned on the transferring vehicle for illustration purposes only.
  • the first and secondary imaging devices can be positioned on either vehicle providing there is at least one imaging device on each vehicle.
  • the systems of the transferring and receiving vehicles will include an image processing module having a container or bin identification module that can identify a container or bin perimeter of the storage portion in at least one of the collected first image data and the collected second image data (where a second imaging device is incorporated into the system configuration).
  • the image processing can also include a spout localizer that is adapted to identify a spout of the transferring vehicle in the collected image data (collected first image data, collected second image data, or both).
  • the image processing module can include an image data evaluator that determines whether to use the first image data, the second image data or both (where a second imaging device is incorporated into the system configuration), based on an evaluation of material variation of intensity of pixel data or material variation in ambient light conditions during a sampling time interval.
  • the image data evaluator is either not activated, is not incorporated into the system, or includes logic that passes the only collected image to the next function.
  • the image processing module can also include an alignment module that is adapted to determine the relative position of the spout and the container perimeter, and to generate command data to the steering controller of the transferring vehicle to steer the transferring vehicle in cooperative alignment with the receiving vehicle such that the spout is aligned within a central zone (or other target zone) of the container perimeter.
  • an alignment module that is adapted to determine the relative position of the spout and the container perimeter, and to generate command data to the steering controller of the transferring vehicle to steer the transferring vehicle in cooperative alignment with the receiving vehicle such that the spout is aligned within a central zone (or other target zone) of the container perimeter.
  • a method for facilitating the transfer of material from a transferring vehicle having a material distribution end to a receiving vehicle having a bin to the store transferred material comprising the steps of:
  • d determining subsequent target areas of the bin that require material based on the representation of the fill level or volumetric distribution of the material in the bin and a desired fill pattern (such as front-to-back, back-to-front, center-to-front-to-back, center-to-back-to-front) to fill the bin;
  • a desired fill pattern such as front-to-back, back-to-front, center-to-front-to-back, center-to-back-to-front
  • FIG. 1 is a block diagram of one embodiment of a machine vision-augmented guidance system for a transferring vehicle being a combine for facilitating the unloading of agricultural material from the transferring vehicle (e.g., combine);
  • FIG. 2 is a block diagram of another embodiment of a machine vision-augmented guidance for a transferring vehicle being a self-propelled forge harvester for facilitating the unloading of agricultural material from the transferring vehicle;
  • FIG. 3 is a block diagram of an embodiments of machine vision- augmented guidance systems for a receiving vehicle for facilitating the unloading of agricultural material from a transferring vehicle to the receiving vehicle (e.g., grain cart and tractor);
  • a receiving vehicle e.g., grain cart and tractor
  • FIG. 4 is a schematic illustrating the data flow and processing by the image processing module from raw images to vehicle commands
  • FIG. 5A illustrates a top view of an imaging devices mounted on a transferring vehicle and facing toward a receiving vehicle
  • FIG. 5B illustrates a view in a horizontal plane as viewed along reference line 5B-5B in FIG. 5A;
  • FIG. 5C illustrates a two-dimensional representation of various possible illustrative distributions of material in the interior of a container (or bin) or storage portion, consistent with a cross-sectional view along reference line 4D-4D in FIG. 4B;
  • FIG. 5D is a top view of a transferring vehicle and a receiving vehicle, where the transferring vehicle is aligned within a matrix of possible offset positions;
  • FIG. 5E illustrates a block diagram of a container identification process using rectified images
  • FIG. 5F illustrates a block diagram of a container identification process capable of using rectified images and disparity images
  • FIG. 6A is a block diagram of a spout localizing process using rectified images and spout position data
  • FIG. 6B is a block diagram of a spout localizing process using rectified images, disparity images, and spout position data.
  • FIG. 7 is a flow chart of a method for operating a machine vision-augmented guidance system for facilitating the unloading of agricultural material from a transferring vehicle.
  • FIGS. 1 and 2 show machine vision augmented guidance systems 1 1 , 1 1 1 for a transferring vehicle 91 for managing the unloading of agricultural material (e.g., grain) from the transferring vehicle 91 (Fig. 1- combine; Fig. 2 - self-propelled forge harvester) to a receiving vehicle 79.
  • FIG. 3 shows a similar machine vision augmented guidance system 31 1 for a receiving vehicle 79 for managing the unloading of agricultural material (e.g., grain) from the transferring vehicle 91 to a receiving vehicle 79.
  • FIG. 5A illustrates a top view of a transferring vehicle 91 and a receiving vehicle 79.
  • the transferring vehicle 91 is shown as a combine with a harvesting head 185, whereas the receiving vehicle 79 is shown as a tractor and a grain cart.
  • the transferring vehicle 91 may comprise other vehicles such as a harvester or other heavy equipment that collects or harvests material for transfer to the receiving vehicle.
  • the receiving vehicle 79 can comprise the combination of a propulsion unit 75 and a storage unit 93 (e.g., a towed storage unit).
  • the spout 89 is generally aligned over a central zone 83, central region or target area with the grid pattern (not shown) of the storage container 85 of the receiving vehicle 79 for unloading material from the transferring vehicle 91 to the receiving vehicle 79.
  • the spout 89 may also be referred to as an unloading auger.
  • the spout end 87 may be referred to as a boot.
  • the transferring vehicle 91 and the receiving vehicle 79 are aligned in position as shown, regardless of whether the vehicles move together in a forward motion (e.g., with coordinated or tracked vehicle headings) during harvesting, as is typical, or are stationary.
  • the receiving vehicle 79 includes system 31 1 that can comprise a first imaging device 10 coupled to an image processing module 18 (Fig. 3).
  • the transferring vehicle 91 includes systems 1 1 , 1 1 1 that can comprise a second imaging device 12 coupled to an image processing module 18 (Figs. 1 and 2).
  • Each imaging device 10, 12 includes an image rectifier 101 to transform the raw image into a rectified image.
  • the example of transferred material disclosed herein is agricultural material, the invention is not to be limited to agricultural material and is applicable to other materials such as coal and other minerals.
  • Embodiments of the first imaging device 10 may comprise a primary stereo camera or a monocular camera, while the second imaging device 12 may comprise a secondary stereo camera or a monocular camera.
  • the second imaging device 12 is a stereo camera and can be optional and provides redundancy to the first imaging device 10 in case of failure, malfunction or unavailability of image data from the first imaging device 10 when the first field of view 277 of the first imaging device 10 is sufficient to view within container 85.
  • the second imaging device with a second field of view of 477 is monocular and is required for a stereo image of the container or bin 85 when used in conjunction with an image from a monocular first imaging device 10 with the first field of view 277 sufficient to view within container 85.
  • imaging processing module or smart unloading controller 18 can be located in either the system architecture of the transferring vehicle 91 or the receiving vehicle 79 or both. Whether data is processed by imaging processing module or smart unloading controller 18 located on the system of transferring vehicle 91 or the system of receiving vehicle 79 or by both will depend on the end-user's specification.
  • a wirelessly link can be established between imaging device 10 of the receiving vehicle 79 and image processing module 18 of the transferring vehicle 91 to the provide the image data back to processing on the transferring vehicle 91.
  • the receiving vehicle 79 would just have the imaging device, some buffer memory, and a wireless transceiver of one side of the wireless link as shown in FIG. 3. Therefore, all of the processing can be performed on the transferring vehicle 91 and eliminate the image processing module 18 on the receiving vehicle.
  • the wireless protocol can be some variant of an IEEE 802.1 1 standard (e.g., 802. l lg or n) or an spread spectrum modulation (e.g., code division multiple access) to reduce interference, for example.
  • the imaging processing module or smart unloading controller 18 is located on both vehicles and only one imaging processing module or smart unloading controller 18 is used for processing data collected from imaging devices and the other imaging processing module or smart unloading controller 18 can be used as a backup or on an as-required basis.
  • FIG. 4 illustrates the data flow and processing by the image processing module 18 from the raw images to the transferring vehicle commands.
  • the dashed lines represent optional steps and/or modules. Modules are discussed in detail below.
  • Raw images can be collected by the imaging device 10, 12 (e.g. camera being either stereo or monocular). Some embodiments of the present invention only require one imaging device.
  • Raw images are processed through the image rectifier 101 to create rectified images.
  • Rectified images are processed by the image data evaluator 25 to provide an image quality score for the rectified image to determine if the image should be used in further processing by the alignment module 24.
  • Rectified images are also processed by the container identification module 20 and material profile module 27.
  • Rectified images can also be processed in conjunction with disparity images by the spout localizer 22 when a disparity image generator 103 is present. Otherwise, spout localizer 22 will only use the data stored in vehicle model 1000, which includes, but not limited to, data on the transferring vehicle 91 , dimensions of spout 89, and spout kinematic model. Spout localizer 22 also requires data about the vehicle state information, which includes, but not limited to, transferring vehicle speed, spout angle(s), auger drive on/ off status, and relative Global Positioning Satellite position of receiving vehicle 79 if machine synchronization is present.
  • vehicle model 1000 includes, but not limited to, data on the transferring vehicle 91 , dimensions of spout 89, and spout kinematic model.
  • Spout localizer 22 also requires data about the vehicle state information, which includes, but not limited to, transferring vehicle speed, spout angle(s), auger drive on/ off status, and relative Global Positioning Satellite position of receiving vehicle
  • Spout localizer 22 output is input into container identification module 20 and processed in conjunction with rectified images and disparity images (if provided) by container identification module 20 to determine container location and dimensions. Rectified images and disparity images (if provided) are processed in conjunction with container location and dimensions data from container identification module 20 by material profile module 27 to generate a fill profile of the container 85.
  • Alignment module 24 processes data generated by the container identification module 20, material profile module 27 in conjunction with the vehicle state information to generate vehicle commands such as transferring vehicle 91 speed/ steering, spout position, auger drive on/off status, and speed/ steering of the receiving vehicle 79 if machine synchronization is present to reposition the spout end 87 over the appropriate open area of the container 85 for even, uniform distribution of the agricultural material in container 85.
  • the receiving vehicle 79 and transferring vehicle 91 both have image processing modules 18, they could be in a master-slave configuration (e.g., with transferring vehicle with the master image processing module 18 that assigns tasks to the receiving vehicle slave image processing module 18 or a parallel processing configuration, which may require the devices to share common electronic memory on one vehicle via wireless link and which is quite complex.
  • a master-slave configuration e.g., with transferring vehicle with the master image processing module 18 that assigns tasks to the receiving vehicle slave image processing module 18 or a parallel processing configuration, which may require the devices to share common electronic memory on one vehicle via wireless link and which is quite complex.
  • first imaging device 10 for a receiving vehicle 79 comprises a monocular imaging device (e.g., digital camera) and the second imaging device 12 for a transferring vehicle 91 , such as a combine, comprises a monocular imaging device (e.g., digital camera) that provides first monocular image data and second monocular image data, respectively.
  • first imaging device 10 is a stereo camera
  • second imaging device 12 can be optional or redundant in case first imaging device 10 malfunctions or its image is poor.
  • the image processing module 18 of systems 1 1 , 1 1 1 , 31 1 can create a stereo image from the first monocular image data (e.g., right image data) and the second monocular image data (e.g., left image data) with reference to the relative position and orientation of the first imaging device 10 and the second imaging device 12.
  • the image processing module 18 determines: (1) at least two points on a common visual axis 479 (FIG. 5A) that bisects the lenses of both the first imaging device 10 and the second imaging device 12, and (2) a linear spatial separation 481 (FIG.
  • the virtual profile of the entire surface of the agricultural material in the storage portion 93 enables the systems 1 1 , 1 1 1 , 31 1 or imaging module 18 to intelligently execute a fill strategy for the storage portion 93 of the receiving vehicle 79.
  • the first imaging device 10 and the second imaging device 12 may provide digital data format output as stereo video image data or a series of stereo still frame images at regular or periodic intervals, or at other sampling intervals.
  • Each stereo image e.g., the first image data or the second image data
  • the first imaging device 10 has a first field of view 277 of the storage portion 93 of the receiving vehicle 79, where the first field of view 277 overlaps at least partially with a second field of view 477 of the second imaging device 12 (if present).
  • the first imaging device 10, the second imaging device 12, or both may comprise a charge-coupled device (CCD), a complementary metal-oxide semiconductor (CMOS) array, or another suitable device for detection or collection of image data.
  • CCD charge-coupled device
  • CMOS complementary metal-oxide semiconductor
  • an optical sensor 1 10, 1 12 (FIGS. 1-3) comprises a light meter, a photo-sensor, photo-resistor, photo-sensitive device, or a cadmium- sulfide cell.
  • a first optical sensor 1 10 may be associated with the first imaging device 10; a second optical sensor 1 12 may be associated with the second imaging device 12.
  • the first optical sensor 1 10 and the second optical sensor 1 12 each may be coupled to the image processing module 18.
  • the optical sensor 1 10, 1 12 provides a reading or level indicative of the ambient light in the field of view of its respective imaging device 10, 12.
  • the image processing module 18 may be coupled, directly or indirectly, to lights 14 (Fig.
  • the image processing module 18 may include a light controller 50 (Fig. 2) that comprises control drivers, relays or switches, which in turn control the activation or deactivation of lights 14 on the transferring vehicle 91.
  • the image processing module 18 may activate the lights 14, 52 on the transferring vehicle for illumination of the storage container 85 (FIG. 5A), spout 89 or both if an optical sensor 1 10, 1 12 or light meter indicates that an ambient light level is below a certain minimum threshold.
  • the optical sensor 1 10, 1 12 face toward the same direction as the lens or aperture of the imaging devices 10, 12.
  • vehicle controller 46 controls spout 89 that includes a rotation sensor 1 16 for sensing a spout rotation angle ( ⁇ ) in FIG. 5B of the spout 89 with respect to one or more axes of rotation, and a rotation actuator 122 for moving the spout 89 to change the spout rotation angle; hence, the spout 89 position with respect to the receiving vehicle 79 or its storage container 85.
  • the rotation actuator 122 may comprise a motor, a linear motor, an electro-hydraulic device, a ratcheting or cable-actuated mechanical device, or another device for moving the spout 89, or the spout end 87.
  • the spout rotation angle may comprise a simple angle, a compound angle or multi-dimensional angles that is measured with reference to a reference axis parallel to the direction of travel of the transferring vehicle.
  • the rotation actuator 122 comprises an electro-hydraulic device
  • the use of proportional control valves in the hydraulic cylinder of the electro-hydraulic device that rotates the spout (or changes the spout rotation angle) facilitates finer adjustments to the spout angle (e.g., a) than otherwise possible.
  • proportional control valves of the electro- hydraulic device support rotation actuator 122 for an even profile or distribution of unloaded agricultural material within the storage portion 93 or container or bin 85.
  • a vehicle controller 46 may be coupled to the vehicle data bus 60 to provide a data message that indicates when the auger drive 47 for unloading agricultural material from the transferring vehicle is activated and inactive.
  • the auger drive 47 may comprise an auger, an electric motor for driving the auger, and a rotation sensor for sensing rotation or rotation rate of the auger or its associated shaft.
  • the auger (not shown) is associated with a container for storing agricultural material (e.g., a grain tank) of a transferring vehicle 91. If the vehicle controller 46 (e.g., auger controller) indicates that the auger of the transferring vehicle 91 is rotating or active, the imaging processing module 18 activates the spout localizer 22 and container or bin identification module 20.
  • vehicle controller 46 may conserve data processing resources or energy consumption by placing the container identification module 20 and the spout identification module 22 in an inactive state (or standby mode) while the transferring vehicle 91 is harvesting, but not unloading, the agricultural material to the receiving vehicle 79.
  • the imaging processing module 18 or any other controller may comprise a controller, a microcomputer, a microprocessor, a microcontroller, an application specific integrated circuit, a programmable logic array, a logic device, an arithmetic logic unit, a digital signal processor, or another data processor and supporting electronic hardware and software.
  • the image processing module 18 comprises a disparity generator 103, a container identification module 20, a spout localizer 22, an alignment module 24, a material profile module 27, and a vehicle model 1000.
  • the image processing module 18 may be associated with a data storage device may comprise electronic memory, non-volatile random access memory, a magnetic disc drive, an optical disc drive, a magnetic storage device or an optical storage device, for example. If the container identification module 20, the spout localizer 22, the alignment module 24, material profile module 27, and vehicle model 1000, are software modules they are stored within the data storage device.
  • the container identification module 20 identifies a set of two- dimensional or three dimensional points (e.g., in Cartesian coordinates or Polar coordinates) in the collected image data or in the real world that define at least a portion of the container perimeter 81 of the storage portion 85 (FIG. 5A).
  • the set of two-dimensional or three dimensional points correspond to pixel positions in images collected by the first imaging device 10, the second imaging device 12, or both.
  • the container identification module 20 may use or retrieve container reference data.
  • Vehicle Module 100 can include container reference data comprising one or more of the following: reference dimensions (e.g., length, width, height), volume, reference shape, drawings, models, layout, and configuration of the container 85, the container perimeter 81 , the container edges 181 ; reference dimensions, reference shape, drawings, models, layout, and configuration of the entire storage portion 93 of receiving vehicle; storage portion wheelbase, storage portion turning radius, storage portion hitch configuration of the storage portion 93 of the receiving vehicle; and distance between hitch pivot point and storage portion wheelbase.
  • the container reference data may be stored and retrieved from the data storage device (e.g., non-volatile electronic memory).
  • the container reference data may be stored by, retrievable by, or indexed by a corresponding receiving vehicle identifier in the data storage device of the transferring vehicle systems 1 1 , 1 1 1. For each receiving vehicle identifier, there can be a corresponding unique container reference data stored therewith in the data storage device.
  • the container identification module 18 identifies the position of the container or bin 85 as follows. If the linear orientation of a set of pixels in the collected image data conforms to one or more edges 181 of the perimeter 81 of the container 85 as prescribed by the container reference data, the position of the container 85 has been identified.
  • a target zone, central region or central zone of the container opening 83 of the container 85 can be identified by dividing (by two) the distance (e.g., shortest distance or surface normal distance) between opposite sides of the container, or by identifying corners of the container and where diagonal lines that intercept the corners intersect, among other possibilities.
  • the central zone may be defined as an opening (e.g., circular, elliptical or rectangular) in the container with an opening surface area that is greater than or equal to the cross-sectional surface area of the spout end by a factor of at least two, although other surface areas fall within the scope of the claims.
  • the spout localizer 22 identifies one or more of the following: (1) the spout pixels on at least a portion of the spout 89, or (2) spout end pixels that are associated with the spout end 87 of the spout 89.
  • the spout identification module 22 may use color discrimination, intensity discrimination, or texture discrimination to identify background pixels from one or more selected spout pixels with associated spout pixel patterns or attributes (e.g., color or color patterns (e.g., Red Green Blue (RGB) pixel values), pixel intensity patterns, texture patterns, luminosity, brightness, hue, or reflectivity) used on the spout 89 or on the spout end 87 of the spout 89 for identification purposes.
  • color or color patterns e.g., Red Green Blue (RGB) pixel values
  • RGB Red Green Blue
  • the alignment module 24, the master controller 59, or both estimate or determine motion commands at regular intervals to maintain alignment of the spout 56 over the central zone, central region or target of the container 85 for unloading agricultural material.
  • the alignment module 24, the master controller 59, or both may send commands or requests to the transferring vehicle 91 with respect to its speed, velocity or heading to maintain alignment of the position of the transferring vehicle 91 with respect to the receiving vehicle 79.
  • the alignment module 24 may transmit a request for a change in a spatial offset between the vehicles 79, 91 to the master controller 59.
  • the master controller 59 or the coordination module 57 transmits a steering command or heading command to the steering controller 32, a braking or deceleration command to a braking system 34, and a propulsion, acceleration or torque command to a propulsion controller 40 to achieve the target spatial offset or change in spatial offset.
  • the alignment module 24 may regularly or periodically move, adjust or rotate the target zone or central zone during loading of the container 85 of the receiving vehicle to promote even filling, a uniform height, or uniform distribution of the agricultural material in the entire container 85, where the image processing module 18 identifies the fill state of the agricultural material in the image data from the material profile module 27.
  • the imaging module 18 may comprise material profile module 27 or a fill level sensor for detecting a one-dimensional, two-dimensional or three-dimensional representation of the fill level or volumetric distribution of the agricultural material in the container 85 or storage portion 93.
  • FIG. 5C shows various illustrative two-dimensional representations of the fill state of the container 85, or the distribution of agricultural material in the container 85, discussed in detail below.
  • the coordination module 57 or the steering controller 32 adjusts the relative position (of offset) of the transferring vehicle 91 to the receiving vehicle 79.
  • the alignment module 24, the coordination module 57 and the auger rotation system 1 16 may control the relative position of the spout 89 or the spout end 87 to the container perimeter 81 to achieve an even fill to the desired fill level.
  • rotator actuator 122 of the combine may adjust the spout angle (e.g., a first spout angle (a), a second spout angle ( ⁇ ), or a compound angle (a and ⁇ )) that the spout 89 makes with respect to a reference axis or reference coordinate system associated with the transferring vehicle 91 or a generally vertical plane associated with the direction of travel of the transferring vehicle 91 , where the spout 89 meets and rotates with respect to the vehicle.
  • the spout angle is controlled by spout controller 54 in communication with rotation sensor 1 16, tilt sensor 1 18, deflector sensor 120, rotation actuator 122, tilt actuator 124, and deflector actuator 126.
  • the spout end 87 may be adjusted for unloading agricultural material by shifting its spout angle or spout position, within the container perimeter 81 and a tolerance clearance from the container perimeter 81 within the container 85.
  • the spout end 87 may be adjusted by various techniques that may be applied alternately, or cumulatively.
  • the alignment module 24 adjusts the spout end 87 for unloading agricultural material by shifting its spout angle (e.g., a first spout angle (a), a second spout angle ( ⁇ ), or both (a and ⁇ ).
  • the spout end 87 may be adjusted regularly (e.g., in a matrix of one or more rows or columns of preset offset positions) for unloading agricultural material by shifting the spatial relationship between the transferring vehicle and the receiving vehicle by a fore and aft offset or a lateral offset to achieve a target alignment or desired even distribution of filling the container 85 or storage portion 93 with agricultural material (Fig. 5D), while using the spout angle adjustment for fine tuning of the distribution of the agricultural material within the container (e.g., from each position within the matrix).
  • the image data evaluator 25 comprise an evaluator, a judging module, Boolean logic circuitry, an electronic module, a software module, or software instructions for determining whether to use the first image data, the second image data, or both for alignment of a relative position of the spout and the container perimeter (or alignment of the spatial offset between the vehicles) based on evaluation of material variation of intensity of pixel data or material variation in ambient light conditions during a sampling time interval.
  • master controller 59 is coupled to the vehicle data bus (e.g., 60). Whereas in the self-propelled forge harvester, master controller 59 is coupled to the implement data base 58 that is connected to vehicle data bus 60 via gateway 29.
  • the master controller 59 comprises an auto-guidance module 55 and coordination module 57.
  • the auto-guidance module 55 or master controller 59 can control the transferring vehicle 91 in accordance with location data from the first location determining receiver 42 and a path plan or desired vehicle path (e.g., stored in data storage).
  • the auto-guidance module 55 or master controller 59 sends command data to the steering controller 32, the braking controller 36 and the propulsion controller 40 to control the path of the transferring vehicle 91 to track automatically a path plan or to track manually steered course of an operator via the user interface 44 or steering system 30.
  • the transferring vehicle 91 in one embodiment in a leader mode, is steered by the auto-guidance module 55 or the steering controller 32 in accordance with path plan, or by a human operator. If the transferring vehicle 91 operates in an automated mode or auto-steering mode, the master controller 59 provides command data locally to the steering controller 32, braking controller 36, and propulsion engine controller 40 of the transferring vehicle 91. In an automated mode and in a leader-follower mode, the transferring vehicle 91 is steered and aligned automatically during transfer of agricultural material from the transferring vehicle 91 to the receiving vehicle 79.
  • the image processing module 18 provides image data (rectified, disparity, or both) to a user interface processing module 26 that provides, directly or indirectly, status message data and performance message data to a user interface 44.
  • a location determining receiver 42, a first wireless communications device 48, a vehicle controller 46, a steering controller 32, a braking controller 36, and a propulsion controller 40 are capable of communicating over the vehicle data bus 60.
  • the steering controller 32 is coupled to a steering system 30 of the transferring vehicle 91 ;
  • the braking controller 36 is coupled to the braking system 34 of the transferring vehicle 91 ;
  • the propulsion controller 40 is coupled to the propulsion system 38 of the transferring vehicle 91.
  • the steering system 30 may comprise an electrically-driven steering system, an electro-hydraulic steering system, a gear driven steering system, a rack and pinion gear steering system, or another steering system that changes the heading of the transferring vehicle 91 or one or more wheels of the transferring vehicle 91.
  • the braking system 34 may comprise a regenerative braking system, an electro-hydraulic braking system, a mechanical breaking system, or another braking system capable of stopping the vehicle by hydraulic, mechanical, friction or electrical forces.
  • the propulsion system 38 may comprise one or more of the following: (1) the combination of an electric motor and an electric controller, (2) internal combustion engine that is controlled by an electronic fuel injection system or another fuel metering device that can be controlled by electrical signals, or (3) a hybrid vehicle in which an internal combustion engine drives a electrical generator, which is coupled to one or more electric drive motors.
  • one or more imaging devices 10, 12 are arranged to collect image data.
  • a container identification module 20 identifies a container perimeter 81 of the storage portion 93 in the collected image data.
  • the storage portion 93 has an opening inward from the container perimeter for receipt of the agricultural material.
  • a spout localizer 22 is configured to identify a spout 89 of the transferring vehicle 91 in the collected image data.
  • An alignment module 24 is adapted for determining the relative position of the spout 89 and the container perimeter 81 and for generating command data to the transferring vehicle 91 to steer the transferring vehicle 91 in cooperative alignment with receiving vehicle 79 (or steer the receiving vehicle 79 in cooperative alignment with transferring vehicle 91) such that the spout 89 is aligned within a central zone 83 or opening of grid pattern 82 of the container perimeter 81.
  • a steering controller 32 is associated with a steering system 30 of the transferring vehicle 91 and receiving vehicle 79 for steering the transferring vehicle 91 and/ or receiving vehicle in accordance with the cooperative alignment.
  • an optional mast controller 674 is coupled to the vehicle data bus 60 (FIG. 1), or the implement data bus 58 (FIGS. 2 and 3) to control an optional adjustable mast 573 for mounting and adjustably positioning the first imaging device 10, the second imaging device 12, or both.
  • the mast controller 674 is adapted to change the orientation or height above ground of the first imaging device 10, the second imaging device 12 or both, where the orientation may be expressed as any of the following: a tilt angle, a pan angle, a down-tilt angle, a depression angle, or a rotation angle.
  • a machine-vision guidance system 1 1 , 1 1 1 , 31 1 that has an adjustable mast 573
  • at least one imaging device 10, 12 faces towards the storage portion 93 of the receiving vehicle 79 and collects image data.
  • the adjustable mast 573 is capable of adjusting a height of the imaging device 10, 12 within a height range, adjusting a down-tilt angle of the imaging device 10, 12 within a down-tilt angular range, and a rotational angle or pan angle within a pan angular range.
  • the image processing module 18 is adapted or programmed (e.g., with software instructions or code) to determine whether to adjust the height of the imaging device 10, 12 or whether to decrement or increment the down-tilt angle of the imaging device 10, 12 based on evaluation of material variation of intensity of pixel data or material variation in ambient light conditions (e.g., from the optical sensor 1 10, 1 12) during a sampling time interval. Under certain operating conditions, such as outdoor ambient light conditions, increasing or incrementing the down-tilt angle may increase the quality level of the collected image data or reduce variation in the intensity of the image data to below a threshold variation level.
  • a container identification module 20 can identify a container perimeter 81 of the storage portion 93 in the collected image data.
  • a spout localizer 22 can identify a spout of the transferring vehicle 91 in the collected image data.
  • An alignment module 24 determines the relative position of the spout 89 and the container perimeter 81 , and generates command data to the steering controller 32 to steer the transferring vehicle 91 in cooperative alignment with the receiving vehicle 79 such that the spout 89, or spout end 87, is aligned within a target zone of the grid pattern (not shown) or central zone 83 of the container perimeter 81.
  • the image processing module 18 sends a data message to a mast controller 674 (or the adjustable mast 573) to increment or increase the down-tilt angle if the material variation of intensity of pixel data or if the material variation in ambient light conditions exceeds a threshold variation level during a sampling time interval.
  • the image processing module 18 sends a data message to a mast controller 674 to increment or increase the down-tilt angle at discrete levels (e.g., one degree increments or decrements) within an angular range of approximately negative ten degrees to approximately negative twenty-five degrees from a generally horizontal plane.
  • the second imaging device 12 If the second imaging device 12 is elevated or mounted on the transferring vehicle 91 sufficiently high with respect to the storage portion 93, the second imaging device 12 will have visibility or second downward field of view 677 into the storage portion 93 or container 85 sufficient to observe and profile the surface (or height (z) versus respective x, y coordinates in the container) of the agricultural material (e.g., grain) as the agricultural material fills the storage portion 85.
  • the second imaging device 12 may be mounted on the roof of the transferring vehicle 91 facing or looking directly away from the side of the transferring vehicle 91 with the spout 89 for unloading agricultural material.
  • the optical axis, perpendicular to respective lens, of the second imaging device 12 is tilted downward from generally horizontal plane at a down-tilted angle ( ⁇ ) (e.g., approximately 10 to 25 degrees downward). If a field of view or optical axis of the second imaging device 12 is tilted downward from a generally horizontal plane, there are several advantages. First, less of the sky is visible in the field of view of the second imaging device 12 such the collected image data tends to have a more uniform image intensity profile.
  • the tilted configuration of the optical axis or axes (which is perpendicular to the lens of the second imaging device 12) is well suited for mitigating the potential dynamic range issues caused by bright sunlight or intermediate cloud cover, for instance.
  • the bottom part of the storage portion 93 becomes more visible in the image data to enable the recording of the image data related to one or more wheels of the storage portion 93.
