WO2006073739A2 - Method and system for guiding a vehicle with vision-based adjustment - Google Patents

Method and system for guiding a vehicle with vision-based adjustment Download PDF

Info

Publication number
WO2006073739A2
WO2006073739A2 PCT/US2005/045616 US2005045616W WO2006073739A2 WO 2006073739 A2 WO2006073739 A2 WO 2006073739A2 US 2005045616 W US2005045616 W US 2005045616W WO 2006073739 A2 WO2006073739 A2 WO 2006073739A2
Authority
WO
WIPO (PCT)
Prior art keywords
vision
location data
data
derived
location
Prior art date
Application number
PCT/US2005/045616
Other languages
French (fr)
Other versions
WO2006073739A3 (en
Inventor
Shufeng Han
John Franklin Reid
Terence Daniel Pickett
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 BRPI0519300-1A priority Critical patent/BRPI0519300B1/en
Priority to AU2005323178A priority patent/AU2005323178A1/en
Priority to CA2592996A priority patent/CA2592996C/en
Priority to EP05854355.4A priority patent/EP1836648B1/en
Publication of WO2006073739A2 publication Critical patent/WO2006073739A2/en
Publication of WO2006073739A3 publication Critical patent/WO2006073739A3/en

Links

Classifications

    • 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
    • G05D1/0276Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
    • G05D1/0278Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using satellite positioning signals, e.g. GPS
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42Determining position
    • G01S19/48Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system
    • G01S19/485Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system whereby the further system is an optical system or imaging system
    • 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