  • the wheel is a feature on the storage portion 93 that can be robustly tracked by image processing techniques.
  • tilting the stereo camera down may mitigate the accumulation of dust and other debris on the lens or external window of the imaging device 10, 12.
  • FIG. 5C illustrates a two-dimensional representation of various possible illustrative distributions of material in the container 85, consistent with a view along reference line 5B in FIG. 5A.
  • the y axis is coincident with the longitudinal axis or direction of travel of the container
  • the z axis is coincident with the height of material in the container
  • the x axis is perpendicular to the direction of travel of the container, where the x, y and z axes are generally mutually orthogonal to each other.
  • the vertical axis is the mean height (Z) 500 of the material in the container 85
  • the horizontal axis represents the longitudinal axis (y) 502 of the container 85.
  • the maximum capacity 504 or container capacity is indicated by the dashed line on the vertical axis.
  • the front 512 of the container 85 is located at the origin, whereas the back 514 of the container 85 is located on the vertical axis.
  • FIG. 5C shows three illustrative distributions of material within the container 85.
  • the first distribution is a bimodal profile 508 in which there are two main peaks in the distribution of material in the container 85.
  • the bimodal profile 508 is shown as a dotted line.
  • the bimodal profile 508 can occur where the spout angle adjustment is governed by an electro- hydraulic system with non-proportional valves.
  • the second distribution is the front- skewed modal profile 510 in which there is single peak of material toward the front of the container 85.
  • the front-skewed modal profile 510 is shown as alternating long and short dashes.
  • the second distribution may occur where the volume or length (y) of the container 85 is greater than a minimum threshold and where the relative alignment between the spout end 87 and the container 85 is generally stationary during a substantial portion of unloading of the material.
  • the third distribution is the target profile 508 which may be achieved by following a suitable fill strategy as disclosed in this document.
  • the spout angle may be adjusted to promote uniform distribution of the agricultural material in the container 85.
  • a user interface 44 is arranged for entering container reference data or dimensional parameters related to the receiving vehicle.
  • the container reference data or dimensional parameters comprise a distance between a trailer hitch or pivot point (which interconnects the propulsion unit 75 and the storage portion 93) and front wheel rotational axis of the storage portion 93 of the receiving vehicle 79.
  • FIGS. 1 and 2 further comprises an optional odometer sensor 440, and an optional inertial sensor 442, as illustrated by the dashed lines.
  • the odometer sensor 440 may comprise a magnetic rotation sensor, a gear driven sensor, or a contactless sensor for measuring the rotation of one or more wheels of the transferring vehicle to estimate a distance traveled by the transferring vehicle during a measurement time period, or a ground speed of the transferring vehicle.
  • the odometry sensor 440 may be coupled to the vehicle data bus 60 or an implement data bus 58.
  • the inertial sensor 442 may comprise one or more accelerometers, gyroscopes or other inertial devices coupled to the vehicle data bus 60 or an implement data bus 58.
  • the optional odometry sensor 440 and the optional inertial sensor 442 may augment or supplement position data or motion data provided by the first location determining receiver 42.
  • the vision-augmented guidance system 1 1 1 of FIG. 2 is similar to the system 1 1 of FIG. 1 ; except that the system 1 1 1 of FIG. 2 further comprises an implement data bus 58, a gateway 29, and light controller 50 and spout controller 54 coupled to the vehicle data bus 60 for the lights 14 and spout 89, respectively.
  • the light controller 50 controls the lights 14;
  • the spout controller 54 controls the spout 89 via a servo-motor, electric motor, or an electro-hydraulic mechanism for moving or adjusting the orientation or spout angle of the spout 89, or its spout end 87.
  • the implement data bus 58 may comprise a Controller Area Network (CAN) implement data bus.
  • CAN Controller Area Network
  • the vehicle data bus 60 may comprise a controller area network (CAN) data bus.
  • the implement data bus 58, the vehicle data bus 60, or both may comprise an ISO (International Organization for Standardization) data bus or ISOBUS, Ethernet or another data protocol or communications standard.
  • ISO International Organization for Standardization
  • the self-propelled forge harvester includes gateway 29 to support secure or controlled communications between the implement data bus 58 and the vehicle data bus 60.
  • the gateway 29 comprises a firewall (e.g., hardware or software), a communications router, or another security device that may restrict or prevent a network element or device on the implement data bus 58 from communicating (e.g., unauthorized communication) with the vehicle data bus 60 or a network element or device on the vehicle data bus 31 , unless the network element or device on the implement data bus 58 follows a certain security protocol, handshake, password and key, or another security measure.
  • the gateway 29 may encrypt communications to the vehicle data bus 60 and decrypt communications from the vehicle data bus 60 if a proper encryption key is entered, or if other security measures are satisfied.
  • the gateway 29 may allow network devices on the implement data bus 58 that communicate via an open standard or third party hardware and software suppliers, whereas the network devices on the vehicle data bus 60 are solely provided by the manufacturer of the transferring vehicle (e.g., self- propelled forage harvester) or those authorized by the manufacturer.
  • a first location determining receiver 42, a user interface 44, a user interface processing module 26, and the gateway 29 are coupled to the implement data bus 58, although in other embodiments such elements or network devices may be connected to the vehicle data bus 60.
  • Light controller 50 and spout controller 54 are coupled to the vehicle data bus 60.
  • the light controller 50 and spout controller 54 are coupled, directly or indirectly, to lights 14 on the transferring vehicle 91 and the spout 89 of the transferring vehicle 91 (e.g., self-propelled forage harvester), respectively.
  • the system of FIG. 2 is well suited for use or installation on a self-propelled forage harvester (SPFH), the system of FIG. 2 may also be applied to harvesters or other heavy equipment.
  • SPFH self-propelled forage harvester
  • FIG. 5D is a top view of a transferring vehicle 91 and a receiving vehicle 79, where the transferring vehicle 91 is aligned within a matrix 500 of possible offset positions 502, 504 between the transferring vehicle 91 and receiving vehicle 79.
  • the matrix 500 is a two-dimensional, 2 x 3 (2 columns by 3 rows) matrix of possible offset positions 502, 504. Although six possible matrix positions 502, 504 are shown, in alternate embodiments the matrix 500 may consistent of any number of possible offset positions greater than or equal to two.
  • the transferring vehicle 91 occupies a current offset position 504 in the first column at the second row of the matrix 500, whereas the other possible offset positions 502 are not occupied by the transferring vehicle 91.
  • the imaging processing module 18, or the master controller 59 of the transferring vehicle 91 can shift to any unoccupied or other possible offset positions 502 within the matrix 500 to promote or facilitate an even distribution of agricultural material within the container 85 or storage portion of the receiving vehicle 79.
  • the spatial separation 481 between the transferring vehicle 91 and the receiving vehicle 79 may be adjusted in accordance with the matrix 500 or another matrix of preset positions of spatial offset to promote even distribution of agricultural material in the storage portion of the receiving vehicle 79, where any matrix is associated with a unique, relative spatial separation 481 between the vehicles 79,91.
  • both the transferring vehicle 91 and the receiving vehicle 79 may be moving forward at approximately the same velocity and heading (e.g., within a tolerance or error of the control systems during harvesting), where the relative position of the receiving vehicle 79 is generally fixed or constant with respect to each position 502, 504 in the matrix 500 that the transferring vehicle 91 can occupy.
  • the receiving vehicle 79 may be shown as occupying a two dimensional matrix (e.g., 3 X 3 matrix, with three columns and three rows) of possible offset positions, while the position of the transferring vehicle 91 is generally fixed or constant with respect to each position of matrix that the receiving vehicle 79 could occupy.
  • the imaging processing module 18 can shift to any unoccupied or other possible offset positions within the matrix to promote or facilitate an even distribution of agricultural material within the container 85 or storage portion 93 of the receiving vehicle 79.
  • each of the blocks or modules may represent software modules, electronic modules, or both.
  • Software modules may contain software instructions, subroutines, object-oriented code, or other software content.
  • the arrows that interconnect the blocks or modules of FIG. 4 show the flow of data or information between the blocks.
  • the arrows may represent physical communication paths or virtual communication paths, or both.
  • Physical communication paths mean transmission lines or one or more data buses for transmitting, receiving or communicating data.
  • Virtual communication paths mean communication of data, software or data messages between modules.
  • the first imaging device 10, the second imaging device 12, or both provide input of raw stereo camera images (or raw image data) to the image rectification module 101.
  • FIG. 5E is a block diagram that shows raw camera (monocular or stereo) processed by image rectifier 101 to create rectified images for input into container identification module 20.
  • Optional input into container identification module 20 is spout localizer data 22.
  • FIGS. 5F is a block diagram that shows raw camera images (monocular or stereo) processed by image rectifier 101 to create a rectified image. The rectified image will be processed by the disparity image generator 103 to create ranges in the form of disparity data.
  • rectified images and disparity data are process by the spout localizer 22 with spout position data 1002.
  • Output from spout localizer 22 is input into container identification module 20.
  • data from spout localizer 22 can be input into container identification module 20 for a refinement in the material distribution in container or bin 85.
  • FIG. 6A is a block diagram that shows raw camera images (monocular or stereo) processed by an image rectifier 101 to create rectified images for input into spout localizer 22 for further processing with spout position data 1002 provided by vehicle model 1000.
  • Output data from spout localizer 22 can be input data for container identification module 20.
  • FIG. 6B is a block diagram that shows raw camera images (monocular or stereo) processed by an image rectifier 101 to create rectified images.
  • the rectified images will be processed by disparity generator 103 to create ranges in the form of disparity data.
  • rectified images and disparity data are processed by the spout localizer 22 along with spout position data 1002.
  • the output data of spout localizer 22 can be further processed by the container identification module 20.
  • the image rectification module 101 provides image processing to the collected image data or raw stereo images to reduce or remove radial lens distortion and image alignment required for stereo correspondence.
  • the radial lens distortion is associated with the radial lenses of the first imaging device 10, the second imaging device 12, or both.
  • the input of the image rectification module 101 is raw stereo image data, whereas the output of the image rectification module 101 is rectified stereo image data.
  • Like reference numbers in FIGS. 1 , 2, 5A, 5E, 5F, 6A, and 6B indicate like elements.
  • the image rectifier 101 eliminates or reduces any vertical offset or differential between a pair of stereo images of the same scene of the image data.
  • the image rectification module can align the horizontal component (or horizontal lines of pixels of the stereo images) to be parallel to the scan lines or common reference axis of each imaging device (e.g., left and right imaging device) within the first and second imaging devices 10, 12.
  • the image rectifier 101 can remap pixels from initial coordinates to revised coordinates for the right image, left image or both to achieve registration of the images or rectified right and left images of the stereo image.
  • the rectified image supports efficient processing and ready identification of corresponding pixels or objects within the image in the left image and right image of a common scene for subsequent image processing.
  • the disparity image generator 103 applies a stereo matching algorithm or disparity calculator to collected stereo image data, such as the rectified stereo image data outputted by the image rectifier 101.
  • the stereo matching algorithm or disparity calculator may comprise a sum of absolute differences algorithm, a sum of squared differences algorithm, a consensus algorithm, or another algorithm to determine the difference or disparity for each set of corresponding pixels in the right and left image (e.g., along a horizontal axis of the images or parallel thereto).
  • the right and left images can be shifted to align corresponding pixels in the right and left image.
  • the stereo matching algorithm or disparity calculator determines a disparity value between corresponding pixels in the left and right images of the image data. For instance, to estimate the disparity value, each first pixel intensity value of a first subject pixel and a first sum of the first surrounding pixel intensity values (e.g., in a block or matrix of pixels) around the first pixel is compared to each corresponding second pixel intensity value of second subject pixel and a second sum of the second surrounding pixel intensity values (e.g., in a block or matrix of pixels) around the second pixel.
  • the disparity values can be used to form a disparity map or image for the corresponding right and left image data.
  • a container localizer estimates a distance or range from the first imaging device 10, the second imaging device 12, or both to the pixels or points lying on the container perimeter 81 , on the container edge 181 , on the spout 89, on the spout end 87, or on any other linear edge, curve, ellipse, circle or object identified by the edge detector, the linear Hough transformer, or both.
  • the image processing module 18 may use the disparity map or image to estimate a distance or range from the first imaging device 10, the second imaging device 12, or both to the pixels or points lying on the container perimeter 81 , the container edges 181 , the container opening 83, in the vicinity of any of the foregoing items, or elsewhere.
  • the container identification module 20 comprises: (1) an edge detector for measuring the strength or reliability of one or more edges 181 , or points on the container perimeter 81 in the image data; (2) a linear Hough transformer for identifying an angle and offset of candidate linear segments in the image data with respect to a reference point on an optical axis, reference axis of the one or more imaging devices 10, 12; (3) a container localizer adapted to use spatial and angular constraints to eliminate candidate linear segments that cannot logically or possibly form part of the identified linear segments of the container perimeter 81 , or points on the container perimeter 81 ; and (4) the container localizer transforms the non-eliminated, identified linear segments, or identified points, into two or three dimensional coordinates relative to a reference point or reference frame of the receiving vehicle and harvesting vehicle.
  • the edge detector may apply an edge detection algorithm to rectified image data from the image rectifier 101. Any number of suitable edge detection algorithms can be used by the edge detector.
  • Edge detection refers to the process of identifying and locating discontinuities between pixels in an image or collected image data.
  • the discontinuities may represent material changes in pixel intensity or pixel color which defines boundaries of objects in an image.
  • a gradient technique of edge detection may be implemented by filtering image data to return different pixel values in first regions of greater discontinuities or gradients than in second regions with lesser discontinuities or gradients.
  • the gradient technique detects the edges of an object by estimating the maximum and minimum of the first derivative of the pixel intensity of the image data.
  • the Laplacian technique detects the edges of an object in an image by searching for zero crossings in the second derivative of the pixel intensity image.
  • suitable edge detection algorithms include, but are not limited to, Roberts, Sobel, and Canny, as are known to those of ordinary skill in the art.
  • the edge detector may provide a numerical output, signal output, or symbol, indicative of the strength or reliability of the edges 181 in field.
  • the edge detector may provide a numerical value or edge strength indicator within a range or scale or relative strength or reliability to the linear Hough transformer.
  • the linear Hough transformer receives edge data (e.g., an edge strength indicator) related to the receiving vehicle and identifies the estimated angle and offset of the strong line segments, curved segments or generally linear edges (e.g., of the container 85, the spout 89, the spout end 87 and opening 83) in the image data.
  • the estimated angle is associated with the angle or compound angle (e.g., multidimensional angle) from a linear axis that intercepts the lenses of the first imaging device 10, the second image device 12, or both.
  • the linear Hough transformer comprises a feature extractor for identifying line segments of objects with certain shapes from the image data.
  • the linear Hough transformer identifies line equation parameters or ellipse equation parameters of objects in the image data from the edge data outputted by the edge detector, or Hough transformer classifies the edge data as a line segment, an ellipse, or a circle.
  • Hough transformer classifies the edge data as a line segment, an ellipse, or a circle.
  • the data manager supports entry or selection of container reference data by the user interface 44.
  • the data manager supports entry, retrieval, and storage of container reference data, such as measurements of cart dimensions, by the image processing module 18 to give spatial constraints to the container localizer on the line segments or data points that are potential edges 181 of the cart opening 83.
  • the angle estimator may comprise a Kalman filter or an extended Kalman filter.
  • the angle estimator estimates the angle of the storage portion 93 (e.g., cart) of the receiving vehicle 79 to the axis of the direction of travel of the propelled portion 75 (e.g., tractor) of the receiving vehicle 79.
  • the angle estimator e.g., Kalman filter
  • the angle estimator or Kalman filter is coupled to the container localizer .
  • the angle estimator filter outputs, or is capable of providing, the received estimated angle of the storage portion 93 relative to the axis of the direction of travel of the propelling portion 75 of the vehicle.
  • the container localizer is adapted to receive measurements of dimensions of the container perimeter 81 or the storage portion 93 of the vehicle to facilitate identification of candidate linear segments that qualify as identified linear segments of the container perimeter 81.
  • the container localizer is adapted to receive an estimated angle of the storage portion 93 relative to the propelling portion 75 of the vehicle to facilitate identification of candidate linear segments that qualify as identified linear segments of the container perimeter 81.
  • the container localizer uses spatial and angular constraints to eliminate candidate lines in the image data that cannot be possibly or logically part of the container opening 83 or container edges 181 , then selects preferential lines (or data points on the container edge 81) as the most likely candidates for valid container opening 83 (material therein) or container edges 181.
  • the container localizer characterizes the preferential lines as, or transformed them into, three dimensional coordinates relative to the vehicle or another frame of reference to represent a container perimeter of the container 85.
  • the spout localizer 22 comprises a spout classifier that is configured to identify candidate pixels in the image data based at least one of reflectivity, intensity, color or texture features of the image data (or pixels), of the rectified image data or raw image data, where the candidate pixels represent a portion of the spout 89 or spout end 87.
  • the spout localizer 22 is adapted to estimate a relative position of the spout 89 to the imaging device based on the classified, identified candidate pixels of a portion of the spout 89.
  • the spout localizer 22 receives an estimated combine spout position or spout angle (a) relative to the mounting location of the imaging device, or optical axis, or reference axis of one or more imaging devices, based on previous measurements to provide constraint data on where the spout 89 can be located possibly.
  • the spout classifier applies or includes software instructions on an algorithm that identifies candidate pixels that are likely part of the spout 89 or spout end 87 based on expected color and texture features within the processed or raw image data.
  • the spout end 87 may be painted, coated, labeled or marked with a coating or pattern of greater optical or infra-red reflectivity, intensity, or luminance than a remaining portion of the spout 89 or the transferring vehicle.
  • the greater luminance, intensity or reflectivity of the spout end 87 may be attained by painting or coating the spout end 87 with white, yellow, chrome or a lighter hue or shade with respect to the remainder of the spout 89 or portions of the transferring vehicle within the field of view of the imaging devices 10, 12.
  • the spout position estimator comprises a Kalman filter or an extended Kalman filter that receives input of previous measurements and container reference data and outputs an estimate of the spout position, spout angle, or its associated error.
  • the spout position estimator provides an estimate of the combine spout position, or spout angle, or its error, relative to one or more of the following: (1) the mounting location or pivot point of the spout on the transferring vehicle, or (2) the optical axis or other reference axis or point of the first imaging device 10, the second imaging device 12, or both, or (3) the axis associated with the forward direction of travel or the heading of the transferring vehicle.
  • the Kalman filter outputs constraints on where the spout 89 or spout end 87 can be located, an estimated spout position, or a spout location zone or estimated spout position zone.
  • the spout position estimator or Kalman filter is coupled to the spout localizer 22.
  • the spout localizer 22 takes pixels that are classified as belonging to the combine auger spout 89 and uses a disparity image from disparity image generator 103 to estimate the relative location of the spout to the first imaging device 10, the second imaging device 12, or both, or reference axis or coordinate system associated with the vehicle.
  • FIG. 7 is a flow chart of a method for facilitating the unloading of agricultural material from a vehicle or between a transferring vehicle 91 and a receiving vehicle 79.
  • the method of FIG. 7 may use one or more of the following embodiments of the systems 1 1 , 1 1 1 , 31 1 previously disclosed herein.
  • the first imaging device 10 faces toward the storage portion of the receiving vehicle 79 (e.g., grain cart) and collects first image data (e.g., first stereo image data, first monocular image data, or a right image of a stereo image).
  • first image data e.g., first stereo image data, first monocular image data, or a right image of a stereo image.
  • the first imaging device 10 may be mounted on the body of transferring vehicle 91 facing the receiving vehicle 79 and facing the container 85.
  • the first imaging device 10 has first field of view 277 or view 477 of the storage portion of the receiving vehicle 79 (FIGS. 5A and 5B).
  • the first imaging device 10 comprises a monocular imaging device that provides a first image section (e.g., left image) of stereo image data of a scene or an object.
  • a first image section e.g., left image
  • the optional second imaging device 12 faces toward the storage portion 93 of the receiving vehicle 79 (e.g., grain cart) and collects second image data (e.g., second stereo image data, second monocular image data, or a left image of a stereo image).
  • the second imaging device 12 may be mounted on the body of the transferring vehicle 91 facing the receiving vehicle 79 (FIGS. 3 and 4A).
  • the second imaging device 12 has a second field of view 677 of the storage portion of the receiving vehicle, where the first field of view 277 overlaps at least partially with the second field of view 677, respectively.
  • the second imaging device 12 comprises a monocular imaging device that provides a second image section (e.g., right image) of stereo image data of a scene or an object, where the image processing module 18 supports the creation of a stereo image from a combination of the first image section (of the first monocular imaging device) and the second image section with reference to the relative position and orientation of the first imaging device 10 and the second imaging device 12.
  • a monocular imaging device that provides a second image section (e.g., right image) of stereo image data of a scene or an object
  • the image processing module 18 supports the creation of a stereo image from a combination of the first image section (of the first monocular imaging device) and the second image section with reference to the relative position and orientation of the first imaging device 10 and the second imaging device 12.
  • an image processing module 18 or a container identification module 20 identifies a container perimeter 81 of the storage portion 93 in the collected image data (e.g., the first image data, the second image data or both), where the storage portion 93 has an opening 83 inward from the container perimeter 81 for receipt of the agricultural material.
  • Step S906 may be carried out in accordance with various techniques, which may be applied alternately or cumulatively.
  • the image processing module 18 or container identification module 20 may employ the following processes or sub-steps: (1) measuring a strength of one or more edges 181 in the image data (raw and rectified image data); (2) identifying an angle and offset of candidate linear segments in the image data with respect to an optical axis, reference axis (e.g., direction of travel of the transferring vehicle), or reference point indexed to one or more imaging devices 10, 12; and (3) using spatial and angular constraints to eliminate identified candidate linear segments that cannot logically or possibly form part of the identified linear segments of the container perimeter, where the container identification module 20 transforms the identified linear segments into three dimensional coordinates relative to a reference point or reference frame of the receiving vehicle and/ or the harvesting vehicle.
  • the image processing module 18 or container identification module 20 may receive container reference data, or measurements of dimensions of the container perimeter 81 or the storage portion 93 of the vehicle, to facilitate identification of candidate linear segments, or candidate data points, that qualify as identified linear segments of the container perimeter 81.
  • the image processing module 18 or container identification module 20 may receive an estimated angle of the storage portion 93 relative to the propelling portion 75 of the vehicle to facilitate identification of candidate linear segments that qualify as identified linear segments of the container perimeter 81.
  • the image processing module 18 or container identification module 20 provides the received estimated angle of the storage portion 93 relative to the propelling portion 75 of the vehicle.
  • the image processing module 18 or a spout localizer 22 identifies a spout 89 (or spout end 87) of the transferring vehicle 91 in the collected image data.
  • the image processing module 18 or the spout localizer 22 may use various techniques, which may be applied alternately or cumulatively. Under a first technique, the image processing module 18 or the spout localizer 22 identifies candidate pixels in the image data (e.g., rectified or raw image data) based on expected color and expected texture features of the image data, where the candidate pixels represent a portion of the spout 89 (e.g., combine auger spout) or spout end 87.
  • the image processing module 18 or the spout identification module 22 estimates a relative position, or relative angle, of the spout 89 or the spout end 87, to the imaging device based on the classified, identified candidate pixels of a portion of the spout 89.
  • the image processing module 18 or the spout identification module 22 receives an estimated combine spout position, or spout angle, relative to the mounting location, optical axis, reference axis, or reference point of the imaging device 10, 12 based on previous measurements to provide constraint data on where the spout 89 can be located possibly.
  • the image processing module 18 or spout localizer 22 provides the estimated combine spout position, or estimated spout angle, to the container identification module 20.
  • step S910 the image data evaluator 25 or image processing module 18 determines whether to use the first image data, the second image data or both, based on an evaluation of the intensity of pixel data or ambient light conditions.
  • Step S910 may be carried out in accordance with various techniques, which may be applied alternately or cumulatively.
  • a first optical sensor 1 10 is associated with the respective first imaging device 10; the image data evaluator 25 or image processing module 18 decides to use the first image data if the variation in ambient light over a sampling time interval (e.g., commensurate with a sampling rate of 1 to 120 samples per second) is less than or equal to a maximum ambient light variation, as measured by the first optical sensor 1 10.
  • a sampling time interval e.g., commensurate with a sampling rate of 1 to 120 samples per second
  • the first image data is collected solely by the first imaging device 10.
  • a background level, mean level, or mode level of variation in the ambient light in the image data, a block of pixels in the first image data, or an object within the image data may be gathered or tracked during operation or normal operation of the systems 1 1 , 1 1 1 , 31 1.
  • the maximum ambient light level is set to be greater than the background level, mean level, or mode level.
  • the maximum ambient light level (e.g., within the visible light spectrum, near- infrared spectrum, or infrared spectrum) is set to be greater by statistical measure (e.g., approximately one to two standard deviations above the background level), mean level or mode level, or a signal level difference between the maximum ambient light level and the mean level of equal to or greater than a threshold level (e.g., within a range of approximately 3 decibels to 6 decibels).
  • statistical measure e.g., approximately one to two standard deviations above the background level
  • mean level or mode level e.g., approximately one to two standard deviations above the background level
  • a threshold level e.g., within a range of approximately 3 decibels to 6 decibels.
  • the image data evaluator 25 or image processing module 18 decides to use the second image data if the variation in ambient light over a sampling time interval (e.g., commensurate with a sampling rate of 1 to 120 samples per second) is less than or equal to a maximum ambient light variation, as measured by the second optical sensor 1 12.
  • a sampling time interval e.g., commensurate with a sampling rate of 1 to 120 samples per second
  • the second image data is collected solely by the second imaging device 12.
  • a background level, mean level, or mode level of variation in the ambient light in the second image data, a block of pixels in the image data, or an object within the image data may be gathered or tracked during operation or normal operation of the systems 1 1 , 1 1 1 , 31 1.
  • the maximum ambient light level is set to be greater than the background level, mean level, or mode level.
  • the maximum ambient light level (e.g., within the visible light spectrum, near- infrared spectrum, or infrared spectrum) is set to be greater by statistical measure (e.g., approximately one to two standard deviations above the background level), mean level or mode level, or a signal level difference between the maximum ambient light level and the mean level of equal to or greater than a threshold level (e.g., within a range of approximately 3 decibels to 6 decibels).
  • statistical measure e.g., approximately one to two standard deviations above the background level
  • mean level or mode level e.g., approximately one to two standard deviations above the background level
  • a threshold level e.g., within a range of approximately 3 decibels to 6 decibels.
  • the image processing module 18, or the image data evaluator 25 decides to use the first image data of the first imaging device 10 if the variation in pixel intensity of a spout, a spout end, or a container in the first image over a sampling time interval is less than or equal to a maximum pixel intensity variation, as detected by the image processing module 18.
  • the image processing module 18, or the image data evaluator 25 decides to use the second image data of the second imaging device 12 if the variation in pixel intensity of a spout or spout end in the second image over a sampling time interval is less than or equal to a maximum pixel intensity variation, as detected by the image processing module 18.
  • the image processing module 18, the image data evaluator 25 is adapted for determining whether to use the first image data, the second image data or both, for the identification of the container perimeter and the identifying of the spout 89 (or spout end 87), based on pixel intensity in rejected image data being outside of a desired range or variation in pixel intensity during the sampling time interval, where the image processing module 18, the image data evaluator 25 or image processing module 18 is configured to disable selectively the processing or use of the rejected image data that comprises a portion of the collected first image data or the second image data that would otherwise be corrupted by one or more of the following conditions: (1) excessive transient sunlight during sunrise, sunset, or excessive light radiation from other sources (e.g., headlights from other vehicles), (2) transitory sunlight or cloud cover, (3) fog, precipitation or moisture, (4) shading (e.g., from vegetation, trees, buildings or plant canopies), (5) airborne dust or debris, (6) reflections of light (e.g.
  • step S912 the image processing module 18 or the alignment module 24 determines the relative position of the spout 89, or the spout end 87, and the container perimeter 81 and for generating command data to modulate the ground speed of the transferring vehicle 91 or reposition the spout 89 or both in cooperative alignment such that the spout 89 (or spout end 87) is aligned with a central zone 83 of the container perimeter 81.
  • the image processing module 18 may use, retrieve or access previously stored data, such as dimensional parameters related to the receiving vehicle, the dimensional parameters comprising a distance between a trailer hitch and front wheel rotational axis of the storage portion 93. Such dimensional parameters may be entered via a user interface 44 coupled to the vehicle data bus 60 or the image processing module 18, for example.
  • the imaging processing module 18 may use first location data of a first location determining receiver 42 on the transferring vehicle 91 to determine relative position between the spout and the container perimeter, and generate command data to modulate the ground speed of the transferring vehicle 91 or reposition the spout 89 or both in cooperative alignment such that the spout 89 is aligned within a central zone of the container perimeter 181 or a section of grid pattern 82.
  • step S914 in a first configuration, the controller 59 or the propulsion controller 40 modulates the ground speed of the transferring vehicle 91.
  • the vehicle controller 46 or the spout controller 54 repositions the spout 89.
  • the rotation actuator 122 e.g., a servo-motor, electric motor, linear motor and linear-to-rotational gear assembly, or electro-hydraulic device
  • both the speed of the transferring vehicle and the spout 89 is repositioned.