Definitions

  • This invention relates to a method and system for guiding a vehicle with vision adjustment.
  • GPS receivers have been used for providing position data for vehicular guidance applications.
  • certain GPS receivers with differential correction may have a general positioning error of approximately 10 centimeters (4 inches) during a majority of their operational time, an absolute positioning error of more than 50 centimeter (20 inches) is typical for five percent of their operational time.
  • GPS signals may be blocked by buildings, trees or other obstructions, which can make GPS-only navigation system unreliable in certain locations or environments. Accordingly, there is a need for supplementing or enhancing a GPS-based navigation system with one or more additional sensors to increase accuracy and robustness.
  • a method and system for guiding a vehicle comprises a location module (e.g., location-determining receiver) for collecting preliminary location data for the vehicle.
  • a vision module collects vision-derived location data for the vehicle during an evaluation time window.
  • a vision module estimates vision quality data for the corresponding collected vision-derived location data during the evaluation time window.
  • a adjuster adjusts the preliminary location data to a revised location data based on the vision-derived location data such that the revised location data is registered with or generally coextensive with the vision-derived location data, if the vision quality data exceeds the minimum threshold level.
  • FIG. 1 is a block diagram of a system for guiding a vehicle based on preliminary location data and vision-derived location data in accordance with the invention.
  • FIG. 2 is a flow chart of a method for guiding a vehicle based on preliminary location data and vision-derived location data in accordance with the invention.
  • FIG. 3 is a flow chart of another method for guiding a vehicle based on preliminary location data and vision-derived location data in accordance with the invention.
  • FIG. 4 is a chart that illustrates static positioning error of location data, such as a guidance signal derived from differential Global Positioning System (GPS).
  • FIG. 5 is a chart that illustrates positioning error of location data, such as a guidance signal derived from differential Global Positioning System (GPS) signal after "tuning" by another sensor, such as a vision module in accordance with the invention.
  • GPS Global Positioning System
  • FIG. 1 is a block diagram of a guidance system 11 for guiding a vehicle.
  • the guidance system 11 may be mounted on or collocated with a vehicle or mobile robot.
  • the guidance system 11 comprises a vision module 22 and a location- determining receiver 28 that communicates with an adjuster 110.
  • the vision module 22 may be associated with a vision quality estimator 20.
  • the location-determining receiver 28 may be associated with a location quality estimator 24.
  • the adjuster 110 may communicate with a vehicular controller 25. In turn, the vehicular controller 25 is coupled to a steering system 27.
  • the location-determining receiver 28 may comprise a Global Positioning System (GPS) receiver with differential correction (e.g., a GPS receiver and a receiver for receiving a differential correction signal transmitted by a satellite or terrestrial source).
  • GPS Global Positioning System
  • the location determining receiver 28 provides location data (e.g., coordinates) of a vehicle.
  • the location-determining receiver 28 may indicate one or more of the following conditions or status (e.g., via a status signal) to at least the adjuster 110 or the location quality estimator 24: (1) where the location-determining receiver 28 is disabled, (2) where location data is not available or corrupt for one or more corresponding evaluation intervals, and (3) where the estimated accuracy or reliability of the location data falls below a minimum threshold for one or more evaluation intervals.
  • the location-determining receiver 28 provides location data for a vehicle that is well-suited for global navigation or global path planning.
  • the location-determining receiver 28 outputs location data in the following format:
  • the vision module 22 may comprise an image collection system and an image processing system.
  • the image collection system may comprise one or more of the following: (1) one or more monocular imaging systems for collecting a group of images (e.g., multiple images of the same scene with different focus settings or lens adjustments, or multiple images for different field of views (FOV)); (2) a stereo vision system (e.g., two digital imaging units separated by a known distance and orientation) for determining depth information or three-dimensional coordinates associated with points on an object in a scene; (3) a range finder (e.g., laser range finder) for determining range measurements or three-dimensional coordinates of points on an object in a scene; (4) a ladar system or laser radar system for detecting the speed, altitude, direction or range of an object in a scene; (5) a scanning laser system (e.g., a laser measurement system that transmits a pulse of light and estimates distance between the laser measurement system and the object based on the time of propagation between transmission of the pulse and reception of its reflection) for determining a distance to an object in a scene; and (6) an imaging system for
  • Free-space optical MEMS use compound semiconductors and materials with a range or refractive indexes to manipulate visible light, infra-red, or ultraviolet light
  • integrated optical MEMS use polysilicon components to reflect, diffract, modulate or manipulate visible light, infra-red, or ultraviolet light.
  • MEMS may be structured as switching matrixes, lens, mirrors and diffraction gratings that can be fabricated in accordance with various semiconductor fabrication techniques.
  • the images collected by the image processing system may be in color, monochrome, black-and-white, or grey-scale images, for example.
  • the vision module 22 or vision-derived location data may support the collection of position data (in two or three dimensional coordinates) corresponding to the location of features of an object within the image.
  • the vision module 22 is well suited for using (a) features or local features of an environment around a vehicle, (b) position data or coordinates associated with such features, or both to facilitate navigation of the vehicle.
  • the local features may comprise one or more of the following: plant row location, fence location, building location, field-edge location, boundary location, boulder location, rock locations (e.g., greater than a minimum threshold size or volume), soil ridge and furrows, tree location, crop edge location, a cutting edge on vegetation (e.g., turf), and a reference marker.
  • the vision-derived location data or position data of local features may be used to tune (e.g., correct for drift) the preliminary location data from the location-determining receiver 28 on a regular basis (e.g., periodically).
  • a reference marker may be associated with high precision location coordinates. Further, other local features may be related to the reference marker position. The current vehicle position may be related to the reference marker position or the fixed location of local features or the location of the vehicle.
  • the vision module 22 may express the vision-derived location data on the vehicle location in coordinates or a data format that is similar to or substantially equivalent to the coordinates or data format of the location-determining receiver 28.
  • the vision module 22 may indicate one or more of the following via a status or data message to at least the adjuster 110 or the vision quality estimator 20: (1) whether the vision module 22 is disabled, (2) whether vision-derived location data is not available during one or more evaluation intervals, (3) whether the vision-derived location data is unstable or corrupt, and (4) whether the image data is subject to an accuracy level, a performance level or a reliability level that does not meet a threshold performance/reliability level.
  • a vision module 22 is able to identify plant row location with an error as small as 1 centimeter for soybeans and 2.4 centimeter for corn. [0019] In one illustrative example, the vision module 22 outputs vision-derived location data in the following format:
  • E o/f _ ws/on is the off track error estimated by the vision module 22 and E he ad_vi s ion is the heading error estimated by the vision module 22.
  • the location quality estimator 24 may comprise one or more of the following devices: a signal strength indicator associated with the location-determining receiver 28, a bit error rate indicator associated with the location-determining receiver 28, another device for measuring signal quality, an error rate, signal strength, or performance of signals, channels, or codes transmitted for location-determination. Further, for satellite-based location-determination, the location quality estimator 24 may comprise a device for determining whether a minimum number of satellite signals (e.g., signals from four or more satellites on the L1 band for GPS) of a sufficient signal quality are received by the location-determining receiver 28 to provide reliable location data for a vehicle during an evaluation interval.
  • a minimum number of satellite signals e.g., signals from four or more satellites on the L1 band for GPS
  • the location quality estimator 24 estimates the quality of the preliminary location data or location quality data (e.g., Q gps ) outputted by the location- determining receiver 28.
  • the location quality estimator 24 may estimate the quality of the preliminary location data based on the signal strength indicator (or bit-error rate) of each signal component received by the location-determining receiver 28.
  • the location quality estimator 24 may also base the quality estimate on any of the following factors: (1) the number of satellite signals that are available in an area, (2) the number of satellites that are acquired or received by the location-determining receiver with a sufficient signal quality (e.g., signal strength profile) and (3) whether each satellite signal has an acceptable signal level or an acceptable bit-error rate (BER) or frame-error rate (FER).
  • BER bit-error rate
  • FER frame-error rate
  • different signal strength ranges are associated with different corresponding quality levels. For example, the lowest signal strength range is associated with the low quality, a medium signal strength range is associated with a fair quality, and highest signal strength range is associated with a highest quality. Conversely, the lowest bit-error rate range is associated with the highest quality, the medium bit error range is associated with the fair quality, and the highest bit error rate range is associated with the lowest quality level.
  • the vision quality estimator 20 estimates the quality of the vision-derived location data or vision quality data (e.g., Qvision) outputted by the vision module 22.
  • the vision quality estimator 20 may consider the illumination present during a series of time intervals in which the vision module 22 operates and acquires corresponding images.
  • the vision quality estimator 20 may include a photo-detector, a photo- detector with a frequency selective lens, a group of photo-detectors with corresponding frequency selective lenses, a charge-coupled device (CCD), a photometer, cadmium-sulfide cell, or the like.
  • the vision quality estimator 30 comprises a clock or timer for time-stamping image collection times and corresponding illumination measurements (e.g., luminance values for images).
  • the vision quality is low for the time interval; if the illumination is within a medium intensity range, the vision quality is high for the time interval; and if the illumination is within a high intensity range, the vision quality is fair, low or high for the time interval depending upon defined subranges within the high intensity range.
  • the foregoing intensity range versus quality may be applied on a light frequency by light frequency or light color basis, in one example. In another example, the intensity range versus quality may be applied for infra-red range frequencies and for ultraviolet range frequencies differently than for visible light.
  • the vision quality estimation may be related to a confidence measure in processing the images. If the desired features (e.g., plant rows) are apparent in one or more images, the vision quality estimator 20 may assign a high image quality or high confidence level for the corresponding images. Conversely, if the desired features are not apparent in one or more images (e.g., due to missing crop rows), the vision quality estimator 20 may assign a low image quality or a low confidence level.
  • the confidence level is determined based on a sum of the absolute-differences (SAD) of the mean intensity of each column vector (e.g., velocity vector for the vision module 22) for the hypothesized yaw/pitch pair.
  • SAD absolute-differences
  • Yaw may be defined as the orientation of the vision module 22 in an x-y plane