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Theoretical Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Multimedia (AREA)
  • Remote Sensing (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Automation & Control Theory (AREA)
  • Environmental Sciences (AREA)
  • Signal Processing (AREA)
  • Electromagnetism (AREA)
  • Transportation (AREA)
  • Quality & Reliability (AREA)
  • General Engineering & Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Geometry (AREA)
  • Combustion & Propulsion (AREA)
  • Chemical & Material Sciences (AREA)
  • Computational Mathematics (AREA)
  • Mathematical Optimization (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Evolutionary Biology (AREA)
  • Soil Sciences (AREA)
  • Evolutionary Computation (AREA)
  • Computing Systems (AREA)
  • Mathematical Analysis (AREA)
  • Artificial Intelligence (AREA)
  • Mathematical Physics (AREA)
  • Pure & Applied Mathematics (AREA)
  • Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
  • Traffic Control Systems (AREA)
  • Control Of Conveyors (AREA)
  • Automobile Manufacture Line, Endless Track Vehicle, Trailer (AREA)
  • Warehouses Or Storage Devices (AREA)
  • Guiding Agricultural Machines (AREA)

Abstract

First imaging device collects first image data, whereas second imaging device collects second image data of a storage portion. A container identification module identifies a container perimeter of the storage portion in at least one of the collected first image data and the collected second image data. A spout identification module is adapted to identify a spout of the transferring vehicle in the collected image data. An image data evaluator determines whether to use the first image data, the second image data, or both based on an evaluation of the intensity of pixel data or ambient light conditions. An alignment module is adapted to determine the relative position of the spout and the container perimeter and to generate command data to the propelled portion to steer the storage portion in cooperative alignment such that the spout is aligned within a central zone or a target zone of the container perimeter.