  • pitch may be defined as the orientation of the vision module 22 in the an x-z plane, which is generally perpendicular to the x-y plane.
  • the vision module 22 may alert the vision quality estimator 20, which may degrade the quality of the vision-derived location data by a quality degradation indicator.
  • the adjuster 110 comprises a data processor, a microcontroller, a microprocessor, a digital signal processor, an embedded processor or any other programmable (e.g., field programmable) device programmed with software instructions.
  • the adjuster 110 comprises a rule manager.
  • the rule manager of the adjuster 110 may apply the preliminary location data, or a derivative thereof, as the error control signal for a corresponding time interval, unless the vision quality data exceeds the minimum threshold level. No adjustment may be required unless the preliminary location data and the vision-derived location data differ by more than a maximum tolerance.
  • the vision weight determines the extent that the contribution of the vision-derived location data (e.g., y ws/O n) from the vision module 22 governs.
  • the location weight determines the extent that the contribution of location data from the location module 22 governs.
  • the mixer 14 determines the relative contributions of location data (e.g., y gps ) and vision-derived location data (e.g., ⁇ vi s i o n) to the error control signal (e.g., y) based on the both the vision weight and the location weight.
  • the mixer 14 may comprise a digital filter, a digital signal processor, or another data processor arranged to apply one or more of the following: (1) the vision-derived location data weight, (2) the location data weight, and (3) a mixing ratio expression of the relative contributions of the location data and the vision-derived location data for an evaluation time interval.
  • the error control signal represents a difference (or an error) between measured location data (measured by the vision module 22 and by location module) and the actual location of the vehicle. Such an error control signal is inputted to the vehicle controller 25 to derive a compensated control signal.
  • the compensated control signal corrects the management and control of the steering system 27 based on the error control signal.
  • the steering system 27 may comprise an electrical interface for communications with the vehicle controller 25. In one embodiment, the electrical interface comprises a solenoid-controlled hydraulic steering system or another electromechanical device for controlling hydraulic fluid. [0029] In another embodiment, the steering system 27 comprises a steering system unit (SSU).
  • the SSLJ may be associated with a heading versus time requirement to steer or direct the vehicle along a desired course or in conformance with a desired path plan.
  • the heading is associated with a heading error (e.g., expressed as the difference between the actual heading angle an the desired heading angle).
  • the SSU may be controlled to compensate for errors in the estimated position of the vehicle by the vision module 22 or the location-determining receiver 28.
  • an off-track error indicates or is representative of the actual position of the vehicle (e.g., in GPS coordinates) versus the desired position of the vehicle (e.g., in GPS coordinates).
  • the off-track error may be used to modify the movement of the vehicle with a compensated heading. However, if there is no off- track error at any point in time or a time interval, an uncompensated heading may suffice.
  • the heading error is a difference between actual vehicle heading and estimated vehicle heading by the vision module 22 and the location-determining receiver 28.
  • FIG. 2 is a flow chart of a method for guiding a vehicle with a vision-derived location data and location data.
  • the method of FIG. 2 begins in step S200.
  • a location-determining receiver 28 or a location-determining receiver 28 determines preliminary location data for a vehicle associated therewith.
  • the location-determining receiver 28 e.g., a GPS receiver with differential correction
  • the location-determining receiver 28 may be used to determine coordinates of the vehicle for one or more evaluation time intervals or corresponding times.
  • the location-determining receiver 28 may determine or derive a location-error signal (e.g., y gps ) from the location data.
  • a location-error signal e.g., y gps
  • the location-error signal may represent a (1) difference between the actual vehicular location and a desired vehicular location for a desired time, (2) a difference between the actual vehicular heading and a desired vehicular heading for a desired time or position, (3) or another expression of error associated with the location data.
  • the location-error signal may be defined, but need not be defined, as vector data.
  • a vision module 22 associated with the vehicle determines vision-derived location data for one or more of said evaluation time intervals or corresponding times.
  • the vision module 22 may collect images and process the collected images to determine vision-derived location data.
  • the vision-derived location data comprises vision-derived position data of a vehicle, which is obtained by reference to one or more visual reference marker or features with corresponding known locations to determine coordinates of a vehicle. The coordinates of a vehicle may be determined in accordance with a global coordinate system or a local coordinate system.
  • the location- determining receiver 28 may determine or derive a vision error signal (e.g., y VIS ⁇ o n) from the location data.
  • the vision error signal represents (1) a difference between the actual vehicular location and a desired vehicular location for a desired time, (2) a difference between the actual vehicular heading and a desired vehicular heading for a desired time or position, (3) or another expression of error associated with the vision-derived location data.
  • a vision quality estimator 20 estimates vision quality data during the evaluation time window.
  • the vision quality estimator 20 may comprise a luminance or photo-detector and a time or clock for time-stamping luminance measurements to determine a quality level based on the ambient lighting conditions.
  • the vision quality estimator 20 may also comprise a measure of confidence or reliability in processing the images to obtain desired features.
  • Step S204 may be carried out by various techniques which may be applied alternately or cumulatively. Under a first technique, the vision quality estimator 20 may estimate a confidence or reliability in the accuracy of vision-derived location data. Under a second technique, the vision quality estimator 20 first estimates the confidence level, reliability level or another quality level in the accuracy of the vision- derived location data; and , second, the vision quality estimator 20 converts the quality level into a corresponding linguistic value.
  • technical specification e.g., resolution
  • the vision quality estimator 20 may estimate a confidence or reliability in the accuracy of vision-derived location data. Under a second technique, the vision quality estimator 20 first estimates the confidence level, reliability level or another quality level in the accuracy of the vision- derived location data; and , second, the vision quality estimator 20 converts the quality level into a corresponding linguistic value.
  • a adjuster 110 adjusts the preliminary location data to a revised location data based on the vision-derived location data such that the revised location data is registered with or generally coextensive with the vision-derived location data, if the vision quality data exceeds the minimum threshold level.
  • the adjuster 110 may adjust the preliminary location data for any time slot or evaluation time window, where the vision quality data exceeds a minimum threshold level.
  • Registered with or generally coextensive with means that the vision- derived location data and the preliminary location data for the same time interval are generally coextensive or differ by a maximum tolerance (e.g., which may be expressed as a distance, a vector, or separation in seconds (or other units) between geographic coordinates).
  • the maximum tolerance may be set to be a particular distance (e.g., 2.54 centimeters) within a range from one centimeter to 10 centimeters.
  • the adjuster 110 transmits or makes available an error control signal to the vehicular controller 25 based on the preliminary location data or revised location data.
  • the revised location data, or the error control signal derived therefrom may be updated on a time-slot-by-time-slot basis (e.g., during an application time window). Each time slot may be commensurate in scope to the evaluation time interval.
  • the adjuster 206 may enhance the reliability and accuracy of the revised location data or position information that is provided for navigation or control of the vehicle by using the vision-derived location data of verified quality as a quality benchmark against the preliminary location data.
  • the preliminary location data and visional-derived quality data are collected during an evaluation time window; the adjustment of step S206 to the revised location data may be applied during an application time window that lags the evaluation time window or that is substantially coextensive with the evaluation time interval.
  • the adjuster 110 may provide predictive control data, feed-forward control data, or feedback control data to the vehicle controller 25.
  • the method of FIG. 3 is similar to the method of FIG. 2, except the method of FIG. 3 includes additional step S205 and replaces step S206 with step S208.
  • Like reference numbers indicate like procedures or steps.
  • a location quality estimator 24 estimates location quality data for the location data during an evaluation time window. Step S205 may be carried out by various techniques which may be applied alternately or cumulatively. Under a first technique, the location quality estimator 24 may estimate or measure signal quality, an error rate (e.g., bit error rate or frame error rate), a signal strength level (e.g., in dBm), or other quality levels.
  • an error rate e.g., bit error rate or frame error rate
  • a signal strength level e.g., in dBm
  • the location quality estimator 24 first estimates or measures signal quality, an error rate (e.g., bit error rate or frame error rate), a signal strength level (e.g., in dBm), or other quality levels; second, the location quality estimator 24 classifies the signal quality data into ranges, linguistic descriptions, linguistic values, or otherwise.
  • an adjuster 110 adjusts the preliminary location data to a revised location data based on the vision-derived location data such that the revised location data is registered with or generally coextensive with the vision-derived location data, if the vision quality data exceeds the minimum threshold level and if the location quality data is less than or equal to a triggering threshold level.
  • the adjuster 110 may adjust the preliminary location data for any time slot or evaluation time window, where the vision quality data exceeds a minimum threshold level and where the location quality data is less than or equal to a triggering threshold level.
  • a triggering threshold level may be where the reliability or accuracy of the preliminary location data is less than desired because of the lack of availability of satellites, or low received signal quality (e.g., low signal strength) of satellite signals or ancillary transmissions (e.g., terrestrial references) used to determine precision preliminary location data.
  • the adjuster 206 may enhance the reliability and accuracy of the revised location data or position information that is provided for navigation or control of the vehicle by using the vision-derived location data of verified quality as a quality benchmark against the preliminary location data.
  • the method of FIG. 3 makes the adjustment to the revised location data in a more selective manner than FIG. 2, by imposing the additional condition of location data quality falling below a standard (e.g., triggering threshold level).
  • FIG. 4 is a chart that illustrates static positioning error of location data, such as a differential GPS signal.
  • the vertical axis shows error in distance (e.g., meters), whereas the horizontal axis shows time (e.g. seconds).
  • FIG. 5 is a chart that illustrates dynamic positioning error of location data, such as a differential GPS signal (e.g., location data) after "tuning" at a desired update frequency or rate.
  • location data such as a differential GPS signal (e.g., location data) after "tuning" at a desired update frequency or rate.
  • the vertical axis shows error in distance (e.g., meters), whereas the horizontal axis shows time (e.g. seconds).
  • FIG. 5 shows the original error without "tuning” as solid circular points and error after “tuning” as circles.
  • the tuning achieved by using the vision-derived location data to adjust the location data at regular intervals (e.g., at 5 second intervals or .2 Hz as illustrated in FIG. 5).

Landscapes

  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Automation & Control Theory (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Electromagnetism (AREA)
  • Multimedia (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Position Fixing By Use Of Radio Waves (AREA)
  • Navigation (AREA)
  • Traffic Control Systems (AREA)

Abstract

A method and system for guiding a vehicle comprises a location module (26) (e.g., location-determining receiver) for collecting preliminary location data for the vehicle. A vision module (22) collects vision-derived location data for the vehicle during an evaluation time window. A location quality estimator (24) estimates location quality data for the corresponding collected preliminary location data during an evaluation time window. A vision module (22) estimates vision quality data for the corresponding collected vision-derived location data during the evaluation time window. A adjuster (110) adjusts the preliminary location data to a revised location data based on the vision-derived location data such that the revised location data is registered with or generally coextensive with the vision-derived location data, if the vision quality data exceeds the minimum threshold level.

Description

METHOD AND SYSTEM FOR GUIDING A VEHICLE WITH VISION-BASED
ADJUSTMENT
Field of the Invention
[0001] This invention relates to a method and system for guiding a vehicle with vision adjustment.
Background of the Invention
[0002] Global Positioning System (GPS) receivers have been used for providing position data for vehicular guidance applications. However, although certain GPS receivers with differential correction may have a general positioning error of approximately 10 centimeters (4 inches) during a majority of their operational time, an absolute positioning error of more than 50 centimeter (20 inches) is typical for five percent of their operational time. Further, GPS signals may be blocked by buildings, trees or other obstructions, which can make GPS-only navigation system unreliable in certain locations or environments. Accordingly, there is a need for supplementing or enhancing a GPS-based navigation system with one or more additional sensors to increase accuracy and robustness.
Summary of the Invention
[0003] A method and system for guiding a vehicle comprises a location module (e.g., location-determining receiver) for collecting preliminary location data for the vehicle. A vision module collects vision-derived location data for the vehicle during an evaluation time window. A vision module estimates vision quality data for the corresponding collected vision-derived location data during the evaluation time window. A adjuster adjusts the preliminary location data to a revised location data based on the vision-derived location data such that the revised location data is registered with or generally coextensive with the vision-derived location data, if the vision quality data exceeds the minimum threshold level.
Brief Description of the Drawings
[0004] FIG. 1 is a block diagram of a system for guiding a vehicle based on preliminary location data and vision-derived location data in accordance with the invention. [0005] FIG. 2 is a flow chart of a method for guiding a vehicle based on preliminary location data and vision-derived location data in accordance with the invention. [0006] FIG. 3 is a flow chart of another method for guiding a vehicle based on preliminary location data and vision-derived location data in accordance with the invention.
[0007] FIG. 4 is a chart that illustrates static positioning error of location data, such as a guidance signal derived from differential Global Positioning System (GPS). [0008] FIG. 5 is a chart that illustrates positioning error of location data, such as a guidance signal derived from differential Global Positioning System (GPS) signal after "tuning" by another sensor, such as a vision module in accordance with the invention.
Description of the Preferred Embodiment
[0009] FIG. 1 is a block diagram of a guidance system 11 for guiding a vehicle. The guidance system 11 may be mounted on or collocated with a vehicle or mobile robot. The guidance system 11 comprises a vision module 22 and a location- determining receiver 28 that communicates with an adjuster 110. [0010] The vision module 22 may be associated with a vision quality estimator 20. The location-determining receiver 28 may be associated with a location quality estimator 24. The adjuster 110 may communicate with a vehicular controller 25. In turn, the vehicular controller 25 is coupled to a steering system 27. [0011] The location-determining receiver 28 may comprise a Global Positioning System (GPS) receiver with differential correction (e.g., a GPS receiver and a receiver for receiving a differential correction signal transmitted by a satellite or terrestrial source). The location determining receiver 28 provides location data (e.g., coordinates) of a vehicle. The location-determining receiver 28 may indicate one or more of the following conditions or status (e.g., via a status signal) to at least the adjuster 110 or the location quality estimator 24: (1) where the location-determining receiver 28 is disabled, (2) where location data is not available or corrupt for one or more corresponding evaluation intervals, and (3) where the estimated accuracy or reliability of the location data falls below a minimum threshold for one or more evaluation intervals. The location-determining receiver 28 provides location data for a vehicle that is well-suited for global navigation or global path planning.
[0012] In one illustrative embodiment, the location-determining receiver 28 outputs location data in the following format:
[0013] ygps= '"Jf -M"
P , where EOff_gps is the off-track error estimated by the location- head _ gps determining receiver 28 (e.g., location-determining receiver 28), and Ehead_gPs is the heading error estimated by the location-determining receiver 28. [0014] The vision module 22 may comprise an image collection system and an image processing system. The image collection system may comprise one or more of the following: (1) one or more monocular imaging systems for collecting a group of images (e.g., multiple images of the same scene with different focus settings or lens adjustments, or multiple images for different field of views (FOV)); (2) a stereo vision system (e.g., two digital imaging units separated by a known distance and orientation) for determining depth information or three-dimensional coordinates associated with points on an object in a scene; (3) a range finder (e.g., laser range finder) for determining range measurements or three-dimensional coordinates of points on an object in a scene; (4) a ladar system or laser radar system for detecting the speed, altitude, direction or range of an object in a scene; (5) a scanning laser system (e.g., a laser measurement system that transmits a pulse of light and estimates distance between the laser measurement system and the object based on the time of propagation between transmission of the pulse and reception of its reflection) for determining a distance to an object in a scene; and (6) an imaging system for collecting images via an optical micro-electromechanical system (MEMS), free-space optical MEMS, or an integrated optical MEMS. Free-space optical MEMS use compound semiconductors and materials with a range or refractive indexes to manipulate visible light, infra-red, or ultraviolet light, whereas integrated optical MEMS use polysilicon components to reflect, diffract, modulate or manipulate visible light, infra-red, or ultraviolet light. MEMS may be structured as switching matrixes, lens, mirrors and diffraction gratings that can be fabricated in accordance with various semiconductor fabrication techniques. The images collected by the image processing system may be in color, monochrome, black-and-white, or grey-scale images, for example.
[0015] The vision module 22 or vision-derived location data may support the collection of position data (in two or three dimensional coordinates) corresponding to the location of features of an object within the image. The vision module 22 is well suited for using (a) features or local features of an environment around a vehicle, (b) position data or coordinates associated with such features, or both to facilitate navigation of the vehicle. The local features may comprise one or more of the following: plant row location, fence location, building location, field-edge location, boundary location, boulder location, rock locations (e.g., greater than a minimum threshold size or volume), soil ridge and furrows, tree location, crop edge location, a cutting edge on vegetation (e.g., turf), and a reference marker. The vision-derived location data or position data of local features may be used to tune (e.g., correct for drift) the preliminary location data from the location-determining receiver 28 on a regular basis (e.g., periodically).
[0016] In one example, a reference marker may be associated with high precision location coordinates. Further, other local features may be related to the reference marker position. The current vehicle position may be related to the reference marker position or the fixed location of local features or the location of the vehicle. In one embodiment, the vision module 22 may express the vision-derived location data on the vehicle location in coordinates or a data format that is similar to or substantially equivalent to the coordinates or data format of the location-determining receiver 28.