Description

SYSTEM AND METHOD OF MATERIAL HANDLING USING ONE OR MORE IMAGING DEVICES ON THE TRANSFERRING VEHICLE AND ON THE RECEIVING VEHICLE TO CONTROL THE MATERIAL DISTRIBUTION INTO THE STORAGE PORTION OF THE RECEIVING VEHICLE
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is an International Application claiming the priority of U.S. Provisional Application 61 /597,346, filed February 10, 2012, and U.S. Provisional Application 61 /597,374, filed February 10, 2012, and U.S. Provisional Application 61 /597,380, filed February 10, 2012, all are incorporated by reference herein
JOINT RESEARCH AGREEMENT
[0002] This application resulted from work performed under or related to a joint research agreement between Carnegie Mellon University and Deere & Company, entitled "Development Agreement between Deere & Company and Carnegie Mellon University," dated January 1 , 2008 and as such is entitled to the benefits available under 35 U.S.C. § 103(c).
FIELD OF THE INVENTION
[0003] This invention relates to a method and stereo vision system for facilitating the unloading of material from a vehicle.
BACKGROUND
[0004] Certain prior art systems may attempt to use global positioning system (GPS) receivers to maintain proper spacing between two vehicles during the unloading or transferring of agricultural material or other material, such as coal and other minerals, between the vehicles. However, such prior art systems are susceptible to misalignment of the proper spacing because of errors or discontinuities in the estimated position of the GPS receivers. For example, one or more of the GPS receivers may misestimate its position because of electromagnetic interference, multipath propagation of the received satellite signals, intermittent reception of the satellite signals or low received signal strength of the satellite signals, among other things. If the vehicles use cameras or other imaging devices in an outdoor work area, such as an agricultural field, the imaging devices may be subject to transitory sunlight, shading, dust, reflections or other lighting conditions that can temporarily disrupt proper operation of the imaging devices; hence, potentially produce errors in estimated ranges to objects observed by the imaging devices. Thus, there is a need for an improved system for managing the unloading of agricultural material from a vehicle to compensate for or address error in the estimated positions or alignment of the vehicles.
SUMMARY OF THE INVENTION
[0005] The system and method facilitates the transfer of agricultural material from a transferring vehicle (e.g., harvesting vehicle) to a receiving vehicle (e.g., grain cart). The system and method comprises a receiving vehicle, which has a propelled portion for propelling the receiving vehicle and a storage portion for storing agricultural material and a transferring vehicle for transferring harvested agricultural material into the storage portion of the receiving vehicle.
[0006] Two embodiments of the present invention include one primary imaging device on the receiving vehicle, and one secondary imaging device on the transferring vehicle, either a combine or a self-propelled forge harvester. A first embodiment mounts one secondary imaging device is on the combine (a transferring vehicle) and one primary imaging device mounted on the receiving vehicle. A second embodiment mounts one secondary imaging device on the self-propelled forge harvester, also a transferring vehicle, and one primary imaging device on the receiving vehicle.
[0007] Embodiments of the present invention include a first (primary) imaging device that is mounted at a first location on the receiving vehicle facing towards the storage portion of the receiving vehicle. The first imaging device collects first image data. A second (secondary) imaging device is associated with a second location on (e.g., mounted on or movably attached to) the transferring vehicle facing towards the storage portion of the receiving vehicle. The second imaging device collects second image data. Though the arrangement of the first and second imaging devices is a matter of user choice and not a limiting aspect of the invention, the description of the operation of the present invention will be in terms of the first imaging device being positioned on the receiving vehicle and the second imaging device being positioned on the transferring vehicle for illustration purposes only. The first and secondary imaging devices can be positioned on either vehicle providing there is at least one imaging device on each vehicle.
[0008] The systems of the transferring and receiving vehicles will include an image processing module having a container or bin identification module that can identify a container or bin perimeter of the storage portion in at least one of the collected first image data and the collected second image data (where a second imaging device is incorporated into the system configuration). The image processing can also include a spout localizer that is adapted to identify a spout of the transferring vehicle in the collected image data (collected first image data, collected second image data, or both). The image processing module can include an image data evaluator that determines whether to use the first image data, the second image data or both (where a second imaging device is incorporated into the system configuration), based on an evaluation of material variation of intensity of pixel data or material variation in ambient light conditions during a sampling time interval. In a system with only one imaging device, the image data evaluator is either not activated, is not incorporated into the system, or includes logic that passes the only collected image to the next function. The image processing module can also include an alignment module that is adapted to determine the relative position of the spout and the container perimeter, and to generate command data to the steering controller of the transferring vehicle to steer the transferring vehicle in cooperative alignment with the receiving vehicle such that the spout is aligned within a central zone (or other target zone) of the container perimeter. Each system will able to process images collected by its dedicated components and can have to ability to process images collected by its counterpart system.
[0009] In operation, a method for facilitating the transfer of material from a transferring vehicle having a material distribution end to a receiving vehicle having a bin to the store transferred material, the method comprising the steps of:
[0010] a. identifying and locating the bin;
[0011] b. detecting a representation of the fill level or volumetric distribution of the material in the bin;
[0012] c. aligning the material distribution end over a current target area of the bin requiring the material (wherein a current target area can be an initial target area the material distribution end is positioned when the filling of material begins);
[0013] d. determining subsequent target areas of the bin that require material based on the representation of the fill level or volumetric distribution of the material in the bin and a desired fill pattern (such as front-to-back, back-to-front, center-to-front-to-back, center-to-back-to-front) to fill the bin;
[0014] e. transferring the material from the transferring vehicle to the current target area of the bin of the receiving vehicle;
[0015] f. detecting when the current target area of the bin is filled with the material;
[0016] g. repeating steps c-f until the subsequent target areas of the bin are filled; and
[0017] h. terminating the transfer of the material from the transferring vehicle to the receiving vehicle. BRIEF DESCRIPTION OF THE DRAWINGS
[0018] FIG. 1 is a block diagram of one embodiment of a machine vision-augmented guidance system for a transferring vehicle being a combine for facilitating the unloading of agricultural material from the transferring vehicle (e.g., combine);
[0019] FIG. 2 is a block diagram of another embodiment of a machine vision-augmented guidance for a transferring vehicle being a self-propelled forge harvester for facilitating the unloading of agricultural material from the transferring vehicle;
[0020] FIG. 3 is a block diagram of an embodiments of machine vision- augmented guidance systems for a receiving vehicle for facilitating the unloading of agricultural material from a transferring vehicle to the receiving vehicle (e.g., grain cart and tractor);
[0021] FIG. 4 is a schematic illustrating the data flow and processing by the image processing module from raw images to vehicle commands;
[0022] FIG. 5A illustrates a top view of an imaging devices mounted on a transferring vehicle and facing toward a receiving vehicle;
[0023] FIG. 5B illustrates a view in a horizontal plane as viewed along reference line 5B-5B in FIG. 5A;
[0024] FIG. 5C illustrates a two-dimensional representation of various possible illustrative distributions of material in the interior of a container (or bin) or storage portion, consistent with a cross-sectional view along reference line 4D-4D in FIG. 4B;
[0025] FIG. 5D is a top view of a transferring vehicle and a receiving vehicle, where the transferring vehicle is aligned within a matrix of possible offset positions;
[0026] FIG. 5E illustrates a block diagram of a container identification process using rectified images; [0027] FIG. 5F illustrates a block diagram of a container identification process capable of using rectified images and disparity images;
[0028] FIG. 6A is a block diagram of a spout localizing process using rectified images and spout position data;
[0029] FIG. 6B is a block diagram of a spout localizing process using rectified images, disparity images, and spout position data; and
[0030] FIG. 7 is a flow chart of a method for operating a machine vision-augmented guidance system for facilitating the unloading of agricultural material from a transferring vehicle.
DESCRIPTION OF THE PREFERRED EMBODIMENT
[0031] One embodiment in accordance with the present invention requires a primary or first imaging device on the receiving vehicle and a secondary or second imaging device on the transferring vehicle, as shown in FIG. 5A. FIGS. 1 and 2 show machine vision augmented guidance systems 1 1 , 1 1 1 for a transferring vehicle 91 for managing the unloading of agricultural material (e.g., grain) from the transferring vehicle 91 (Fig. 1- combine; Fig. 2 - self-propelled forge harvester) to a receiving vehicle 79. FIG. 3 shows a similar machine vision augmented guidance system 31 1 for a receiving vehicle 79 for managing the unloading of agricultural material (e.g., grain) from the transferring vehicle 91 to a receiving vehicle 79.
[0032] FIG. 5A illustrates a top view of a transferring vehicle 91 and a receiving vehicle 79. As illustrated in FIG. 5A for explanatory purposes, the transferring vehicle 91 is shown as a combine with a harvesting head 185, whereas the receiving vehicle 79 is shown as a tractor and a grain cart. The transferring vehicle 91 may comprise other vehicles such as a harvester or other heavy equipment that collects or harvests material for transfer to the receiving vehicle. The receiving vehicle 79 can comprise the combination of a propulsion unit 75 and a storage unit 93 (e.g., a towed storage unit). The spout 89, or the spout end 87, is generally aligned over a central zone 83, central region or target area with the grid pattern (not shown) of the storage container 85 of the receiving vehicle 79 for unloading material from the transferring vehicle 91 to the receiving vehicle 79. The spout 89 may also be referred to as an unloading auger. The spout end 87 may be referred to as a boot. Similarly, the transferring vehicle 91 and the receiving vehicle 79 are aligned in position as shown, regardless of whether the vehicles move together in a forward motion (e.g., with coordinated or tracked vehicle headings) during harvesting, as is typical, or are stationary.
[0033] As mentioned above, the receiving vehicle 79 includes system 31 1 that can comprise a first imaging device 10 coupled to an image processing module 18 (Fig. 3). The transferring vehicle 91 includes systems 1 1 , 1 1 1 that can comprise a second imaging device 12 coupled to an image processing module 18 (Figs. 1 and 2). Each imaging device 10, 12 includes an image rectifier 101 to transform the raw image into a rectified image. Though the example of transferred material disclosed herein is agricultural material, the invention is not to be limited to agricultural material and is applicable to other materials such as coal and other minerals.
[0034] Embodiments of the first imaging device 10 may comprise a primary stereo camera or a monocular camera, while the second imaging device 12 may comprise a secondary stereo camera or a monocular camera. In one configuration, the second imaging device 12 is a stereo camera and can be optional and provides redundancy to the first imaging device 10 in case of failure, malfunction or unavailability of image data from the first imaging device 10 when the first field of view 277 of the first imaging device 10 is sufficient to view within container 85. In one configuration, the second imaging device with a second field of view of 477 is monocular and is required for a stereo image of the container or bin 85 when used in conjunction with an image from a monocular first imaging device 10 with the first field of view 277 sufficient to view within container 85. The boundaries of the fields of view 277, 477 are merely shown for illustrative purposes and will vary in actual practice. [0035] Like reference numbers in the figures indicate like elements, and the first description of the element is a sufficient disclosure to apply to all subsequent recitals of the element. For example, imaging processing module or smart unloading controller 18 can be located in either the system architecture of the transferring vehicle 91 or the receiving vehicle 79 or both. Whether data is processed by imaging processing module or smart unloading controller 18 located on the system of transferring vehicle 91 or the system of receiving vehicle 79 or by both will depend on the end-user's specification. A wirelessly link can be established between imaging device 10 of the receiving vehicle 79 and image processing module 18 of the transferring vehicle 91 to the provide the image data back to processing on the transferring vehicle 91. Here, the receiving vehicle 79 would just have the imaging device, some buffer memory, and a wireless transceiver of one side of the wireless link as shown in FIG. 3. Therefore, all of the processing can be performed on the transferring vehicle 91 and eliminate the image processing module 18 on the receiving vehicle. The wireless protocol can be some variant of an IEEE 802.1 1 standard (e.g., 802. l lg or n) or an spread spectrum modulation (e.g., code division multiple access) to reduce interference, for example. Therefore, it is possible that the imaging processing module or smart unloading controller 18 is located on both vehicles and only one imaging processing module or smart unloading controller 18 is used for processing data collected from imaging devices and the other imaging processing module or smart unloading controller 18 can be used as a backup or on an as-required basis.
[0036] Now turning to FIG. 4 that illustrates the data flow and processing by the image processing module 18 from the raw images to the transferring vehicle commands. The dashed lines represent optional steps and/or modules. Modules are discussed in detail below. Raw images can be collected by the imaging device 10, 12 (e.g. camera being either stereo or monocular). Some embodiments of the present invention only require one imaging device. Raw images are processed through the image rectifier 101 to create rectified images. Rectified images are processed by the image data evaluator 25 to provide an image quality score for the rectified image to determine if the image should be used in further processing by the alignment module 24. Rectified images are also processed by the container identification module 20 and material profile module 27. Rectified images can also be processed in conjunction with disparity images by the spout localizer 22 when a disparity image generator 103 is present. Otherwise, spout localizer 22 will only use the data stored in vehicle model 1000, which includes, but not limited to, data on the transferring vehicle 91 , dimensions of spout 89, and spout kinematic model. Spout localizer 22 also requires data about the vehicle state information, which includes, but not limited to, transferring vehicle speed, spout angle(s), auger drive on/ off status, and relative Global Positioning Satellite position of receiving vehicle 79 if machine synchronization is present. Spout localizer 22 output is input into container identification module 20 and processed in conjunction with rectified images and disparity images (if provided) by container identification module 20 to determine container location and dimensions. Rectified images and disparity images (if provided) are processed in conjunction with container location and dimensions data from container identification module 20 by material profile module 27 to generate a fill profile of the container 85. Alignment module 24 processes data generated by the container identification module 20, material profile module 27 in conjunction with the vehicle state information to generate vehicle commands such as transferring vehicle 91 speed/ steering, spout position, auger drive on/off status, and speed/ steering of the receiving vehicle 79 if machine synchronization is present to reposition the spout end 87 over the appropriate open area of the container 85 for even, uniform distribution of the agricultural material in container 85.
[0037] In the embodiment where the receiving vehicle 79 and transferring vehicle 91 both have image processing modules 18, they could be in a master-slave configuration (e.g., with transferring vehicle with the master image processing module 18 that assigns tasks to the receiving vehicle slave image processing module 18 or a parallel processing configuration, which may require the devices to share common electronic memory on one vehicle via wireless link and which is quite complex. With the large amount of vision data to process, there is an advantage to dual vision processing systems.
[0038] One embodiment of the present invention requires the first imaging device 10 for a receiving vehicle 79 comprises a monocular imaging device (e.g., digital camera) and the second imaging device 12 for a transferring vehicle 91 , such as a combine, comprises a monocular imaging device (e.g., digital camera) that provides first monocular image data and second monocular image data, respectively. If first imaging device 10 is a stereo camera, then second imaging device 12 can be optional or redundant in case first imaging device 10 malfunctions or its image is poor. The image processing module 18 of systems 1 1 , 1 1 1 , 31 1 can create a stereo image from the first monocular image data (e.g., right image data) and the second monocular image data (e.g., left image data) with reference to the relative position and orientation of the first imaging device 10 and the second imaging device 12. The image processing module 18 determines: (1) at least two points on a common visual axis 479 (FIG. 5A) that bisects the lenses of both the first imaging device 10 and the second imaging device 12, and (2) a linear spatial separation 481 (FIG. 5A) between the first imaging device 10 and the second imaging device 12, where the first field of view 277 of the first imaging device 10 and the second field of view 477 of the second imaging device 12 overlap, at least partially, to capture the spout 89, the spout end 87, the bin perimeter 81 , the level (e.g., height z or average height z) or profile of agricultural material in the container or bin 85 (e.g., at some x, y coordinates or positions in the bin 85) in the collected image data. The other components have like reference numbers that have been discussed above.
[0039] Where the fields of view 277, 477 overlap, data fusion of image data from a first imaging device 10 and a second imaging device 12 enables the image processing module 18 to create a virtual profile of the material distribution level (Fig. 5C) inside the storage portion 85, even when the entire surface of the agricultural material is not visible to one of the two imaging devices 10, 12. The spout rotation sensor 1 16 (FIGS. 1 and 2) may facilitate using the spout end 87 as a reference point in any collected image data (e.g., for fusion, virtual stitching or alignment of image data from different imaging devices.) The virtual profile of the entire surface of the agricultural material in the storage portion 93 enables the systems 1 1 , 1 1 1 , 31 1 or imaging module 18 to intelligently execute a fill strategy for the storage portion 93 of the receiving vehicle 79.
[0040] The first imaging device 10 and the second imaging device 12 may provide digital data format output as stereo video image data or a series of stereo still frame images at regular or periodic intervals, or at other sampling intervals. Each stereo image (e.g., the first image data or the second image data) has two component images of the same scene or a portion of the same scene. For example, the first imaging device 10 has a first field of view 277 of the storage portion 93 of the receiving vehicle 79, where the first field of view 277 overlaps at least partially with a second field of view 477 of the second imaging device 12 (if present). In one embodiment, the first imaging device 10, the second imaging device 12, or both may comprise a charge-coupled device (CCD), a complementary metal-oxide semiconductor (CMOS) array, or another suitable device for detection or collection of image data.
[0041] In one configuration, an optical sensor 1 10, 1 12 (FIGS. 1-3) comprises a light meter, a photo-sensor, photo-resistor, photo-sensitive device, or a cadmium- sulfide cell. A first optical sensor 1 10 may be associated with the first imaging device 10; a second optical sensor 1 12 may be associated with the second imaging device 12. The first optical sensor 1 10 and the second optical sensor 1 12 each may be coupled to the image processing module 18. The optical sensor 1 10, 1 12 provides a reading or level indicative of the ambient light in the field of view of its respective imaging device 10, 12. [0042] The image processing module 18 may be coupled, directly or indirectly, to lights 14 (Fig. 1) on a transferring vehicle 91 for illumination of a storage container 85 and/or spout 89. For example, the image processing module 18 may include a light controller 50 (Fig. 2) that comprises control drivers, relays or switches, which in turn control the activation or deactivation of lights 14 on the transferring vehicle 91. The image processing module 18 may activate the lights 14, 52 on the transferring vehicle for illumination of the storage container 85 (FIG. 5A), spout 89 or both if an optical sensor 1 10, 1 12 or light meter indicates that an ambient light level is below a certain minimum threshold. In one configuration the optical sensor 1 10, 1 12 face toward the same direction as the lens or aperture of the imaging devices 10, 12.
[0043] In the combine embodiment (Fig. 1), vehicle controller 46 controls spout 89 that includes a rotation sensor 1 16 for sensing a spout rotation angle (β) in FIG. 5B of the spout 89 with respect to one or more axes of rotation, and a rotation actuator 122 for moving the spout 89 to change the spout rotation angle; hence, the spout 89 position with respect to the receiving vehicle 79 or its storage container 85. The rotation actuator 122 may comprise a motor, a linear motor, an electro-hydraulic device, a ratcheting or cable-actuated mechanical device, or another device for moving the spout 89, or the spout end 87. The spout rotation angle may comprise a simple angle, a compound angle or multi-dimensional angles that is measured with reference to a reference axis parallel to the direction of travel of the transferring vehicle.
[0044] If the rotation actuator 122 comprises an electro-hydraulic device, the use of proportional control valves in the hydraulic cylinder of the electro-hydraulic device that rotates the spout (or changes the spout rotation angle) facilitates finer adjustments to the spout angle (e.g., a) than otherwise possible. Accordingly, proportional control valves of the electro- hydraulic device support rotation actuator 122 for an even profile or distribution of unloaded agricultural material within the storage portion 93 or container or bin 85. Many commercially available combines are typically equipped with non-proportional control valves for controlling spout angle or movement of the spout 89; electro-hydraulic devices with non-proportional control valves can fill the storage container with an inefficient multi-modal or humped distribution (e.g., 508) of agricultural material with local high areas and local low areas, as depicted in FIG. 5C, for example.
[0045] A vehicle controller 46 may be coupled to the vehicle data bus 60 to provide a data message that indicates when the auger drive 47 for unloading agricultural material from the transferring vehicle is activated and inactive. The auger drive 47 may comprise an auger, an electric motor for driving the auger, and a rotation sensor for sensing rotation or rotation rate of the auger or its associated shaft. In one embodiment, the auger (not shown) is associated with a container for storing agricultural material (e.g., a grain tank) of a transferring vehicle 91. If the vehicle controller 46 (e.g., auger controller) indicates that the auger of the transferring vehicle 91 is rotating or active, the imaging processing module 18 activates the spout localizer 22 and container or bin identification module 20. Thus, vehicle controller 46 may conserve data processing resources or energy consumption by placing the container identification module 20 and the spout identification module 22 in an inactive state (or standby mode) while the transferring vehicle 91 is harvesting, but not unloading, the agricultural material to the receiving vehicle 79.
[0046] The imaging processing module 18 or any other controller may comprise a controller, a microcomputer, a microprocessor, a microcontroller, an application specific integrated circuit, a programmable logic array, a logic device, an arithmetic logic unit, a digital signal processor, or another data processor and supporting electronic hardware and software. In one embodiment, the image processing module 18 comprises a disparity generator 103, a container identification module 20, a spout localizer 22, an alignment module 24, a material profile module 27, and a vehicle model 1000. [0047] The image processing module 18 may be associated with a data storage device may comprise electronic memory, non-volatile random access memory, a magnetic disc drive, an optical disc drive, a magnetic storage device or an optical storage device, for example. If the container identification module 20, the spout localizer 22, the alignment module 24, material profile module 27, and vehicle model 1000, are software modules they are stored within the data storage device.
[0048] The container identification module 20 identifies a set of two- dimensional or three dimensional points (e.g., in Cartesian coordinates or Polar coordinates) in the collected image data or in the real world that define at least a portion of the container perimeter 81 of the storage portion 85 (FIG. 5A). The set of two-dimensional or three dimensional points correspond to pixel positions in images collected by the first imaging device 10, the second imaging device 12, or both. The container identification module 20 may use or retrieve container reference data.
[0049] Vehicle Module 100 can include container reference data comprising one or more of the following: reference dimensions (e.g., length, width, height), volume, reference shape, drawings, models, layout, and configuration of the container 85, the container perimeter 81 , the container edges 181 ; reference dimensions, reference shape, drawings, models, layout, and configuration of the entire storage portion 93 of receiving vehicle; storage portion wheelbase, storage portion turning radius, storage portion hitch configuration of the storage portion 93 of the receiving vehicle; and distance between hitch pivot point and storage portion wheelbase. The container reference data may be stored and retrieved from the data storage device (e.g., non-volatile electronic memory). For example, the container reference data may be stored by, retrievable by, or indexed by a corresponding receiving vehicle identifier in the data storage device of the transferring vehicle systems 1 1 , 1 1 1. For each receiving vehicle identifier, there can be a corresponding unique container reference data stored therewith in the data storage device. [0050] In one configuration, the container identification module 18 identifies the position of the container or bin 85 as follows. If the linear orientation of a set of pixels in the collected image data conforms to one or more edges 181 of the perimeter 81 of the container 85 as prescribed by the container reference data, the position of the container 85 has been identified. A target zone, central region or central zone of the container opening 83 of the container 85 can be identified by dividing (by two) the distance (e.g., shortest distance or surface normal distance) between opposite sides of the container, or by identifying corners of the container and where diagonal lines that intercept the corners intersect, among other possibilities. In one configuration, the central zone may be defined as an opening (e.g., circular, elliptical or rectangular) in the container with an opening surface area that is greater than or equal to the cross-sectional surface area of the spout end by a factor of at least two, although other surface areas fall within the scope of the claims.
[0051] The spout localizer 22 identifies one or more of the following: (1) the spout pixels on at least a portion of the spout 89, or (2) spout end pixels that are associated with the spout end 87 of the spout 89. The spout identification module 22 may use color discrimination, intensity discrimination, or texture discrimination to identify background pixels from one or more selected spout pixels with associated spout pixel patterns or attributes (e.g., color or color patterns (e.g., Red Green Blue (RGB) pixel values), pixel intensity patterns, texture patterns, luminosity, brightness, hue, or reflectivity) used on the spout 89 or on the spout end 87 of the spout 89 for identification purposes.
[0052] The alignment module 24, the master controller 59, or both estimate or determine motion commands at regular intervals to maintain alignment of the spout 56 over the central zone, central region or target of the container 85 for unloading agricultural material. The alignment module 24, the master controller 59, or both, may send commands or requests to the transferring vehicle 91 with respect to its speed, velocity or heading to maintain alignment of the position of the transferring vehicle 91 with respect to the receiving vehicle 79. For example, the alignment module 24 may transmit a request for a change in a spatial offset between the vehicles 79, 91 to the master controller 59. In response, the master controller 59 or the coordination module 57 transmits a steering command or heading command to the steering controller 32, a braking or deceleration command to a braking system 34, and a propulsion, acceleration or torque command to a propulsion controller 40 to achieve the target spatial offset or change in spatial offset.
[0053] In another configuration, the alignment module 24 may regularly or periodically move, adjust or rotate the target zone or central zone during loading of the container 85 of the receiving vehicle to promote even filling, a uniform height, or uniform distribution of the agricultural material in the entire container 85, where the image processing module 18 identifies the fill state of the agricultural material in the image data from the material profile module 27.
[0054] The imaging module 18 may comprise material profile module 27 or a fill level sensor for detecting a one-dimensional, two-dimensional or three-dimensional representation of the fill level or volumetric distribution of the agricultural material in the container 85 or storage portion 93. For example, FIG. 5C shows various illustrative two-dimensional representations of the fill state of the container 85, or the distribution of agricultural material in the container 85, discussed in detail below.
[0055] In one configuration, the coordination module 57 or the steering controller 32 adjusts the relative position (of offset) of the transferring vehicle 91 to the receiving vehicle 79. The alignment module 24, the coordination module 57 and the auger rotation system 1 16 may control the relative position of the spout 89 or the spout end 87 to the container perimeter 81 to achieve an even fill to the desired fill level. For example, rotator actuator 122 of the combine may adjust the spout angle (e.g., a first spout angle (a), a second spout angle (β), or a compound angle (a and β)) that the spout 89 makes with respect to a reference axis or reference coordinate system associated with the transferring vehicle 91 or a generally vertical plane associated with the direction of travel of the transferring vehicle 91 , where the spout 89 meets and rotates with respect to the vehicle. With regards to the self-propelled forge harvester, the spout angle is controlled by spout controller 54 in communication with rotation sensor 1 16, tilt sensor 1 18, deflector sensor 120, rotation actuator 122, tilt actuator 124, and deflector actuator 126.
[0056] The spout end 87 may be adjusted for unloading agricultural material by shifting its spout angle or spout position, within the container perimeter 81 and a tolerance clearance from the container perimeter 81 within the container 85. The spout end 87 may be adjusted by various techniques that may be applied alternately, or cumulatively. Under one technique, the alignment module 24 adjusts the spout end 87 for unloading agricultural material by shifting its spout angle (e.g., a first spout angle (a), a second spout angle (β), or both (a and β). Accordingly, the spout end 87 may be adjusted regularly (e.g., in a matrix of one or more rows or columns of preset offset positions) for unloading agricultural material by shifting the spatial relationship between the transferring vehicle and the receiving vehicle by a fore and aft offset or a lateral offset to achieve a target alignment or desired even distribution of filling the container 85 or storage portion 93 with agricultural material (Fig. 5D), while using the spout angle adjustment for fine tuning of the distribution of the agricultural material within the container (e.g., from each position within the matrix).
[0057] In the image processing module 18, the image data evaluator 25 comprise an evaluator, a judging module, Boolean logic circuitry, an electronic module, a software module, or software instructions for determining whether to use the first image data, the second image data, or both for alignment of a relative position of the spout and the container perimeter (or alignment of the spatial offset between the vehicles) based on evaluation of material variation of intensity of pixel data or material variation in ambient light conditions during a sampling time interval. [0058] In the combine, master controller 59 is coupled to the vehicle data bus (e.g., 60). Whereas in the self-propelled forge harvester, master controller 59 is coupled to the implement data base 58 that is connected to vehicle data bus 60 via gateway 29. In one embodiment, the master controller 59 comprises an auto-guidance module 55 and coordination module 57. The auto-guidance module 55 or master controller 59 can control the transferring vehicle 91 in accordance with location data from the first location determining receiver 42 and a path plan or desired vehicle path (e.g., stored in data storage). The auto-guidance module 55 or master controller 59 sends command data to the steering controller 32, the braking controller 36 and the propulsion controller 40 to control the path of the transferring vehicle 91 to track automatically a path plan or to track manually steered course of an operator via the user interface 44 or steering system 30.
[0059] In one embodiment in a leader mode, the transferring vehicle 91 is steered by the auto-guidance module 55 or the steering controller 32 in accordance with path plan, or by a human operator. If the transferring vehicle 91 operates in an automated mode or auto-steering mode, the master controller 59 provides command data locally to the steering controller 32, braking controller 36, and propulsion engine controller 40 of the transferring vehicle 91. In an automated mode and in a leader-follower mode, the transferring vehicle 91 is steered and aligned automatically during transfer of agricultural material from the transferring vehicle 91 to the receiving vehicle 79.
[0060] The image processing module 18 provides image data (rectified, disparity, or both) to a user interface processing module 26 that provides, directly or indirectly, status message data and performance message data to a user interface 44.
[0061] In one embodiment, a location determining receiver 42, a first wireless communications device 48, a vehicle controller 46, a steering controller 32, a braking controller 36, and a propulsion controller 40 are capable of communicating over the vehicle data bus 60. In turn, the steering controller 32 is coupled to a steering system 30 of the transferring vehicle 91 ; the braking controller 36 is coupled to the braking system 34 of the transferring vehicle 91 ; and the propulsion controller 40 is coupled to the propulsion system 38 of the transferring vehicle 91.
[0062] The steering system 30 may comprise an electrically-driven steering system, an electro-hydraulic steering system, a gear driven steering system, a rack and pinion gear steering system, or another steering system that changes the heading of the transferring vehicle 91 or one or more wheels of the transferring vehicle 91. The braking system 34 may comprise a regenerative braking system, an electro-hydraulic braking system, a mechanical breaking system, or another braking system capable of stopping the vehicle by hydraulic, mechanical, friction or electrical forces. The propulsion system 38 may comprise one or more of the following: (1) the combination of an electric motor and an electric controller, (2) internal combustion engine that is controlled by an electronic fuel injection system or another fuel metering device that can be controlled by electrical signals, or (3) a hybrid vehicle in which an internal combustion engine drives a electrical generator, which is coupled to one or more electric drive motors.
[0063] In summary, one or more imaging devices 10, 12 are arranged to collect image data. A container identification module 20 identifies a container perimeter 81 of the storage portion 93 in the collected image data. The storage portion 93 has an opening inward from the container perimeter for receipt of the agricultural material. A spout localizer 22 is configured to identify a spout 89 of the transferring vehicle 91 in the collected image data. An alignment module 24 is adapted for determining the relative position of the spout 89 and the container perimeter 81 and for generating command data to the transferring vehicle 91 to steer the transferring vehicle 91 in cooperative alignment with receiving vehicle 79 (or steer the receiving vehicle 79 in cooperative alignment with transferring vehicle 91) such that the spout 89 is aligned within a central zone 83 or opening of grid pattern 82 of the container perimeter 81. A steering controller 32 is associated with a steering system 30 of the transferring vehicle 91 and receiving vehicle 79 for steering the transferring vehicle 91 and/ or receiving vehicle in accordance with the cooperative alignment.
[0064] In one embodiment, an optional mast controller 674, indicated by dashed lines, is coupled to the vehicle data bus 60 (FIG. 1), or the implement data bus 58 (FIGS. 2 and 3) to control an optional adjustable mast 573 for mounting and adjustably positioning the first imaging device 10, the second imaging device 12, or both. The mast controller 674 is adapted to change the orientation or height above ground of the first imaging device 10, the second imaging device 12 or both, where the orientation may be expressed as any of the following: a tilt angle, a pan angle, a down-tilt angle, a depression angle, or a rotation angle.
[0065] In one illustrative embodiment of a machine-vision guidance system 1 1 , 1 1 1 , 31 1 that has an adjustable mast 573, at least one imaging device 10, 12 faces towards the storage portion 93 of the receiving vehicle 79 and collects image data. For example, via data from the mast controller 674 the adjustable mast 573 is capable of adjusting a height of the imaging device 10, 12 within a height range, adjusting a down-tilt angle of the imaging device 10, 12 within a down-tilt angular range, and a rotational angle or pan angle within a pan angular range. The image processing module 18 is adapted or programmed (e.g., with software instructions or code) to determine whether to adjust the height of the imaging device 10, 12 or whether to decrement or increment the down-tilt angle of the imaging device 10, 12 based on evaluation of material variation of intensity of pixel data or material variation in ambient light conditions (e.g., from the optical sensor 1 10, 1 12) during a sampling time interval. Under certain operating conditions, such as outdoor ambient light conditions, increasing or incrementing the down-tilt angle may increase the quality level of the collected image data or reduce variation in the intensity of the image data to below a threshold variation level. Reduced variation in intensity of the image data or reduced collection of dust or debris on a lens of the imaging device are some advantages that can be realized by increasing or adjusting down-tilt angle of the imaging device 10, 12, for example. As previously noted, a container identification module 20 can identify a container perimeter 81 of the storage portion 93 in the collected image data. Similarly, a spout localizer 22 can identify a spout of the transferring vehicle 91 in the collected image data. An alignment module 24 determines the relative position of the spout 89 and the container perimeter 81 , and generates command data to the steering controller 32 to steer the transferring vehicle 91 in cooperative alignment with the receiving vehicle 79 such that the spout 89, or spout end 87, is aligned within a target zone of the grid pattern (not shown) or central zone 83 of the container perimeter 81.
[0066] In one illustrative embodiment of a machine-vision guidance system with the adjustable mast 573, the image processing module 18 sends a data message to a mast controller 674 (or the adjustable mast 573) to increment or increase the down-tilt angle if the material variation of intensity of pixel data or if the material variation in ambient light conditions exceeds a threshold variation level during a sampling time interval. For example, the image processing module 18 sends a data message to a mast controller 674 to increment or increase the down-tilt angle at discrete levels (e.g., one degree increments or decrements) within an angular range of approximately negative ten degrees to approximately negative twenty-five degrees from a generally horizontal plane.
[0067] If the second imaging device 12 is elevated or mounted on the transferring vehicle 91 sufficiently high with respect to the storage portion 93, the second imaging device 12 will have visibility or second downward field of view 677 into the storage portion 93 or container 85 sufficient to observe and profile the surface (or height (z) versus respective x, y coordinates in the container) of the agricultural material (e.g., grain) as the agricultural material fills the storage portion 85. The second imaging device 12 may be mounted on the roof of the transferring vehicle 91 facing or looking directly away from the side of the transferring vehicle 91 with the spout 89 for unloading agricultural material. [0068] In one illustrative configuration, consistent with the downward field of view 677 the optical axis, perpendicular to respective lens, of the second imaging device 12 is tilted downward from generally horizontal plane at a down-tilted angle (ε) (e.g., approximately 10 to 25 degrees downward). If a field of view or optical axis of the second imaging device 12 is tilted downward from a generally horizontal plane, there are several advantages. First, less of the sky is visible in the field of view of the second imaging device 12 such the collected image data tends to have a more uniform image intensity profile. The tilted configuration of the optical axis or axes (which is perpendicular to the lens of the second imaging device 12) is well suited for mitigating the potential dynamic range issues caused by bright sunlight or intermediate cloud cover, for instance. Second, the bottom part of the storage portion 93 becomes more visible in the image data to enable the recording of the image data related to one or more wheels of the storage portion 93. The wheel is a feature on the storage portion 93 that can be robustly tracked by image processing techniques. Third, tilting the stereo camera down may mitigate the accumulation of dust and other debris on the lens or external window of the imaging device 10, 12.
[0069] FIG. 5C illustrates a two-dimensional representation of various possible illustrative distributions of material in the container 85, consistent with a view along reference line 5B in FIG. 5A. In one configuration, the y axis is coincident with the longitudinal axis or direction of travel of the container, the z axis is coincident with the height of material in the container, and the x axis is perpendicular to the direction of travel of the container, where the x, y and z axes are generally mutually orthogonal to each other.
[0070] In the chart of FIG. 5C, the vertical axis is the mean height (Z) 500 of the material in the container 85, the horizontal axis represents the longitudinal axis (y) 502 of the container 85. The maximum capacity 504 or container capacity is indicated by the dashed line on the vertical axis. The front 512 of the container 85 is located at the origin, whereas the back 514 of the container 85 is located on the vertical axis. [0071] FIG. 5C shows three illustrative distributions of material within the container 85. The first distribution is a bimodal profile 508 in which there are two main peaks in the distribution of material in the container 85. The bimodal profile 508 is shown as a dotted line. The bimodal profile 508 can occur where the spout angle adjustment is governed by an electro- hydraulic system with non-proportional valves.
[0072] The second distribution is the front- skewed modal profile 510 in which there is single peak of material toward the front of the container 85. The front-skewed modal profile 510 is shown as alternating long and short dashes. The second distribution may occur where the volume or length (y) of the container 85 is greater than a minimum threshold and where the relative alignment between the spout end 87 and the container 85 is generally stationary during a substantial portion of unloading of the material.
[0073] The third distribution is the target profile 508 which may be achieved by following a suitable fill strategy as disclosed in this document. For example, during unloading, the spout angle may be adjusted to promote uniform distribution of the agricultural material in the container 85.
[0074] In one configuration, a user interface 44 is arranged for entering container reference data or dimensional parameters related to the receiving vehicle. For example, the container reference data or dimensional parameters comprise a distance between a trailer hitch or pivot point (which interconnects the propulsion unit 75 and the storage portion 93) and front wheel rotational axis of the storage portion 93 of the receiving vehicle 79.
[0075] In an alternate embodiment, FIGS. 1 and 2 further comprises an optional odometer sensor 440, and an optional inertial sensor 442, as illustrated by the dashed lines. The odometer sensor 440 may comprise a magnetic rotation sensor, a gear driven sensor, or a contactless sensor for measuring the rotation of one or more wheels of the transferring vehicle to estimate a distance traveled by the transferring vehicle during a measurement time period, or a ground speed of the transferring vehicle. The odometry sensor 440 may be coupled to the vehicle data bus 60 or an implement data bus 58. The inertial sensor 442 may comprise one or more accelerometers, gyroscopes or other inertial devices coupled to the vehicle data bus 60 or an implement data bus 58. The optional odometry sensor 440 and the optional inertial sensor 442 may augment or supplement position data or motion data provided by the first location determining receiver 42.
[0076] As mentioned above, the vision-augmented guidance system 1 1 1 of FIG. 2 is similar to the system 1 1 of FIG. 1 ; except that the system 1 1 1 of FIG. 2 further comprises an implement data bus 58, a gateway 29, and light controller 50 and spout controller 54 coupled to the vehicle data bus 60 for the lights 14 and spout 89, respectively. The light controller 50 controls the lights 14; the spout controller 54 controls the spout 89 via a servo-motor, electric motor, or an electro-hydraulic mechanism for moving or adjusting the orientation or spout angle of the spout 89, or its spout end 87. In one configuration, the implement data bus 58 may comprise a Controller Area Network (CAN) implement data bus. Similarly, the vehicle data bus 60 may comprise a controller area network (CAN) data bus. In an alternate embodiment, the implement data bus 58, the vehicle data bus 60, or both may comprise an ISO (International Organization for Standardization) data bus or ISOBUS, Ethernet or another data protocol or communications standard.
[0077] The self-propelled forge harvester includes gateway 29 to support secure or controlled communications between the implement data bus 58 and the vehicle data bus 60. The gateway 29 comprises a firewall (e.g., hardware or software), a communications router, or another security device that may restrict or prevent a network element or device on the implement data bus 58 from communicating (e.g., unauthorized communication) with the vehicle data bus 60 or a network element or device on the vehicle data bus 31 , unless the network element or device on the implement data bus 58 follows a certain security protocol, handshake, password and key, or another security measure. Further, in one embodiment, the gateway 29 may encrypt communications to the vehicle data bus 60 and decrypt communications from the vehicle data bus 60 if a proper encryption key is entered, or if other security measures are satisfied. The gateway 29 may allow network devices on the implement data bus 58 that communicate via an open standard or third party hardware and software suppliers, whereas the network devices on the vehicle data bus 60 are solely provided by the manufacturer of the transferring vehicle (e.g., self- propelled forage harvester) or those authorized by the manufacturer.
[0078] In FIG. 2, a first location determining receiver 42, a user interface 44, a user interface processing module 26, and the gateway 29 are coupled to the implement data bus 58, although in other embodiments such elements or network devices may be connected to the vehicle data bus 60. Light controller 50 and spout controller 54 are coupled to the vehicle data bus 60. In turn, the light controller 50 and spout controller 54 are coupled, directly or indirectly, to lights 14 on the transferring vehicle 91 and the spout 89 of the transferring vehicle 91 (e.g., self-propelled forage harvester), respectively. Although the system of FIG. 2 is well suited for use or installation on a self-propelled forage harvester (SPFH), the system of FIG. 2 may also be applied to harvesters or other heavy equipment.
[0079] FIG. 5D is a top view of a transferring vehicle 91 and a receiving vehicle 79, where the transferring vehicle 91 is aligned within a matrix 500 of possible offset positions 502, 504 between the transferring vehicle 91 and receiving vehicle 79. As shown, the matrix 500 is a two-dimensional, 2 x 3 (2 columns by 3 rows) matrix of possible offset positions 502, 504. Although six possible matrix positions 502, 504 are shown, in alternate embodiments the matrix 500 may consistent of any number of possible offset positions greater than or equal to two. Here, the transferring vehicle 91 occupies a current offset position 504 in the first column at the second row of the matrix 500, whereas the other possible offset positions 502 are not occupied by the transferring vehicle 91. As directed by any of the systems 1 1 , 1 1 1 , 31 1 , the imaging processing module 18, or the master controller 59 of the transferring vehicle 91 can shift to any unoccupied or other possible offset positions 502 within the matrix 500 to promote or facilitate an even distribution of agricultural material within the container 85 or storage portion of the receiving vehicle 79. The spatial separation 481 between the transferring vehicle 91 and the receiving vehicle 79 may be adjusted in accordance with the matrix 500 or another matrix of preset positions of spatial offset to promote even distribution of agricultural material in the storage portion of the receiving vehicle 79, where any matrix is associated with a unique, relative spatial separation 481 between the vehicles 79,91.
[0080] In one embodiment of FIG. 5D, both the transferring vehicle 91 and the receiving vehicle 79 may be moving forward at approximately the same velocity and heading (e.g., within a tolerance or error of the control systems during harvesting), where the relative position of the receiving vehicle 79 is generally fixed or constant with respect to each position 502, 504 in the matrix 500 that the transferring vehicle 91 can occupy.
[0081] In an alternate embodiment, the receiving vehicle 79 may be shown as occupying a two dimensional matrix (e.g., 3 X 3 matrix, with three columns and three rows) of possible offset positions, while the position of the transferring vehicle 91 is generally fixed or constant with respect to each position of matrix that the receiving vehicle 79 could occupy. As directed by any of the systems 1 1 , 1 1 1 , 31 1 in the alternate embodiment, the imaging processing module 18 can shift to any unoccupied or other possible offset positions within the matrix to promote or facilitate an even distribution of agricultural material within the container 85 or storage portion 93 of the receiving vehicle 79.
[0082] In FIGS. 1-3, each of the blocks or modules may represent software modules, electronic modules, or both. Software modules may contain software instructions, subroutines, object-oriented code, or other software content. The arrows that interconnect the blocks or modules of FIG. 4 show the flow of data or information between the blocks. The arrows may represent physical communication paths or virtual communication paths, or both. Physical communication paths mean transmission lines or one or more data buses for transmitting, receiving or communicating data. Virtual communication paths mean communication of data, software or data messages between modules.
[0083] As illustrated in FIGS. 1-3, the first imaging device 10, the second imaging device 12, or both, provide input of raw stereo camera images (or raw image data) to the image rectification module 101. FIG. 5E is a block diagram that shows raw camera (monocular or stereo) processed by image rectifier 101 to create rectified images for input into container identification module 20. Optional input into container identification module 20 is spout localizer data 22. FIGS. 5F is a block diagram that shows raw camera images (monocular or stereo) processed by image rectifier 101 to create a rectified image. The rectified image will be processed by the disparity image generator 103 to create ranges in the form of disparity data. Thereafter, rectified images and disparity data are process by the spout localizer 22 with spout position data 1002. Output from spout localizer 22 is input into container identification module 20. In an alternative embodiment, data from spout localizer 22 can be input into container identification module 20 for a refinement in the material distribution in container or bin 85.