[0017] The vision module 22 may indicate one or more of the following via a status or data message to at least the adjuster 110 or the vision quality estimator 20: (1) whether the vision module 22 is disabled, (2) whether vision-derived location data is not available during one or more evaluation intervals, (3) whether the vision-derived location data is unstable or corrupt, and (4) whether the image data is subject to an accuracy level, a performance level or a reliability level that does not meet a threshold performance/reliability level.
[0018] In one example, a vision module 22 is able to identify plant row location with an error as small as 1 centimeter for soybeans and 2.4 centimeter for corn. [0019] In one illustrative example, the vision module 22 outputs vision-derived location data in the following format:
[0020] where Eo/f_ws/on is the off track error estimated by the
Figure imgf000007_0001
vision module 22 and Ehead_vision is the heading error estimated by the vision module 22.
[0021] The location quality estimator 24 may comprise one or more of the following devices: a signal strength indicator associated with the location-determining receiver 28, a bit error rate indicator associated with the location-determining receiver 28, another device for measuring signal quality, an error rate, signal strength, or performance of signals, channels, or codes transmitted for location-determination. Further, for satellite-based location-determination, the location quality estimator 24 may comprise a device for determining whether a minimum number of satellite signals (e.g., signals from four or more satellites on the L1 band for GPS) of a sufficient signal quality are received by the location-determining receiver 28 to provide reliable location data for a vehicle during an evaluation interval. [0022] The location quality estimator 24 estimates the quality of the preliminary location data or location quality data (e.g., Qgps) outputted by the location- determining receiver 28. The location quality estimator 24 may estimate the quality of the preliminary location data based on the signal strength indicator (or bit-error rate) of each signal component received by the location-determining receiver 28. The location quality estimator 24 may also base the quality estimate on any of the following factors: (1) the number of satellite signals that are available in an area, (2) the number of satellites that are acquired or received by the location-determining receiver with a sufficient signal quality (e.g., signal strength profile) and (3) whether each satellite signal has an acceptable signal level or an acceptable bit-error rate (BER) or frame-error rate (FER).
[0023] In one embodiment, different signal strength ranges are associated with different corresponding quality levels. For example, the lowest signal strength range is associated with the low quality, a medium signal strength range is associated with a fair quality, and highest signal strength range is associated with a highest quality. Conversely, the lowest bit-error rate range is associated with the highest quality, the medium bit error range is associated with the fair quality, and the highest bit error rate range is associated with the lowest quality level.
[0024] The vision quality estimator 20 estimates the quality of the vision-derived location data or vision quality data (e.g., Qvision) outputted by the vision module 22. The vision quality estimator 20 may consider the illumination present during a series of time intervals in which the vision module 22 operates and acquires corresponding images. The vision quality estimator 20 may include a photo-detector, a photo- detector with a frequency selective lens, a group of photo-detectors with corresponding frequency selective lenses, a charge-coupled device (CCD), a photometer, cadmium-sulfide cell, or the like. Further, the vision quality estimator 30 comprises a clock or timer for time-stamping image collection times and corresponding illumination measurements (e.g., luminance values for images). If the illumination is within a low intensity range, the vision quality is low for the time interval; if the illumination is within a medium intensity range, the vision quality is high for the time interval; and if the illumination is within a high intensity range, the vision quality is fair, low or high for the time interval depending upon defined subranges within the high intensity range. The foregoing intensity range versus quality may be applied on a light frequency by light frequency or light color basis, in one example. In another example, the intensity range versus quality may be applied for infra-red range frequencies and for ultraviolet range frequencies differently than for visible light.
[0025] The vision quality estimation may be related to a confidence measure in processing the images. If the desired features (e.g., plant rows) are apparent in one or more images, the vision quality estimator 20 may assign a high image quality or high confidence level for the corresponding images. Conversely, if the desired features are not apparent in one or more images (e.g., due to missing crop rows), the vision quality estimator 20 may assign a low image quality or a low confidence level. In one example, the confidence level is determined based on a sum of the absolute-differences (SAD) of the mean intensity of each column vector (e.g., velocity vector for the vision module 22) for the hypothesized yaw/pitch pair. Yaw may be defined as the orientation of the vision module 22 in an x-y plane and pitch may be defined as the orientation of the vision module 22 in the an x-z plane, which is generally perpendicular to the x-y plane.
[0026] If the vision module 22 is unable to locate or reference a reference feature or reference marker in an image or has not referenced a reference marker in an image for a threshold maximum time, the vision module 22 may alert the vision quality estimator 20, which may degrade the quality of the vision-derived location data by a quality degradation indicator.
[0027] In general, the adjuster 110 comprises a data processor, a microcontroller, a microprocessor, a digital signal processor, an embedded processor or any other programmable (e.g., field programmable) device programmed with software instructions. In one embodiment, the adjuster 110 comprises a rule manager. The rule manager of the adjuster 110 may apply the preliminary location data, or a derivative thereof, as the error control signal for a corresponding time interval, unless the vision quality data exceeds the minimum threshold level. No adjustment may be required unless the preliminary location data and the vision-derived location data differ by more than a maximum tolerance. The vision weight determines the extent that the contribution of the vision-derived location data (e.g., yws/On) from the vision module 22 governs. The location weight determines the extent that the contribution of location data from the location module 22 governs. The mixer 14 determines the relative contributions of location data (e.g., ygps) and vision-derived location data ( e.g., ^vision) to the error control signal (e.g., y) based on the both the vision weight and the location weight. In one embodiment, the mixer 14 may comprise a digital filter, a digital signal processor, or another data processor arranged to apply one or more of the following: (1) the vision-derived location data weight, (2) the location data weight, and (3) a mixing ratio expression of the relative contributions of the location data and the vision-derived location data for an evaluation time interval. [0028] The error control signal represents a difference (or an error) between measured location data (measured by the vision module 22 and by location module) and the actual location of the vehicle. Such an error control signal is inputted to the vehicle controller 25 to derive a compensated control signal. The compensated control signal corrects the management and control of the steering system 27 based on the error control signal. The steering system 27 may comprise an electrical interface for communications with the vehicle controller 25. In one embodiment, the electrical interface comprises a solenoid-controlled hydraulic steering system or another electromechanical device for controlling hydraulic fluid. [0029] In another embodiment, the steering system 27 comprises a steering system unit (SSU). The SSLJ may be associated with a heading versus time requirement to steer or direct the vehicle along a desired course or in conformance with a desired path plan. The heading is associated with a heading error (e.g., expressed as the difference between the actual heading angle an the desired heading angle). [0030] The SSU may be controlled to compensate for errors in the estimated position of the vehicle by the vision module 22 or the location-determining receiver 28. For example, an off-track error indicates or is representative of the actual position of the vehicle (e.g., in GPS coordinates) versus the desired position of the vehicle (e.g., in GPS coordinates). The off-track error may be used to modify the movement of the vehicle with a compensated heading. However, if there is no off- track error at any point in time or a time interval, an uncompensated heading may suffice. The heading error is a difference between actual vehicle heading and estimated vehicle heading by the vision module 22 and the location-determining receiver 28.