[0084] FIG. 6A is a block diagram that shows raw camera images (monocular or stereo) processed by an image rectifier 101 to create rectified images for input into spout localizer 22 for further processing with spout position data 1002 provided by vehicle model 1000. Output data from spout localizer 22 can be input data for container identification module 20.
[0085] FIG. 6B is a block diagram that shows raw camera images (monocular or stereo) processed by an image rectifier 101 to create rectified images. The rectified images will be processed by disparity generator 103 to create ranges in the form of disparity data. Thereafter, rectified images and disparity data are processed by the spout localizer 22 along with spout position data 1002. The output data of spout localizer 22 can be further processed by the container identification module 20. The image rectification module 101 provides image processing to the collected image data or raw stereo images to reduce or remove radial lens distortion and image alignment required for stereo correspondence. The radial lens distortion is associated with the radial lenses of the first imaging device 10, the second imaging device 12, or both. The input of the image rectification module 101 is raw stereo image data, whereas the output of the image rectification module 101 is rectified stereo image data. Like reference numbers in FIGS. 1 , 2, 5A, 5E, 5F, 6A, and 6B indicate like elements.
[0086] In one illustrative embodiment, the image rectifier 101 eliminates or reduces any vertical offset or differential between a pair of stereo images of the same scene of the image data. Further, the image rectification module can align the horizontal component (or horizontal lines of pixels of the stereo images) to be parallel to the scan lines or common reference axis of each imaging device (e.g., left and right imaging device) within the first and second imaging devices 10, 12. For example, the image rectifier 101 can remap pixels from initial coordinates to revised coordinates for the right image, left image or both to achieve registration of the images or rectified right and left images of the stereo image. The rectified image supports efficient processing and ready identification of corresponding pixels or objects within the image in the left image and right image of a common scene for subsequent image processing.
[0087] In one configuration, the disparity image generator 103 applies a stereo matching algorithm or disparity calculator to collected stereo image data, such as the rectified stereo image data outputted by the image rectifier 101. The stereo matching algorithm or disparity calculator may comprise a sum of absolute differences algorithm, a sum of squared differences algorithm, a consensus algorithm, or another algorithm to determine the difference or disparity for each set of corresponding pixels in the right and left image (e.g., along a horizontal axis of the images or parallel thereto).
[0088] In an illustrative sum of the absolute differences procedure, the right and left images (or blocks of image data or rows in image data) can be shifted to align corresponding pixels in the right and left image. The stereo matching algorithm or disparity calculator determines a disparity value between corresponding pixels in the left and right images of the image data. For instance, to estimate the disparity value, each first pixel intensity value of a first subject pixel and a first sum of the first surrounding pixel intensity values (e.g., in a block or matrix of pixels) around the first pixel is compared to each corresponding second pixel intensity value of second subject pixel and a second sum of the second surrounding pixel intensity values (e.g., in a block or matrix of pixels) around the second pixel. The disparity values can be used to form a disparity map or image for the corresponding right and left image data.
[0089] A container localizer estimates a distance or range from the first imaging device 10, the second imaging device 12, or both to the pixels or points lying on the container perimeter 81 , on the container edge 181 , on the spout 89, on the spout end 87, or on any other linear edge, curve, ellipse, circle or object identified by the edge detector, the linear Hough transformer, or both. For example, the image processing module 18 may use the disparity map or image to estimate a distance or range from the first imaging device 10, the second imaging device 12, or both to the pixels or points lying on the container perimeter 81 , the container edges 181 , the container opening 83, in the vicinity of any of the foregoing items, or elsewhere.
[0090] In one embodiment, the container identification module 20 comprises: (1) an edge detector for measuring the strength or reliability of one or more edges 181 , or points on the container perimeter 81 in the image data; (2) a linear Hough transformer for identifying an angle and offset of candidate linear segments in the image data with respect to a reference point on an optical axis, reference axis of the one or more imaging devices 10, 12; (3) a container localizer adapted to use spatial and angular constraints to eliminate candidate linear segments that cannot logically or possibly form part of the identified linear segments of the container perimeter 81 , or points on the container perimeter 81 ; and (4) the container localizer transforms the non-eliminated, identified linear segments, or identified points, into two or three dimensional coordinates relative to a reference point or reference frame of the receiving vehicle and harvesting vehicle.
[0091] The edge detector may apply an edge detection algorithm to rectified image data from the image rectifier 101. Any number of suitable edge detection algorithms can be used by the edge detector. Edge detection refers to the process of identifying and locating discontinuities between pixels in an image or collected image data. For example, the discontinuities may represent material changes in pixel intensity or pixel color which defines boundaries of objects in an image. A gradient technique of edge detection may be implemented by filtering image data to return different pixel values in first regions of greater discontinuities or gradients than in second regions with lesser discontinuities or gradients. For example, the gradient technique detects the edges of an object by estimating the maximum and minimum of the first derivative of the pixel intensity of the image data. The Laplacian technique detects the edges of an object in an image by searching for zero crossings in the second derivative of the pixel intensity image. Further examples of suitable edge detection algorithms include, but are not limited to, Roberts, Sobel, and Canny, as are known to those of ordinary skill in the art. The edge detector may provide a numerical output, signal output, or symbol, indicative of the strength or reliability of the edges 181 in field. For example, the edge detector may provide a numerical value or edge strength indicator within a range or scale or relative strength or reliability to the linear Hough transformer.
[0092] The linear Hough transformer receives edge data (e.g., an edge strength indicator) related to the receiving vehicle and identifies the estimated angle and offset of the strong line segments, curved segments or generally linear edges (e.g., of the container 85, the spout 89, the spout end 87 and opening 83) in the image data. The estimated angle is associated with the angle or compound angle (e.g., multidimensional angle) from a linear axis that intercepts the lenses of the first imaging device 10, the second image device 12, or both. The linear Hough transformer comprises a feature extractor for identifying line segments of objects with certain shapes from the image data. For example, the linear Hough transformer identifies line equation parameters or ellipse equation parameters of objects in the image data from the edge data outputted by the edge detector, or Hough transformer classifies the edge data as a line segment, an ellipse, or a circle. Thus, it is possible to detect containers or spouts with generally linear, rectangular, elliptical or circular features.
[0093] In one embodiment, the data manager supports entry or selection of container reference data by the user interface 44. The data manager supports entry, retrieval, and storage of container reference data, such as measurements of cart dimensions, by the image processing module 18 to give spatial constraints to the container localizer on the line segments or data points that are potential edges 181 of the cart opening 83.
[0094] In one embodiment, the angle estimator may comprise a Kalman filter or an extended Kalman filter. The angle estimator estimates the angle of the storage portion 93 (e.g., cart) of the receiving vehicle 79 to the axis of the direction of travel of the propelled portion 75 (e.g., tractor) of the receiving vehicle 79. The angle estimator (e.g., Kalman filter) provides angular constraints to the container localizer on the lines, or data points, that are potential edges 181 of the container opening 83. In configuration, the angle estimator or Kalman filter is coupled to the container localizer . The angle estimator filter outputs, or is capable of providing, the received estimated angle of the storage portion 93 relative to the axis of the direction of travel of the propelling portion 75 of the vehicle.
[0095] The container localizer is adapted to receive measurements of dimensions of the container perimeter 81 or the storage portion 93 of the vehicle to facilitate identification of candidate linear segments that qualify as identified linear segments of the container perimeter 81. In one embodiment, the container localizer is adapted to receive an estimated angle of the storage portion 93 relative to the propelling portion 75 of the vehicle to facilitate identification of candidate linear segments that qualify as identified linear segments of the container perimeter 81. The container localizer uses spatial and angular constraints to eliminate candidate lines in the image data that cannot be possibly or logically part of the container opening 83 or container edges 181 , then selects preferential lines (or data points on the container edge 81) as the most likely candidates for valid container opening 83 (material therein) or container edges 181. The container localizer characterizes the preferential lines as, or transformed them into, three dimensional coordinates relative to the vehicle or another frame of reference to represent a container perimeter of the container 85.
[0096] In one embodiment, the spout localizer 22 comprises a spout classifier that is configured to identify candidate pixels in the image data based at least one of reflectivity, intensity, color or texture features of the image data (or pixels), of the rectified image data or raw image data, where the candidate pixels represent a portion of the spout 89 or spout end 87. The spout localizer 22 is adapted to estimate a relative position of the spout 89 to the imaging device based on the classified, identified candidate pixels of a portion of the spout 89. The spout localizer 22 receives an estimated combine spout position or spout angle (a) relative to the mounting location of the imaging device, or optical axis, or reference axis of one or more imaging devices, based on previous measurements to provide constraint data on where the spout 89 can be located possibly.
[0097] The spout classifier applies or includes software instructions on an algorithm that identifies candidate pixels that are likely part of the spout 89 or spout end 87 based on expected color and texture features within the processed or raw image data. For example, in one configuration the spout end 87 may be painted, coated, labeled or marked with a coating or pattern of greater optical or infra-red reflectivity, intensity, or luminance than a remaining portion of the spout 89 or the transferring vehicle. The greater luminance, intensity or reflectivity of the spout end 87 (or associated spout pixels of the image data versus background pixels) may be attained by painting or coating the spout end 87 with white, yellow, chrome or a lighter hue or shade with respect to the remainder of the spout 89 or portions of the transferring vehicle within the field of view of the imaging devices 10, 12.
[0098] In one embodiment, the spout position estimator comprises a Kalman filter or an extended Kalman filter that receives input of previous measurements and container reference data and outputs an estimate of the spout position, spout angle, or its associated error. The spout position estimator provides an estimate of the combine spout position, or spout angle, or its error, relative to one or more of the following: (1) the mounting location or pivot point of the spout on the transferring vehicle, or (2) the optical axis or other reference axis or point of the first imaging device 10, the second imaging device 12, or both, or (3) the axis associated with the forward direction of travel or the heading of the transferring vehicle. The Kalman filter outputs constraints on where the spout 89 or spout end 87 can be located, an estimated spout position, or a spout location zone or estimated spout position zone. In one embodiment, the spout position estimator or Kalman filter is coupled to the spout localizer 22.
[0099] The spout localizer 22 takes pixels that are classified as belonging to the combine auger spout 89 and uses a disparity image from disparity image generator 103 to estimate the relative location of the spout to the first imaging device 10, the second imaging device 12, or both, or reference axis or coordinate system associated with the vehicle.
[00100] FIG. 7 is a flow chart of a method for facilitating the unloading of agricultural material from a vehicle or between a transferring vehicle 91 and a receiving vehicle 79. The method of FIG. 7 may use one or more of the following embodiments of the systems 1 1 , 1 1 1 , 31 1 previously disclosed herein.
[00101] In step S902, the first imaging device 10 faces toward the storage portion of the receiving vehicle 79 (e.g., grain cart) and collects first image data (e.g., first stereo image data, first monocular image data, or a right image of a stereo image). For example, the first imaging device 10 may be mounted on the body of transferring vehicle 91 facing the receiving vehicle 79 and facing the container 85. In one embodiment, the first imaging device 10 has first field of view 277 or view 477 of the storage portion of the receiving vehicle 79 (FIGS. 5A and 5B).
[00102] In an alternative embodiment, the first imaging device 10 comprises a monocular imaging device that provides a first image section (e.g., left image) of stereo image data of a scene or an object.
[00103] In step S904, where present, the optional second imaging device 12 faces toward the storage portion 93 of the receiving vehicle 79 (e.g., grain cart) and collects second image data (e.g., second stereo image data, second monocular image data, or a left image of a stereo image). For example, the second imaging device 12 may be mounted on the body of the transferring vehicle 91 facing the receiving vehicle 79 (FIGS. 3 and 4A). In one embodiment, the second imaging device 12 has a second field of view 677 of the storage portion of the receiving vehicle, where the first field of view 277 overlaps at least partially with the second field of view 677, respectively.
[00104] In an alternate embodiment, the second imaging device 12 comprises a monocular imaging device that provides a second image section (e.g., right image) of stereo image data of a scene or an object, where the image processing module 18 supports the creation of a stereo image from a combination of the first image section (of the first monocular imaging device) and the second image section with reference to the relative position and orientation of the first imaging device 10 and the second imaging device 12.
[00105] In step S906, an image processing module 18 or a container identification module 20 identifies a container perimeter 81 of the storage portion 93 in the collected image data (e.g., the first image data, the second image data or both), where the storage portion 93 has an opening 83 inward from the container perimeter 81 for receipt of the agricultural material. Step S906 may be carried out in accordance with various techniques, which may be applied alternately or cumulatively. Under a first technique, the image processing module 18 or container identification module 20 may employ the following processes or sub-steps: (1) measuring a strength of one or more edges 181 in the image data (raw and rectified image data); (2) identifying an angle and offset of candidate linear segments in the image data with respect to an optical axis, reference axis (e.g., direction of travel of the transferring vehicle), or reference point indexed to one or more imaging devices 10, 12; and (3) using spatial and angular constraints to eliminate identified candidate linear segments that cannot logically or possibly form part of the identified linear segments of the container perimeter, where the container identification module 20 transforms the identified linear segments into three dimensional coordinates relative to a reference point or reference frame of the receiving vehicle and/ or the harvesting vehicle.
[00106] Under a second technique, the image processing module 18 or container identification module 20 may receive container reference data, or measurements of dimensions of the container perimeter 81 or the storage portion 93 of the vehicle, to facilitate identification of candidate linear segments, or candidate data points, that qualify as identified linear segments of the container perimeter 81.
[00107] Under the third technique, the image processing module 18 or container identification module 20 may receive an estimated angle of the storage portion 93 relative to the propelling portion 75 of the vehicle to facilitate identification of candidate linear segments that qualify as identified linear segments of the container perimeter 81.
[00108] Under a fourth technique, the image processing module 18 or container identification module 20 provides the received estimated angle of the storage portion 93 relative to the propelling portion 75 of the vehicle.
[00109] In step S908, the image processing module 18 or a spout localizer 22 identifies a spout 89 (or spout end 87) of the transferring vehicle 91 in the collected image data. The image processing module 18 or the spout localizer 22 may use various techniques, which may be applied alternately or cumulatively. Under a first technique, the image processing module 18 or the spout localizer 22 identifies candidate pixels in the image data (e.g., rectified or raw image data) based on expected color and expected texture features of the image data, where the candidate pixels represent a portion of the spout 89 (e.g., combine auger spout) or spout end 87.
[00110] Under a second technique, the image processing module 18 or the spout identification module 22 estimates a relative position, or relative angle, of the spout 89 or the spout end 87, to the imaging device based on the classified, identified candidate pixels of a portion of the spout 89.
[00111] Under a third technique, the image processing module 18 or the spout identification module 22 receives an estimated combine spout position, or spout angle, relative to the mounting location, optical axis, reference axis, or reference point of the imaging device 10, 12 based on previous measurements to provide constraint data on where the spout 89 can be located possibly.
[00112] Under a fourth technique, the image processing module 18 or spout localizer 22 provides the estimated combine spout position, or estimated spout angle, to the container identification module 20.
[00113] In step S910, the image data evaluator 25 or image processing module 18 determines whether to use the first image data, the second image data or both, based on an evaluation of the intensity of pixel data or ambient light conditions. Step S910 may be carried out in accordance with various techniques, which may be applied alternately or cumulatively.
[00114] Under a first technique, where a first optical sensor 1 10 is associated with the respective first imaging device 10; the image data evaluator 25 or image processing module 18 decides to use the first image data if the variation in ambient light over a sampling time interval (e.g., commensurate with a sampling rate of 1 to 120 samples per second) is less than or equal to a maximum ambient light variation, as measured by the first optical sensor 1 10. Here, under the first technique the first image data is collected solely by the first imaging device 10. A background level, mean level, or mode level of variation in the ambient light in the image data, a block of pixels in the first image data, or an object within the image data (e.g., spout, spout end, container perimeter or container) may be gathered or tracked during operation or normal operation of the systems 1 1 , 1 1 1 , 31 1. In one embodiment, the maximum ambient light level is set to be greater than the background level, mean level, or mode level. For example, the maximum ambient light level (e.g., within the visible light spectrum, near- infrared spectrum, or infrared spectrum) is set to be greater by statistical measure (e.g., approximately one to two standard deviations above the background level), mean level or mode level, or a signal level difference between the maximum ambient light level and the mean level of equal to or greater than a threshold level (e.g., within a range of approximately 3 decibels to 6 decibels).
[00115] Under a second technique, where a second optical sensor 1 12 is associated with the second imaging device 12; the image data evaluator 25 or image processing module 18 decides to use the second image data if the variation in ambient light over a sampling time interval (e.g., commensurate with a sampling rate of 1 to 120 samples per second) is less than or equal to a maximum ambient light variation, as measured by the second optical sensor 1 12. Here under the second technique, the second image data is collected solely by the second imaging device 12. A background level, mean level, or mode level of variation in the ambient light in the second image data, a block of pixels in the image data, or an object within the image data (e.g., spout, spout end, container perimeter or container) may be gathered or tracked during operation or normal operation of the systems 1 1 , 1 1 1 , 31 1. In one embodiment, the maximum ambient light level is set to be greater than the background level, mean level, or mode level. For example, the maximum ambient light level (e.g., within the visible light spectrum, near- infrared spectrum, or infrared spectrum) is set to be greater by statistical measure (e.g., approximately one to two standard deviations above the background level), mean level or mode level, or a signal level difference between the maximum ambient light level and the mean level of equal to or greater than a threshold level (e.g., within a range of approximately 3 decibels to 6 decibels). [00116] Under a third technique, the image processing module 18, or the image data evaluator 25 decides to use the first image data of the first imaging device 10 if the variation in pixel intensity of a spout, a spout end, or a container in the first image over a sampling time interval is less than or equal to a maximum pixel intensity variation, as detected by the image processing module 18.
[00117] Under a fourth technique, the image processing module 18, or the image data evaluator 25 decides to use the second image data of the second imaging device 12 if the variation in pixel intensity of a spout or spout end in the second image over a sampling time interval is less than or equal to a maximum pixel intensity variation, as detected by the image processing module 18.
[00118] Under a fifth technique, the image processing module 18, the image data evaluator 25 is adapted for determining whether to use the first image data, the second image data or both, for the identification of the container perimeter and the identifying of the spout 89 (or spout end 87), based on pixel intensity in rejected image data being outside of a desired range or variation in pixel intensity during the sampling time interval, where the image processing module 18, the image data evaluator 25 or image processing module 18 is configured to disable selectively the processing or use of the rejected image data that comprises a portion of the collected first image data or the second image data that would otherwise be corrupted by one or more of the following conditions: (1) excessive transient sunlight during sunrise, sunset, or excessive light radiation from other sources (e.g., headlights from other vehicles), (2) transitory sunlight or cloud cover, (3) fog, precipitation or moisture, (4) shading (e.g., from vegetation, trees, buildings or plant canopies), (5) airborne dust or debris, (6) reflections of light (e.g., from polished, glossy or reflective surfaces of other machines or vehicles) or other lighting conditions that can temporarily disrupt or interfere with proper operation of the imaging devices 10, 12. [00119] In step S912, the image processing module 18 or the alignment module 24 determines the relative position of the spout 89, or the spout end 87, and the container perimeter 81 and for generating command data to modulate the ground speed of the transferring vehicle 91 or reposition the spout 89 or both in cooperative alignment such that the spout 89 (or spout end 87) is aligned with a central zone 83 of the container perimeter 81. The image processing module 18 may use, retrieve or access previously stored data, such as dimensional parameters related to the receiving vehicle, the dimensional parameters comprising a distance between a trailer hitch and front wheel rotational axis of the storage portion 93. Such dimensional parameters may be entered via a user interface 44 coupled to the vehicle data bus 60 or the image processing module 18, for example.
[00120] To execute step S912, the imaging processing module 18 may use first location data of a first location determining receiver 42 on the transferring vehicle 91 to determine relative position between the spout and the container perimeter, and generate command data to modulate the ground speed of the transferring vehicle 91 or reposition the spout 89 or both in cooperative alignment such that the spout 89 is aligned within a central zone of the container perimeter 181 or a section of grid pattern 82.
[00121] In step S914, in a first configuration, the controller 59 or the propulsion controller 40 modulates the ground speed of the transferring vehicle 91. In a second configuration, the vehicle controller 46 or the spout controller 54 repositions the spout 89. The rotation actuator 122 (e.g., a servo-motor, electric motor, linear motor and linear-to-rotational gear assembly, or electro-hydraulic device) controls the spout angle of the spout 89, or the spout end 87, with respect to the direct of travel or another reference axis of the transferring vehicle in response to alignment module 24 or the image processing module 18 (e.g., smart unloading controller). In a third configuration, both the speed of the transferring vehicle and the spout 89 is repositioned. [00122] While the disclosure has been described in detail and with reference to specific embodiments thereof, it will be apparent to one skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the embodiments. Thus, it is intended that the present disclosure cover the modifications and variations of this disclosure provided they come within the scope of the appended claims and their equivalents.

Claims

1. A system for facilitating the transfer of material from a transferring vehicle to a receiving vehicle, the system comprising: a receiving vehicle comprising a propelled portion for propelling the receiving vehicle and a storage portion for storing material; a first imaging device facing towards the storage portion of the receiving vehicle, the first imaging device collecting first image data; a bin identification module for identifying a bin perimeter of the storage portion in the collected image data; a spout identification module for identifying a spout of the transferring vehicle in the collected image data; an image data evaluator for determining whether to use the first image data, the second image data or both for alignment of a relative position of the spout and the bin perimeter based on evaluation of material variation of intensity of pixel data or material variation in ambient light conditions during a sampling time interval; an alignment module for determining the relative position of the spout and the bin perimeter and for generating command data to the propelled portion to steer the storage portion in cooperative alignment such that the spout is aligned within a zone of the bin perimeter; and a steering controller associated with a steering system of the propelled portion for steering the receiving vehicle in accordance with the cooperative alignment.
2. The system according to claim 1 , wherein the first imaging device is mounted on the receiving vehicle.
3. The system according to claim 2, further comprises a second imaging device mounted on the transferring vehicle or movably attached to the transferring vehicle.
4. The system according to claim 3, wherein the first imaging device has a first field of view of the storage portion and the second imaging device has a second field of view of the storage portion, the first field of view overlapping at least partially with the second field of view.
5. The system according to claim 3, wherein the first imaging device and the second imaging device each comprise a stereo vision camera.
6. The system according to claim 3, wherein the first imaging device comprises a monocular imaging device, the second imaging device comprises a monocular imaging device and together a stereo image is created from the first collected image data and the second collected image data with reference to the relative position and orientation of the first imaging device and the second imaging device.
7. The system according to claim 1 , wherein an imaging processing module uses first location data of a first location determining receiver on the transferring vehicle and second location data of a second location determining receiver to determine a relative position of the first imaging device and the second imaging device and to determine a relative alignment between the spout and the bin perimeter.
8. The system according to claim 1 , further comprising a first optical sensor associated with the first imaging device, the image data evaluator deciding to use the first image data if the variation in ambient light over a sampling time interval is less than or equal to a maximum ambient light variation, as measured by the first optical sensor.
9. The system according to claim 8, further comprising a second optical sensor associated with the second imaging device, the image data evaluator deciding to use the second image data if the variation in ambient light over a sampling time interval is less than or equal to a maximum ambient light variation, as measured by the second optical sensor.
10. The system according to claim 1 , further comprising an image processing module associated with the first imaging device, the image data evaluator deciding to use the first image data if the variation in pixel intensity of a spout or spout end in the first image over a sampling time interval is less than or equal to a maximum pixel intensity variation, as detected by the image processing module.
1 1. The system according to claim 10, further comprising an image processing module associated with the second imaging device, the image data evaluator deciding to use the second image data if the variation in pixel intensity of a spout or spout end in the second image over a sampling time interval is less than or equal to a maximum pixel intensity variation, as detected by the image processing module.
12. The system according to claim 1 , further comprising: the image data evaluator adapted for determining whether to use the first image data, the second image data or both, for the identification of the bin perimeter and the identifying of the spout, based on pixel intensity in rejected image data being outside of a desired range or variation in pixel intensity during the sampling time interval, where the image data evaluator is configured to disable selectively the processing or use of the rejected image data that comprises a portion of the collected first image data or the second image data that would otherwise be corrupted by excessive transient sunlight during sunrise or sunset.
13. The system according to claim 1 , wherein at least one of the first imaging device and the second imaging device has its optical axis, perpendicular to its lens, tilted downward from a generally horizontal plane.
14. A method for facilitating the transfer of material from a transferring vehicle to a receiving vehicle, the method comprising the steps of: collecting first image data by a first imaging device facing towards a storage portion of a receiving vehicle, the storage portion capable of storing material; identifying a bin perimeter of the storage portion in the collected image data; identifying a spout of the transferring vehicle in the collected image data; determining the relative position of the spout and the bin perimeter; and generating command data for a propelled portion of the receiving vehicle to steer the storage portion in cooperative alignment such that the spout is aligned within a zone of the bin perimeter.
15. The method according to claim 14, further comprising the step of transmitting a data message for steering the receiving vehicle in accordance with the cooperative alignment.
16. The method according to claim 14, further comprising the steps of: collecting second image data by a second imaging device facing towards the storage portion of the receiving vehicle; and determining whether to use the first image data, the second image data or both for alignment of a relative position of the spout and the bin perimeter based on evaluation of material variation of intensity of pixel data or material variation in ambient light conditions during a sampling time interval.
17. The method according to claim 16, wherein the first imaging device has a first field of view of the storage portion and the second imaging device has a second field of view of the storage portion, the first field of view overlapping at least partially with the second field of view.
18. The method according to claim 16, wherein the first imaging device comprises a monocular imaging device, the second imaging device comprises a monocular imaging device; and further comprising the step of creating a stereo image from the first collected image data and the second collected image data with reference to the relative position and orientation of the first imaging device and the second imaging device.
19. The method according to claim 16, wherein an imaging processing module uses first location data of a first location determining receiver on the transferring vehicle and second location data of a second location determining receiver to determine a relative position of the first imaging device and the second imaging device and to determine a relative alignment between the spout and the bin perimeter.
20. The method according to claim 16, further comprising the step of deciding to use the first image data if the variation in ambient light over a sampling time interval is less than or equal to a maximum ambient light variation, as measured by a first optical sensor associated with the first imaging device.
21. The method according to claim 20 further comprising the step of deciding to use the second image data if the variation in ambient light over a sampling time interval is less than or equal to a maximum ambient light variation, as measured by the second optical sensor associated with a second imaging device.
22. The method according to claim 14, further comprising the step of deciding to use the first image data if the variation in pixel intensity of a spout or spout end in the first image over a sampling time interval is less than or equal to a maximum pixel intensity variation, as detected by the image processing module.
23. The method according to claim 22, further comprising the step of deciding to use the second image data if the variation in pixel intensity of a spout or spout end in the second image over a sampling time interval is less than or equal to a maximum pixel intensity variation, as detected by the image processing module.
24. The method according to claim 16 further comprising step of determining whether to use the first image data, the second image data or both, for the identification of the bin perimeter and the identifying of the spout, based on pixel intensity in rejected image data being outside of a desired range or variation in pixel intensity during the sampling time interval, where the image data evaluator is configured to disable selectively the processing or use of the rejected image data that comprises a portion of the collected first image data or the second image data that would otherwise be corrupted by excessive transient sunlight during sunrise or sunset.
25. The method according to claim 4 wherein at least one of the first imaging device and the second imaging device has its optical axis, perpendicular to its lens, tilted downward from a generally horizontal plane.
26. A system for facilitating the transfer of material from a transferring vehicle to a receiving vehicle, the system comprising: a receiving vehicle comprising a propelled portion for propelling the receiving vehicle and a storage portion for storing agricultural material; an imaging device facing towards the storage portion of the receiving vehicle, the first imaging device collecting image data; a bin identification module for identifying a bin perimeter of the storage portion in the collected image data; a spout identification module for identifying a spout of the transferring vehicle in the collected image data; an adjustable mast capable of adjusting a height of the imaging device within a height range and adjusting a down-tilt angle of the imaging device within a down-tilt angular range; an image processing module for determining whether to adjust the height of the imaging device or whether to decrement or increment the down-tilt angle of the imaging device based on evaluation of material variation of intensity of pixel data or material variation in ambient light conditions during a sampling time interval; an alignment module for determining the relative position of the spout and the bin perimeter and for generating command data to the propelled portion to steer the storage portion in cooperative alignment such that the spout is aligned within a central zone of the bin perimeter; and a steering controller associated with a steering system of the propelled portion for steering the receiving vehicle in accordance with the cooperative alignment.
27. The system according to claim 26, wherein the image processing module sends a data message to a mast controller to increment or increase the down-tilt angle if the material variation of intensity of pixel data or if the material variation in ambient light conditions exceeds a threshold variation level during a sampling time interval.
28. The system according to claim 26, wherein the image processing module sends a data message to a mast controller to increment or increase the down-tilt angle at discrete levels within an angular range of approximately negative ten degrees to approximately negative twenty-five degrees from a generally horizontal plane.
PCT/US2013/025588 2012-02-10 2013-02-11 System and method of material handling using one or more imaging devices on the transferring vehicle and on the receiving vehicle to control the material distribution into the storage portion of the receiving vehicle WO2013120079A1 (en)

Priority Applications (4)

Application Number Priority Date Filing Date Title
AU2013216776A AU2013216776B2 (en) 2012-02-10 2013-02-11 System and method of material handling using one or more imaging devices on the transferring vehicle and on the receiving vehicle to control the material distribution into the storage portion of the receiving vehicle
US14/377,413 US9522792B2 (en) 2012-02-10 2013-02-11 System and method of material handling using one or more imaging devices on the transferring vehicle and on the receiving vehicle to control the material distribution into the storage portion of the receiving vehicle
DE112013000929.3T DE112013000929T5 (en) 2012-02-10 2013-02-11 System and method for material transport with one or more imaging devices at the transferring vehicle and the receiving vehicle for controlling the distribution of material in the transport trailer of the receiving vehicle
GB1412567.8A GB2517292B (en) 2012-02-10 2013-02-11 System and method of material handling using one or more imaging devices

Applications Claiming Priority (6)

Application Number Priority Date Filing Date Title
US201261597380P 2012-02-10 2012-02-10
US201261597374P 2012-02-10 2012-02-10
US201261597346P 2012-02-10 2012-02-10
US61/597,346 2012-02-10
US61/597,380 2012-02-10
US61/597,374 2012-02-10

Publications (1)

Publication Number Publication Date
WO2013120079A1 true WO2013120079A1 (en) 2013-08-15

Family

ID=48948097

Family Applications (6)

Application Number Title Priority Date Filing Date
PCT/US2013/025581 WO2013151619A2 (en) 2012-02-10 2013-02-11 System and method of material handling using one imaging device on the receiving vehicle to control the material distribution into the storage portion of the receiving vehicle
PCT/US2013/025588 WO2013120079A1 (en) 2012-02-10 2013-02-11 System and method of material handling using one or more imaging devices on the transferring vehicle and on the receiving vehicle to control the material distribution into the storage portion of the receiving vehicle
PCT/US2013/025609 WO2013162673A2 (en) 2012-02-10 2013-02-11 System and method of material handling using one or more imaging devices on the transferring vehicle to control the material distribution into the storage portion of the receiving vehicle
PCT/US2013/025572 WO2013184177A2 (en) 2012-02-10 2013-02-11 System and method of material handling using one imaging device on the receiving vehicle to control the material distribution into the storage portion of the receiving vehicle
PCT/US2013/025587 WO2013141975A2 (en) 2012-02-10 2013-02-11 System and method of material handling using one or more imaging devices on the transferring vehicle and on the receiving vehicle to control the material distribution into the storage portion of the receiving vehicle
PCT/US2013/025604 WO2013184178A2 (en) 2012-02-10 2013-02-11 System and method of material handling using one or more imaging devices on the transferring vehicle to control the material distribution into the storage portion of the receiving vehicle

Family Applications Before (1)

Application Number Title Priority Date Filing Date
PCT/US2013/025581 WO2013151619A2 (en) 2012-02-10 2013-02-11 System and method of material handling using one imaging device on the receiving vehicle to control the material distribution into the storage portion of the receiving vehicle

Family Applications After (4)

Application Number Title Priority Date Filing Date
PCT/US2013/025609 WO2013162673A2 (en) 2012-02-10 2013-02-11 System and method of material handling using one or more imaging devices on the transferring vehicle to control the material distribution into the storage portion of the receiving vehicle
PCT/US2013/025572 WO2013184177A2 (en) 2012-02-10 2013-02-11 System and method of material handling using one imaging device on the receiving vehicle to control the material distribution into the storage portion of the receiving vehicle
PCT/US2013/025587 WO2013141975A2 (en) 2012-02-10 2013-02-11 System and method of material handling using one or more imaging devices on the transferring vehicle and on the receiving vehicle to control the material distribution into the storage portion of the receiving vehicle
PCT/US2013/025604 WO2013184178A2 (en) 2012-02-10 2013-02-11 System and method of material handling using one or more imaging devices on the transferring vehicle to control the material distribution into the storage portion of the receiving vehicle

Country Status (5)

Country Link
US (6) US9511958B2 (en)
AU (7) AU2013252988B2 (en)
DE (6) DE112013000947T5 (en)
GB (8) GB2555730B (en)
WO (6) WO2013151619A2 (en)

Cited By (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2015032809A1 (en) * 2013-09-03 2015-03-12 Cnh Industrial Belgium Nv Unloading system for agricultural harvesting machines
WO2015063078A1 (en) 2013-10-28 2015-05-07 Cnh Industrial Belgium Nv Unloading systems
WO2015063107A1 (en) * 2013-10-28 2015-05-07 Cnh Industrial Belgium Nv Unloading systems
EP2893797A3 (en) * 2014-01-08 2015-08-12 CLAAS Selbstfahrende Erntemaschinen GmbH Harvesting device
EP2954770A1 (en) * 2014-06-13 2015-12-16 CNH Industrial Belgium nv System and method for calibrating alignment of agricultural vehicles
EP2980669A3 (en) * 2014-08-01 2016-03-02 AGCO Corporation Determining field characterisitics using optical recognition
US9915952B2 (en) 2014-06-13 2018-03-13 Cnh Industrial America Llc System and method for coordinated control of agricultural vehicles
CN111348554A (en) * 2018-12-21 2020-06-30 卡哥特科专利许可有限公司 Vehicle provided with a control system and method relating to such a vehicle
EP3747248A1 (en) * 2019-05-31 2020-12-09 Deere & Company Sensor assembly for an agricultural vehicle
US20210015042A1 (en) * 2018-01-29 2021-01-21 Deere & Company Monitor and control system for a harvester
US11744180B2 (en) 2018-01-29 2023-09-05 Deere & Company Harvester crop mapping
US12082531B2 (en) 2022-01-26 2024-09-10 Deere & Company Systems and methods for predicting material dynamics

Families Citing this family (98)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9861040B2 (en) 2012-02-10 2018-01-09 Deere & Company Method and stereo vision system for facilitating the unloading of agricultural material from a vehicle
AU2013252988B2 (en) * 2012-02-10 2017-01-19 Carnegie Mellon University System and method of material handling on transferring vehicle to control material distribution to receiving vehicle
US20160110791A1 (en) * 2014-10-15 2016-04-21 Toshiba Global Commerce Solutions Holdings Corporation Method, computer program product, and system for providing a sensor-based environment
US10560245B2 (en) * 2014-10-21 2020-02-11 Lg Electronics Inc. Data transmission/reception method in wireless communication system that supports low latency, and apparatus therefor
US9655205B2 (en) * 2015-02-17 2017-05-16 Pointgrab Ltd. Method and system for calculating ambient light
DE102015004330A1 (en) 2015-04-09 2016-10-13 Eisenmann Se Position and position recognition for a conveyor
EP3998455A1 (en) * 2015-08-03 2022-05-18 TomTom Global Content B.V. Methods and systems for generating and using localisation reference data
US9642305B2 (en) 2015-08-10 2017-05-09 Deere & Company Method and stereo vision system for managing the unloading of an agricultural material from a vehicle
US10015928B2 (en) 2015-08-10 2018-07-10 Deere & Company Method and stereo vision system for managing the unloading of an agricultural material from a vehicle
EP3150052B1 (en) 2015-09-30 2018-06-13 CLAAS E-Systems KGaA mbH & Co KG Crop harvesting machine
US10067029B2 (en) * 2016-02-12 2018-09-04 Google Llc Systems and methods for estimating modulation transfer function in an optical system
EP3445918B1 (en) * 2016-04-19 2021-10-27 Volvo Construction Equipment AB Control unit for dumping of material
US10489662B2 (en) 2016-07-27 2019-11-26 Ford Global Technologies, Llc Vehicle boundary detection
CN106274907A (en) * 2016-08-12 2017-01-04 浙江零跑科技有限公司 A kind of many trains splice angle vision measurement optimization method based on Kalman filtering
US20180047177A1 (en) * 2016-08-15 2018-02-15 Raptor Maps, Inc. Systems, devices, and methods for monitoring and assessing characteristics of harvested specialty crops
US10488493B2 (en) * 2016-09-27 2019-11-26 Denso International America, Inc. Sensor array for autonomous vehicle
US10721859B2 (en) 2017-01-08 2020-07-28 Dolly Y. Wu PLLC Monitoring and control implement for crop improvement
US10255670B1 (en) 2017-01-08 2019-04-09 Dolly Y. Wu PLLC Image sensor and module for agricultural crop improvement
WO2018172614A1 (en) * 2017-03-22 2018-09-27 Nokia Technologies Oy A method and an apparatus and a computer program product for adaptive streaming
CA3008116C (en) * 2017-06-19 2020-08-18 GrainX Incorporated Agricultural product storage system including adaptive conditioning control function dependent upon state of storage
US10196047B1 (en) 2017-08-07 2019-02-05 Ford Global Technologies, Llc Contamination prevention of vehicle cameras and sensors
US11040828B1 (en) * 2017-10-13 2021-06-22 Amazon Technologies, Inc. Modular transfer units for delivering items
CN110022264B (en) * 2018-01-08 2020-09-08 华为技术有限公司 Method for controlling network congestion, access device and computer readable storage medium
US20190230848A1 (en) * 2018-01-30 2019-08-01 Cnh Industrial Canada, Ltd. Sensing and agitation control system for particulate material
US10817755B2 (en) 2018-06-22 2020-10-27 Cnh Industrial Canada, Ltd. Measuring crop residue from imagery using a machine-learned classification model in combination with principal components analysis
US11079725B2 (en) 2019-04-10 2021-08-03 Deere & Company Machine control using real-time model
US11641800B2 (en) 2020-02-06 2023-05-09 Deere & Company Agricultural harvesting machine with pre-emergence weed detection and mitigation system
US11589509B2 (en) 2018-10-26 2023-02-28 Deere & Company Predictive machine characteristic map generation and control system
US12069978B2 (en) 2018-10-26 2024-08-27 Deere & Company Predictive environmental characteristic map generation and control system
US11957072B2 (en) 2020-02-06 2024-04-16 Deere & Company Pre-emergence weed detection and mitigation system
US11467605B2 (en) 2019-04-10 2022-10-11 Deere & Company Zonal machine control
US11672203B2 (en) 2018-10-26 2023-06-13 Deere & Company Predictive map generation and control
US11653588B2 (en) 2018-10-26 2023-05-23 Deere & Company Yield map generation and control system
US11240961B2 (en) 2018-10-26 2022-02-08 Deere & Company Controlling a harvesting machine based on a geo-spatial representation indicating where the harvesting machine is likely to reach capacity
US11178818B2 (en) 2018-10-26 2021-11-23 Deere & Company Harvesting machine control system with fill level processing based on yield data
US11297763B2 (en) 2019-02-01 2022-04-12 Cnh Industrial Canada, Ltd. Agitation and leveling system for particulate material
US11665995B2 (en) * 2019-02-01 2023-06-06 Cnh Industrial Canada, Ltd. Agitation control system
US10744943B1 (en) * 2019-04-08 2020-08-18 Ford Global Technologies, Llc System and method for trailer alignment
US11778945B2 (en) 2019-04-10 2023-10-10 Deere & Company Machine control using real-time model
US11234366B2 (en) 2019-04-10 2022-02-01 Deere & Company Image selection for machine control
CN110400263B (en) * 2019-04-13 2020-10-09 浙江辛巴达机器人科技有限公司 Action execution system based on data detection
CN111240234B (en) * 2019-04-13 2020-11-17 万金芬 Action execution method based on data detection
EP3733970B1 (en) * 2019-04-30 2021-03-17 Joseph Vögele AG Road finisher or feeder with a firewall
US11226627B2 (en) * 2019-06-20 2022-01-18 Caterpillar Global Mining Llc System for modifying a spot location
CN110588773A (en) * 2019-09-16 2019-12-20 山东沃华农业科技股份有限公司 Harvester steering control system and harvester thereof
US11358637B2 (en) * 2019-12-16 2022-06-14 GM Global Technology Operations LLC Method and apparatus for determining a trailer hitch articulation angle in a motor vehicle
US11659788B2 (en) 2019-12-31 2023-05-30 Deere & Company Vehicle automated unloading
US12035648B2 (en) 2020-02-06 2024-07-16 Deere & Company Predictive weed map generation and control system
US12016257B2 (en) 2020-02-19 2024-06-25 Sabanto, Inc. Methods for detecting and clearing debris from planter gauge wheels, closing wheels and seed tubes
DE102020203524A1 (en) 2020-03-19 2021-09-23 Deere & Company Damping of pitching vibrations of a work vehicle by changing the speed and adjusting an element taking into account the operating mode
US11477940B2 (en) 2020-03-26 2022-10-25 Deere & Company Mobile work machine control based on zone parameter modification
US11635768B2 (en) 2020-04-28 2023-04-25 Cnh Industrial America Llc System for coordinating control of multiple work vehicles
US11390263B2 (en) * 2020-05-04 2022-07-19 Deere & Company Forage harvester with automatic detection of receiving vehicle
US20220071078A1 (en) * 2020-09-04 2022-03-10 Deere & Company Automatic machine guidance initiation for agricultural machine during unloading
EP3967983A1 (en) * 2020-09-14 2022-03-16 Mettler-Toledo (Albstadt) GmbH Method, apparatus and computer program for displaying an evolution of a filling quantity
US11856889B2 (en) * 2020-09-28 2024-01-02 Deere & Company Automated camera system control for harvesting machine unloading
US11727680B2 (en) 2020-10-09 2023-08-15 Deere & Company Predictive map generation based on seeding characteristics and control
US11849671B2 (en) 2020-10-09 2023-12-26 Deere & Company Crop state map generation and control system
US11474523B2 (en) 2020-10-09 2022-10-18 Deere & Company Machine control using a predictive speed map
US11983009B2 (en) 2020-10-09 2024-05-14 Deere & Company Map generation and control system
US11844311B2 (en) 2020-10-09 2023-12-19 Deere & Company Machine control using a predictive map
US11895948B2 (en) 2020-10-09 2024-02-13 Deere & Company Predictive map generation and control based on soil properties
US11871697B2 (en) 2020-10-09 2024-01-16 Deere & Company Crop moisture map generation and control system
US11946747B2 (en) 2020-10-09 2024-04-02 Deere & Company Crop constituent map generation and control system
US11889788B2 (en) 2020-10-09 2024-02-06 Deere & Company Predictive biomass map generation and control
US12013245B2 (en) 2020-10-09 2024-06-18 Deere & Company Predictive map generation and control system
US11849672B2 (en) 2020-10-09 2023-12-26 Deere & Company Machine control using a predictive map
US12069986B2 (en) 2020-10-09 2024-08-27 Deere & Company Map generation and control system
US11845449B2 (en) 2020-10-09 2023-12-19 Deere & Company Map generation and control system
US11874669B2 (en) 2020-10-09 2024-01-16 Deere & Company Map generation and control system
US11592822B2 (en) 2020-10-09 2023-02-28 Deere & Company Machine control using a predictive map
US11635765B2 (en) 2020-10-09 2023-04-25 Deere & Company Crop state map generation and control system
US11825768B2 (en) 2020-10-09 2023-11-28 Deere & Company Machine control using a predictive map
US11927459B2 (en) 2020-10-09 2024-03-12 Deere & Company Machine control using a predictive map
US11711995B2 (en) 2020-10-09 2023-08-01 Deere & Company Machine control using a predictive map
US11675354B2 (en) 2020-10-09 2023-06-13 Deere & Company Machine control using a predictive map
US11650587B2 (en) 2020-10-09 2023-05-16 Deere & Company Predictive power map generation and control system
US11864483B2 (en) 2020-10-09 2024-01-09 Deere & Company Predictive map generation and control system
US11889787B2 (en) 2020-10-09 2024-02-06 Deere & Company Predictive speed map generation and control system
US11980134B2 (en) * 2021-03-09 2024-05-14 Deere & Company Operator commanded placement for control of filling mechanisms
US12004449B2 (en) 2021-03-24 2024-06-11 Deere & Company Control system for controlling filling mechanisms in communication with a mobile device
DE102021204054B3 (en) 2021-04-23 2022-09-01 Zf Friedrichshafen Ag Body panel assembly and vehicle
US12071746B2 (en) 2021-05-12 2024-08-27 Deere & Company System and method for assisted positioning of transport vehicles relative to a work machine during material loading
US11953337B2 (en) 2021-05-12 2024-04-09 Deere & Company System and method for assisted positioning of transport vehicles for material discharge in a worksite
EP4341053A1 (en) * 2021-05-18 2024-03-27 Mujin, Inc. A robotic system for object size measurement
US11966220B2 (en) 2021-05-25 2024-04-23 Deere & Company Method and user interface for selectively assisted automation of loading operation stages for work vehicles
US11930738B2 (en) 2021-06-28 2024-03-19 Deere & Company Closed loop control of filling mechanisms
JP2023013128A (en) * 2021-07-15 2023-01-26 株式会社マキタ Dolly
US12089529B2 (en) * 2021-07-22 2024-09-17 Cnh Industrial America Llc System and method for controlling crop unloading tube position of an agricultural harvester
US12036958B2 (en) 2021-09-17 2024-07-16 Deere & Company Selectively implementing automated cleaning routines during unloading cycles for transport vehicles
US11970179B2 (en) 2021-09-29 2024-04-30 Zero Motorcycles, Inc. Turn signal cancelation systems and methods for two-wheeled vehicles
DE102021214119B3 (en) 2021-12-10 2023-02-16 Zf Friedrichshafen Ag Supervision of the dumping of material
US12058951B2 (en) 2022-04-08 2024-08-13 Deere & Company Predictive nutrient map and control
USD1030806S1 (en) 2022-05-09 2024-06-11 Deere & Company Display screen or portion thereof with an icon
USD1046915S1 (en) 2022-05-09 2024-10-15 Deere & Company Display screen or portion thereof with an icon
USD1034674S1 (en) 2022-05-09 2024-07-09 Deere & Company Display screen with an animated graphical user interface
USD1036466S1 (en) 2022-05-09 2024-07-23 Deere & Company Display screen with an animated graphical user interface
CN115006710B (en) * 2022-06-20 2024-05-14 楚天科技股份有限公司 Grain filling system and grain filling method