[0031] FIG. 2 is a flow chart of a method for guiding a vehicle with a vision-derived location data and location data. The method of FIG. 2 begins in step S200. [0032] In step S200, a location-determining receiver 28 or a location-determining receiver 28 determines preliminary location data for a vehicle associated therewith. For example, the location-determining receiver 28 (e.g., a GPS receiver with differential correction) may be used to determine coordinates of the vehicle for one or more evaluation time intervals or corresponding times. Further, in step S200, the location-determining receiver 28 may determine or derive a location-error signal (e.g., ygps) from the location data. The location-error signal may represent a (1) difference between the actual vehicular location and a desired vehicular location for a desired time, (2) a difference between the actual vehicular heading and a desired vehicular heading for a desired time or position, (3) or another expression of error associated with the location data. The location-error signal may be defined, but need not be defined, as vector data.
[0033] In step S202, a vision module 22 associated with the vehicle determines vision-derived location data for one or more of said evaluation time intervals or corresponding times. For example, the vision module 22 may collect images and process the collected images to determine vision-derived location data. In one example, the vision-derived location data comprises vision-derived position data of a vehicle, which is obtained by reference to one or more visual reference marker or features with corresponding known locations to determine coordinates of a vehicle. The coordinates of a vehicle may be determined in accordance with a global coordinate system or a local coordinate system. Further, in step S202, the location- determining receiver 28 may determine or derive a vision error signal (e.g., yVISιon) from the location data. The vision error signal represents (1) a difference between the actual vehicular location and a desired vehicular location for a desired time, (2) a difference between the actual vehicular heading and a desired vehicular heading for a desired time or position, (3) or another expression of error associated with the vision-derived location data.
[0034] In step S204, a vision quality estimator 20 estimates vision quality data during the evaluation time window. The vision quality estimator 20 may comprise a luminance or photo-detector and a time or clock for time-stamping luminance measurements to determine a quality level based on the ambient lighting conditions. The vision quality estimator 20 may also comprise a measure of confidence or reliability in processing the images to obtain desired features. The confidence or reliability in processing the images may depend upon any of the following factors, among others: technical specification (e.g., resolution) of the vision module 22, reliability of recognizing an object (e.g., landmark in an image), reliability of estimating a location of the recognized object or a point thereon, reliability of converting image coordinates or local coordinates to a global coordinates or vision- derived location data that is spatially and temporally consistent with the location data from the location-determining receiver 28. [0035] Step S204 may be carried out by various techniques which may be applied alternately or cumulatively. Under a first technique, the vision quality estimator 20 may estimate a confidence or reliability in the accuracy of vision-derived location data. Under a second technique, the vision quality estimator 20 first estimates the confidence level, reliability level or another quality level in the accuracy of the vision- derived location data; and , second, the vision quality estimator 20 converts the quality level into a corresponding linguistic value.
[0036] In step S206, a adjuster 110 adjusts the preliminary location data to a revised location data based on the vision-derived location data such that the revised location data is registered with or generally coextensive with the vision-derived location data, if the vision quality data exceeds the minimum threshold level. For example, the adjuster 110 may adjust the preliminary location data for any time slot or evaluation time window, where the vision quality data exceeds a minimum threshold level. Registered with or generally coextensive with means that the vision- derived location data and the preliminary location data for the same time interval are generally coextensive or differ by a maximum tolerance (e.g., which may be expressed as a distance, a vector, or separation in seconds (or other units) between geographic coordinates). For example, the maximum tolerance may be set to be a particular distance (e.g., 2.54 centimeters) within a range from one centimeter to 10 centimeters.
[0037] In one embodiment, the adjuster 110 transmits or makes available an error control signal to the vehicular controller 25 based on the preliminary location data or revised location data. The revised location data, or the error control signal derived therefrom, may be updated on a time-slot-by-time-slot basis (e.g., during an application time window). Each time slot may be commensurate in scope to the evaluation time interval.
[0038] The adjuster 206 may enhance the reliability and accuracy of the revised location data or position information that is provided for navigation or control of the vehicle by using the vision-derived location data of verified quality as a quality benchmark against the preliminary location data. Although the preliminary location data and visional-derived quality data are collected during an evaluation time window; the adjustment of step S206 to the revised location data may be applied during an application time window that lags the evaluation time window or that is substantially coextensive with the evaluation time interval. Regardless of how the evaluation time window and the application time window are defined in this example, in other examples the adjuster 110 may provide predictive control data, feed-forward control data, or feedback control data to the vehicle controller 25. [0039] The method of FIG. 3 is similar to the method of FIG. 2, except the method of FIG. 3 includes additional step S205 and replaces step S206 with step S208. Like reference numbers indicate like procedures or steps.
[0040] In step S205, a location quality estimator 24 estimates location quality data for the location data during an evaluation time window. Step S205 may be carried out by various techniques which may be applied alternately or cumulatively. Under a first technique, the location quality estimator 24 may estimate or measure signal quality, an error rate (e.g., bit error rate or frame error rate), a signal strength level (e.g., in dBm), or other quality levels. Under a second technique, the location quality estimator 24 first estimates or measures signal quality, an error rate (e.g., bit error rate or frame error rate), a signal strength level (e.g., in dBm), or other quality levels; second, the location quality estimator 24 classifies the signal quality data into ranges, linguistic descriptions, linguistic values, or otherwise. [0041] In step S208, an adjuster 110 adjusts the preliminary location data to a revised location data based on the vision-derived location data such that the revised location data is registered with or generally coextensive with the vision-derived location data, if the vision quality data exceeds the minimum threshold level and if the location quality data is less than or equal to a triggering threshold level. For example, the adjuster 110 may adjust the preliminary location data for any time slot or evaluation time window, where the vision quality data exceeds a minimum threshold level and where the location quality data is less than or equal to a triggering threshold level. For example, he triggering threshold level may be where the reliability or accuracy of the preliminary location data is less than desired because of the lack of availability of satellites, or low received signal quality (e.g., low signal strength) of satellite signals or ancillary transmissions (e.g., terrestrial references) used to determine precision preliminary location data. The adjuster 206 may enhance the reliability and accuracy of the revised location data or position information that is provided for navigation or control of the vehicle by using the vision-derived location data of verified quality as a quality benchmark against the preliminary location data. The method of FIG. 3 makes the adjustment to the revised location data in a more selective manner than FIG. 2, by imposing the additional condition of location data quality falling below a standard (e.g., triggering threshold level).
[0042] FIG. 4 is a chart that illustrates static positioning error of location data, such as a differential GPS signal. The vertical axis shows error in distance (e.g., meters), whereas the horizontal axis shows time (e.g. seconds).
[0043] FIG. 5 is a chart that illustrates dynamic positioning error of location data, such as a differential GPS signal (e.g., location data) after "tuning" at a desired update frequency or rate. The vertical axis shows error in distance (e.g., meters), whereas the horizontal axis shows time (e.g. seconds). FIG. 5 shows the original error without "tuning" as solid circular points and error after "tuning" as circles. The tuning achieved by using the vision-derived location data to adjust the location data at regular intervals (e.g., at 5 second intervals or .2 Hz as illustrated in FIG. 5). [0044] Having described the preferred embodiment, it will become apparent that various modifications can be made without departing from the scope of the invention as defined in the accompanying claims.

Claims

Claims The following is claimed:
1. A method for guiding a vehicle, the method comprising: collecting preliminary location data for the vehicle based on a location- determining receiver associated with the vehicle during an evaluation time window; collecting vision-derived location data for the vehicle based on a vision module associated with the vehicle during the evaluation time window; estimating vision quality data for the vision-derived location data during the evaluation time window; and adjusting the preliminary location data to a revised location data based on the vision-derived location data such that the revised location data is registered with or generally coextensive with the vision-derived location data, if the vision quality data exceeds the minimum threshold level.
2. The method according to claim 1 wherein the adjusting comprises adjusting the preliminary location data if the vision quality data exceeds the minimum threshold level and if the vision-derived location data is substantially the same as the preliminary location data within a defined tolerance.
3. The method according to claim 1 further comprising designating the vision- derived location data as in a good state if the vision quality data corresponding to the vision-derived location data meets or exceeds the minimum threshold level.
4. I he method according to claim 1 further comprising determining if the preliminary location data is consistent with a vision-derived location data for the evaluation time window if vision quality data exceeds a minimum threshold level.
5. The method according to claim 1 further comprising repeating the above process for a next evaluation time window of less than or equal to approximately .2 seconds.
6. The method according to claim 1 wherein the adjusting is accomplished by providing a revised location data at a frequency of 5 Hertz.
7. The method according to claim 1 wherein the collected vision-derived location data estimates a vehicle location with respect one or more a visual reference landmarks in a field of view, where each visual reference landmark has a known geographic coordinates.
8. The method according to claim 7 wherein the visual reference marker comprises a row of plants.
9. A system for guiding a vehicle, the system comprising: a location module for collecting preliminary location data for the vehicle based on a location-determining receiver associated with the vehicle during an evaluation time window; a vision module for collecting vision-derived location data for the vehicle based on a vision module associated with the vehicle during the evaluation time window; a vision quality estimator for estimating vision quality data for the vision- derived location data during the evaluation time window; and an adjuster for adjusting the preliminary location data to a revised location data based on the vision-derived location data such that the revised location data is registered with or generally coextensive with the vision-derived location data, if the vision quality data exceeds the minimum threshold level.
10. The system according to claim 9 wherein the adjuster adjusting the preliminary location data if the vision quality data exceeds the minimum threshold level and if the vision-derived location data is substantially the same as the preliminary location data within a defined tolerance.
11. The system according to claim 9 further wherein the vision quality estimator designates the vision-derived location data as in a good state if the vision quality data corresponding to the vision-derived location data meets or exceeds the minimum threshold level.
12. The system according to claim 9 wherein an evaluator determines if the preliminary location data is consistent with a vision-derived location data for the evaluation time window if vision quality data exceeds a minimum threshold level.
13. The system according to claim 9 further comprising repeating the above process for a next evaluation time window of less than or equal to approximately .2 seconds.
14. The system according to claim 9 wherein the adjuster adjusts the revised location data at a frequency of 5 Hertz.
15. The system according to claim 9 wherein a vision-derived location data processing module estimates a vehicle location with respect one or more a visual reference landmarks in a field of view, where each visual reference landmark has a known geographic coordinates.
16. The system according to claim 15 wherein the visual reference marker comprises a row of plants.
PCT/US2005/045616 2005-01-04 2005-12-15 Method and system for guiding a vehicle with vision-based adjustment WO2006073739A2 (en)

Priority Applications (4)

Application Number Priority Date Filing Date Title
BRPI0519300-1A BRPI0519300B1 (en) 2005-01-04 2005-12-15 METHOD AND SYSTEM FOR DRIVING A VEHICLE
AU2005323178A AU2005323178A1 (en) 2005-01-04 2005-12-15 Method and system for guiding a vehicle with vision-based adjustment
CA2592996A CA2592996C (en) 2005-01-04 2005-12-15 Method and system for guiding a vehicle with vision-based adjustment
EP05854355.4A EP1836648B1 (en) 2005-01-04 2005-12-15 Method and system for guiding a vehicle with vision-based adjustment

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
US64124005P 2005-01-04 2005-01-04
US60/641,240 2005-01-04
US11/107,114 US7233683B2 (en) 2005-01-04 2005-04-15 Method and system for guiding a vehicle with vision-based adjustment
US11/107,114 2005-04-15

Publications (2)

Publication Number Publication Date
WO2006073739A2 true WO2006073739A2 (en) 2006-07-13
WO2006073739A3 WO2006073739A3 (en) 2006-12-28

Family

ID=36640491

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2005/045616 WO2006073739A2 (en) 2005-01-04 2005-12-15 Method and system for guiding a vehicle with vision-based adjustment

Country Status (6)

Country Link
US (1) US7233683B2 (en)
EP (1) EP1836648B1 (en)
AU (1) AU2005323178A1 (en)
BR (1) BRPI0519300B1 (en)
CA (1) CA2592996C (en)
WO (1) WO2006073739A2 (en)