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5742340A (en) * 1995-06-06 1998-04-21 Hughes Missile Systems Company Ambient light automatic gain control for electronic imaging cameras and the like
US5749783A (en) * 1995-08-29 1998-05-12 Claas Kgaa Device for automatic filling of load containers
US20030174207A1 (en) * 2002-03-13 2003-09-18 Deere & Company, A Delaware Corporation Image processing spout control system
US20050074183A1 (en) * 2003-09-19 2005-04-07 Narlow Douglas A. Object recognition system including an adaptive light source
US20100063692A1 (en) * 2008-06-25 2010-03-11 Tommy Ertbolle Madsen Transferring device and an agricultural vehicle
US20100332051A1 (en) * 2009-06-26 2010-12-30 Georg Kormann Control Arrangement For Controlling The Transfer Of Agricultural Crop From A Harvesting Machine To A Transport Vehicle

Family Cites Families (51)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH02177815A (en) 1988-12-28 1990-07-10 Iseki & Co Ltd Grain-discharging system for combine
ZA952853B (en) 1994-04-18 1995-12-21 Caterpillar Inc Method and apparatus for real time monitoring and co-ordination of multiple geography altering machines on a work site
DE4426059C2 (en) * 1994-07-25 2001-07-05 Case Harvesting Sys Gmbh harvester
DE19514223B4 (en) 1995-04-15 2005-06-23 Claas Kgaa Mbh Method for optimizing the use of agricultural machinery
JPH0977267A (en) * 1995-09-19 1997-03-25 Mitsubishi Heavy Ind Ltd Unloading and loading device
AU7110698A (en) * 1997-04-16 1998-11-11 Carnegie Wave Energy Limited Agricultural harvester with robotic control
US5842920A (en) * 1997-06-09 1998-12-01 Siepker; Gary Grain cart periscope
US5881780A (en) * 1997-08-05 1999-03-16 Dcl, Inc. Apapratus for and method of locating the center of an opening in a vehicle
JP3038474B2 (en) * 1998-09-11 2000-05-08 五洋建設株式会社 Method and apparatus for measuring the amount of soil loaded on an earth moving ship
US6216071B1 (en) 1998-12-16 2001-04-10 Caterpillar Inc. Apparatus and method for monitoring and coordinating the harvesting and transporting operations of an agricultural crop by multiple agricultural machines on a field
US6682416B2 (en) 2000-12-23 2004-01-27 Claas Selbstfahrende Erntemaschinen Gmbh Automatic adjustment of a transfer device on an agricultural harvesting machine
US6732024B2 (en) 2001-05-07 2004-05-04 The Board Of Trustees Of The Leland Stanford Junior University Method and apparatus for vehicle control, navigation and positioning
DE10224939B4 (en) 2002-05-31 2009-01-08 Deere & Company, Moline Driving-axle trailer
US6687616B1 (en) 2002-09-09 2004-02-03 Pioneer Hi-Bred International, Inc. Post-harvest non-containerized reporting system
GB0223867D0 (en) * 2002-10-14 2002-11-20 Sumpter Derek E Material and waste transportation
DE20307086U1 (en) * 2003-05-08 2004-09-16 Haver & Boecker Device for loading vehicles with bulk and / or flowable goods
DE102004039460B3 (en) * 2004-08-14 2006-04-20 Deere & Company, Moline A system for determining the relative position of a second agricultural vehicle with respect to a first agricultural vehicle
DE102004052298A1 (en) * 2004-10-06 2006-06-08 Claas Selbstfahrende Erntemaschinen Gmbh Overcharge assistance system
RU2385286C2 (en) 2004-12-14 2010-03-27 Нестек С.А. Device and method for controlling cup being filled with drinks in automatic slot machines, such as automatic coffee slot machine
WO2006084385A1 (en) * 2005-02-11 2006-08-17 Macdonald Dettwiler & Associates Inc. 3d imaging system
US8185275B2 (en) * 2005-07-01 2012-05-22 Deere & Company System for vehicular guidance with respect to harvested crop
US7610122B2 (en) * 2005-08-16 2009-10-27 Deere & Company Mobile station for an unmanned vehicle
US8942483B2 (en) * 2009-09-14 2015-01-27 Trimble Navigation Limited Image-based georeferencing
US8108063B2 (en) * 2006-06-22 2012-01-31 International Business Machines Corporation User interface for color transfer control in textile processing equipment
DE102007009666A1 (en) 2007-02-22 2008-08-28 Carl Zeiss Microimaging Gmbh Arrangement for filling a container with bulk material
EP2020174B1 (en) 2007-08-03 2012-02-29 AGROCOM GmbH & Co. Agrarsystem KG Agricultural working machine
US8060283B2 (en) * 2007-10-15 2011-11-15 Deere & Company Method and system for controlling the loading of a container associated with a vehicle
DE102008015277A1 (en) * 2008-03-20 2009-09-24 Deere & Company, Moline Method and device for steering a second agricultural machine, which is steerable over a field relative to a first agricultural machine
US8487991B2 (en) * 2008-04-24 2013-07-16 GM Global Technology Operations LLC Clear path detection using a vanishing point
WO2010022062A2 (en) * 2008-08-18 2010-02-25 Mylet Niel T Monitoring and control system for commodity loading
US8180534B2 (en) 2008-09-18 2012-05-15 Deere & Company Multiple harvester unloading system
US8498480B2 (en) 2009-02-25 2013-07-30 The United States Of America, As Represented By The Secretary Of The Navy Computationally efficient method for image segmentation with intensity and texture discrimination
EP2301318B1 (en) 2009-09-07 2011-11-16 CLAAS Agrosystems GmbH & Co. KG A control system of an agricultural vehicle with a goods carrier, an agricultural vehicle and a method of controlling a goods carrier of the agricultural vehicle
PL2311307T3 (en) 2009-09-07 2012-09-28 Claas E Systems Gmbh A filling degree gauge, an agricultural vehicle comprising such gauge, and a method of controlling filling of a target area
BE1019192A3 (en) * 2010-02-21 2012-04-03 Cnh Belgium Nv METHOD FOR DIRECTING A DISCHARGE DEVICE FROM A HARVESTING MACHINE TO A CONTAINER.
US8451139B2 (en) 2010-02-22 2013-05-28 Cnh America Llc System and method for coordinating harvester and transport vehicle unloading operations
US8380401B2 (en) * 2010-06-09 2013-02-19 Cnh America Llc Automatic grain transfer control system based on real time modeling of a fill level profile for regions of the receiving container
US8749628B2 (en) * 2011-02-08 2014-06-10 Trimble Navigation Limited Dry agricultural materials management
DE102011002071A1 (en) * 2011-04-15 2012-10-18 Claas Selbstfahrende Erntemaschinen Gmbh System and method for controlling crop overload
US9545048B2 (en) * 2011-08-15 2017-01-17 Deere & Company System for automated unloading of an agricultural material
DE102011082052B4 (en) * 2011-09-02 2015-05-28 Deere & Company Arrangement and method for the automatic overloading of crop material from a harvester onto a transport vehicle
BE1020293A3 (en) * 2011-11-10 2013-07-02 Cnh Belgium Nv METHOD FOR SENDING A CAMERA SYSTEM ON AGRICULTURAL MACHINES
US8868304B2 (en) * 2012-02-10 2014-10-21 Deere & Company Method and stereo vision system for facilitating the unloading of agricultural material from a vehicle
AU2013252988B2 (en) * 2012-02-10 2017-01-19 Carnegie Mellon University System and method of material handling on transferring vehicle to control material distribution to receiving vehicle
US9392746B2 (en) * 2012-02-10 2016-07-19 Deere & Company Artificial intelligence for detecting and filling void areas of agricultural commodity containers
US8649940B2 (en) * 2012-02-10 2014-02-11 Deere & Company Method and stereo vision system for managing the unloading of an agricultural material from a vehicle
US9861040B2 (en) * 2012-02-10 2018-01-09 Deere & Company Method and stereo vision system for facilitating the unloading of agricultural material from a vehicle
US9326444B2 (en) * 2013-02-08 2016-05-03 Deere & Company Method and stereo vision system for facilitating the unloading of agricultural material from a vehicle
EP2792229B1 (en) * 2013-04-02 2016-03-23 Deere & Company Control arrangement and method for controlling a position of a transfer device of a harvesting machine
DE102014105643A1 (en) * 2013-04-22 2014-10-23 Carnegie Mellon University Method for improving the robustness of an automated end-loading system
US10015928B2 (en) * 2015-08-10 2018-07-10 Deere & Company Method and stereo vision system for managing the unloading of an agricultural material from a vehicle

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5742340A (en) * 1995-06-06 1998-04-21 Hughes Missile Systems Company Ambient light automatic gain control for electronic imaging cameras and the like
US5749783A (en) * 1995-08-29 1998-05-12 Claas Kgaa Device for automatic filling of load containers
US20030174207A1 (en) * 2002-03-13 2003-09-18 Deere & Company, A Delaware Corporation Image processing spout control system
US20050074183A1 (en) * 2003-09-19 2005-04-07 Narlow Douglas A. Object recognition system including an adaptive light source
US20100063692A1 (en) * 2008-06-25 2010-03-11 Tommy Ertbolle Madsen Transferring device and an agricultural vehicle
US20100332051A1 (en) * 2009-06-26 2010-12-30 Georg Kormann Control Arrangement For Controlling The Transfer Of Agricultural Crop From A Harvesting Machine To A Transport Vehicle

Cited By (21)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2015032809A1 (en) * 2013-09-03 2015-03-12 Cnh Industrial Belgium Nv Unloading system for agricultural harvesting machines
BE1021106B1 (en) * 2013-09-03 2016-03-15 Cnh Industrial Belgium Nv DISCHARGING DEVICES FOR HARVESTERS FOR USE IN AGRICULTURE
WO2015063078A1 (en) 2013-10-28 2015-05-07 Cnh Industrial Belgium Nv Unloading systems
WO2015063107A1 (en) * 2013-10-28 2015-05-07 Cnh Industrial Belgium Nv Unloading systems
US10681872B2 (en) 2013-10-28 2020-06-16 Cnh Industrial America Llc Controller configured for controlling an unloading system and related methods
BE1021108B1 (en) * 2013-10-28 2016-01-18 Cnh Industrial Belgium Nv DISCHARGE SYSTEMS
BE1021164B1 (en) * 2013-10-28 2016-01-18 Cnh Industrial Belgium Nv DISCHARGE SYSTEMS
US20160270294A1 (en) * 2013-10-28 2016-09-22 Cnh Industrial America Llc Unloading Systems
EP2893797A3 (en) * 2014-01-08 2015-08-12 CLAAS Selbstfahrende Erntemaschinen GmbH Harvesting device
RU2672401C2 (en) * 2014-01-08 2018-11-14 КЛААС Зельбстфаренде Эрнтемашинен ГмбХ Complex of machines for cleaning harvest containing agricultural cleaning machine and vehicle, and a method of speed regulation of such complex
US9462748B2 (en) 2014-06-13 2016-10-11 Cnh Industrial America Llc System and method for calibrating alignment of agricultural vehicles
US9915952B2 (en) 2014-06-13 2018-03-13 Cnh Industrial America Llc System and method for coordinated control of agricultural vehicles
EP2954770A1 (en) * 2014-06-13 2015-12-16 CNH Industrial Belgium nv System and method for calibrating alignment of agricultural vehicles
EP2980669A3 (en) * 2014-08-01 2016-03-02 AGCO Corporation Determining field characterisitics using optical recognition
US10390472B2 (en) 2014-08-01 2019-08-27 Agco Corporation Determining field characteristics using optical recognition
US20210015042A1 (en) * 2018-01-29 2021-01-21 Deere & Company Monitor and control system for a harvester
US11744180B2 (en) 2018-01-29 2023-09-05 Deere & Company Harvester crop mapping
US11812694B2 (en) * 2018-01-29 2023-11-14 Deere & Company Monitor system for a harvester
CN111348554A (en) * 2018-12-21 2020-06-30 卡哥特科专利许可有限公司 Vehicle provided with a control system and method relating to such a vehicle
EP3747248A1 (en) * 2019-05-31 2020-12-09 Deere & Company Sensor assembly for an agricultural vehicle
US12082531B2 (en) 2022-01-26 2024-09-10 Deere & Company Systems and methods for predicting material dynamics

Also Published As

Publication number Publication date
GB2549430B (en) 2018-03-21
WO2013184178A3 (en) 2015-06-18
AU2017202408B2 (en) 2018-08-23
DE112013000938B4 (en) 2021-04-22
GB201711057D0 (en) 2017-08-23
WO2013184178A2 (en) 2013-12-12
DE112013000929T5 (en) 2015-03-12
DE112013000936T5 (en) 2014-11-27
AU2013216776A1 (en) 2014-08-21
GB2517293B (en) 2017-11-08
AU2013272263B2 (en) 2017-04-20
WO2013162673A2 (en) 2013-10-31
GB201412565D0 (en) 2014-08-27
GB2555730B (en) 2018-08-01
WO2013141975A2 (en) 2013-09-26
WO2013151619A3 (en) 2013-12-05
AU2017202408A1 (en) 2017-05-18
US20150109410A1 (en) 2015-04-23
GB2549430A (en) 2017-10-18
GB201412567D0 (en) 2014-08-27
US20140350801A1 (en) 2014-11-27
WO2013151619A2 (en) 2013-10-10
US20150378359A1 (en) 2015-12-31
WO2013141975A3 (en) 2015-06-18
AU2013243995A1 (en) 2014-08-21
AU2013235751A1 (en) 2014-08-21
GB2511714B (en) 2017-12-27
GB2525260A (en) 2015-10-21
GB201412569D0 (en) 2014-08-27
AU2013272264B2 (en) 2017-05-04
WO2013162673A3 (en) 2014-05-30
AU2013272264A1 (en) 2014-08-21
AU2013243995B2 (en) 2017-04-20
US9511958B2 (en) 2016-12-06
US9522792B2 (en) 2016-12-20
DE112013000935T5 (en) 2015-03-12
GB2511715B (en) 2018-06-13
US9457971B2 (en) 2016-10-04
GB2511715A (en) 2014-09-10
GB2517292B (en) 2017-11-08
AU2013216776B2 (en) 2017-01-19
DE112013000947T5 (en) 2015-02-05
US20150356722A1 (en) 2015-12-10
GB2525260B (en) 2017-11-08
WO2013184177A3 (en) 2014-02-27
US9463939B2 (en) 2016-10-11
GB2555730A (en) 2018-05-09
GB2517294A (en) 2015-02-18
GB201719461D0 (en) 2018-01-10
DE112013000939T5 (en) 2014-11-06
US9522791B2 (en) 2016-12-20
AU2013252988B2 (en) 2017-01-19
WO2013184177A2 (en) 2013-12-12
GB201412568D0 (en) 2014-08-27
AU2013252988A1 (en) 2014-08-21
DE112013000938T5 (en) 2014-11-06
GB2517292A (en) 2015-02-18
GB201412570D0 (en) 2014-08-27
GB2517294B (en) 2017-11-08
GB2517293A (en) 2015-02-18
GB2511714A (en) 2014-09-10
WO2013184178A9 (en) 2014-01-30
US9415953B2 (en) 2016-08-16
AU2013272263A1 (en) 2014-08-21
US20160009509A1 (en) 2016-01-14
GB201412566D0 (en) 2014-08-27
US20150023775A1 (en) 2015-01-22

Similar Documents

Publication Publication Date Title
AU2017202408B2 (en) System and method of material handling using one or more imaging devices on the transferring vehicle and on the receiving vehicle to control the material distribution into the storage portion of the receiving vehicle
US11252869B2 (en) Imaging system for facilitating the unloading of agricultural material from a vehicle
US9326444B2 (en) Method and stereo vision system for facilitating the unloading of agricultural material from a vehicle
US8649940B2 (en) Method and stereo vision system for managing the unloading of an agricultural material from a vehicle
US8868304B2 (en) Method and stereo vision system for facilitating the unloading of agricultural material from a vehicle

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 13746978

Country of ref document: EP

Kind code of ref document: A1

ENP Entry into the national phase

Ref document number: 1412567

Country of ref document: GB

Kind code of ref document: A

Free format text: PCT FILING DATE = 20130211

WWE Wipo information: entry into national phase

Ref document number: 1412567.8

Country of ref document: GB

WWE Wipo information: entry into national phase

Ref document number: 14377413

Country of ref document: US

WWE Wipo information: entry into national phase

Ref document number: 112013000929

Country of ref document: DE

Ref document number: 1120130009293

Country of ref document: DE

ENP Entry into the national phase

Ref document number: 2013216776

Country of ref document: AU

Date of ref document: 20130211

Kind code of ref document: A

122 Ep: pct application non-entry in european phase

Ref document number: 13746978

Country of ref document: EP

Kind code of ref document: A1