Families Citing this family (37)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
GB2404819A (en) * 2003-08-05 2005-02-09 Research In Motion Ltd Mobile communications device with integral optical navigation
US8150574B2 (en) * 2005-01-04 2012-04-03 Deere & Company Method and system for guiding a vehicle with vision-based adjustment
US7876927B2 (en) * 2005-01-04 2011-01-25 Deere & Company Method and system for guiding a vehicle with vision-based adjustment
US7570783B2 (en) * 2005-07-01 2009-08-04 Deere & Company Method and system for vehicular guidance using a crop image
US7580549B2 (en) * 2005-07-01 2009-08-25 Deere & Company Method and system for vehicular guidance using a crop image
US7684916B2 (en) * 2005-07-01 2010-03-23 Deere & Company Method and system for vehicular guidance using a crop image
US7792622B2 (en) * 2005-07-01 2010-09-07 Deere & Company Method and system for vehicular guidance using a crop image
WO2008154737A1 (en) * 2007-06-18 2008-12-24 Leddartech Inc. Lighting system with traffic management capabilities
US10378896B2 (en) * 2006-02-27 2019-08-13 Trimble Inc. Method and system for planning the path of an agricultural vehicle
EP2149131B1 (en) * 2007-05-25 2013-04-03 Continental Teves AG & Co. oHG Method and device for identifying traffic-relevant information
JP2010529932A (en) * 2007-06-18 2010-09-02 レッダーテック インコーポレイテッド Lighting system with driver assistance function
JP5671345B2 (en) 2007-12-21 2015-02-18 レッダーテック インコーポレイテッド Detection and ranging method
EP2232462B1 (en) * 2007-12-21 2015-12-16 Leddartech Inc. Parking management system and method using lighting system
USRE46930E1 (en) 2007-12-21 2018-07-03 Leddartech Inc. Distance detection method and system
US8229595B2 (en) * 2008-06-19 2012-07-24 Seelinger Michael J Method and system for providing autonomous control of a platform
US8099205B2 (en) * 2008-07-08 2012-01-17 Caterpillar Inc. Machine guidance system
JP5272605B2 (en) * 2008-09-18 2013-08-28 日産自動車株式会社 Driving operation support device and driving operation support method
WO2011077400A2 (en) 2009-12-22 2011-06-30 Leddartech Inc. Active 3d monitoring system for traffic detection
US8908159B2 (en) 2011-05-11 2014-12-09 Leddartech Inc. Multiple-field-of-view scannerless optical rangefinder in high ambient background light
US8589014B2 (en) * 2011-06-01 2013-11-19 Google Inc. Sensor field selection
US9378640B2 (en) 2011-06-17 2016-06-28 Leddartech Inc. System and method for traffic side detection and characterization
US20130147661A1 (en) * 2011-12-07 2013-06-13 International Business Machines Corporation System and method for optical landmark identification for gps error correction
US9381916B1 (en) 2012-02-06 2016-07-05 Google Inc. System and method for predicting behaviors of detected objects through environment representation
CA2865733C (en) 2012-03-02 2023-09-26 Leddartech Inc. System and method for multipurpose traffic detection and characterization
US9068839B2 (en) * 2012-06-29 2015-06-30 Nokia Technologies Oy Method and apparatus for providing shadow-based location positioning
US9091628B2 (en) 2012-12-21 2015-07-28 L-3 Communications Security And Detection Systems, Inc. 3D mapping with two orthogonal imaging views
DE102014111231A1 (en) 2014-08-07 2016-02-11 Amazonen-Werke H. Dreyer Gmbh & Co. Kg Method for correcting position data stored in a memory of a work computer
WO2016038536A1 (en) 2014-09-09 2016-03-17 Leddartech Inc. Discretization of detection zone
DK3123260T3 (en) * 2014-12-31 2021-06-14 Sz Dji Technology Co Ltd SELECTIVE PROCESSING OF SENSOR DATA
US9878711B2 (en) 2015-12-14 2018-01-30 Honda Motor Co., Ltd. Method and system for lane detection and validation
DE102016210495A1 (en) * 2016-06-14 2017-12-14 Robert Bosch Gmbh Method and apparatus for creating an optimized location map and method for creating a location map for a vehicle
US10757485B2 (en) 2017-08-25 2020-08-25 Honda Motor Co., Ltd. System and method for synchronized vehicle sensor data acquisition processing using vehicular communication
US11181929B2 (en) 2018-07-31 2021-11-23 Honda Motor Co., Ltd. System and method for shared autonomy through cooperative sensing
US11163317B2 (en) 2018-07-31 2021-11-02 Honda Motor Co., Ltd. System and method for shared autonomy through cooperative sensing
CA3210182A1 (en) 2020-07-21 2021-10-06 Leddartech Inc. Beam-steering devices and methods for lidar applications
WO2022016276A1 (en) 2020-07-21 2022-01-27 Leddartech Inc. Beam-steering device particularly for lidar systems
US11402510B2 (en) 2020-07-21 2022-08-02 Leddartech Inc. Systems and methods for wide-angle LiDAR using non-uniform magnification optics

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6445983B1 (en) 2000-07-07 2002-09-03 Case Corporation Sensor-fusion navigator for automated guidance of off-road vehicles

Family Cites Families (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH0579846A (en) * 1991-09-19 1993-03-30 Matsushita Electric Ind Co Ltd Vehicle position calculator
WO1995018432A1 (en) 1993-12-30 1995-07-06 Concord, Inc. Field navigation system
US5974348A (en) * 1996-12-13 1999-10-26 Rocks; James K. System and method for performing mobile robotic work operations
US6385515B1 (en) 2000-06-15 2002-05-07 Case Corporation Trajectory path planner for a vision guidance system
US6819780B2 (en) 2001-02-02 2004-11-16 Cnh America Llc Method and apparatus for automatically steering a vehicle in an agricultural field using a plurality of fuzzy logic membership functions
US6898585B2 (en) 2001-02-02 2005-05-24 University Of Illinois Fuzzy logic method for adaptively evaluating the validity of sensor data
DE10129135B4 (en) 2001-06-16 2013-10-24 Deere & Company Device for determining the position of an agricultural work vehicle and an agricultural work vehicle with this
DE10129133A1 (en) 2001-06-16 2002-12-19 Deere & Co Device for the automatic steering of an agricultural work vehicle
US6946978B2 (en) * 2002-04-25 2005-09-20 Donnelly Corporation Imaging system for vehicle

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6445983B1 (en) 2000-07-07 2002-09-03 Case Corporation Sensor-fusion navigator for automated guidance of off-road vehicles

Also Published As

Publication number Publication date
CA2592996A1 (en) 2006-07-13
EP1836648A2 (en) 2007-09-26
BRPI0519300A2 (en) 2009-01-06
US7233683B2 (en) 2007-06-19
WO2006073739A3 (en) 2006-12-28
CA2592996C (en) 2013-12-10
EP1836648B1 (en) 2016-04-20
AU2005323178A1 (en) 2006-07-13
EP1836648A4 (en) 2012-09-05
US20060147089A1 (en) 2006-07-06
BRPI0519300B1 (en) 2018-01-16

Similar Documents

Publication Publication Date Title
CA2592996C (en) Method and system for guiding a vehicle with vision-based adjustment
US7242791B2 (en) Method and system for guiding a vehicle with vision enhancement
US8150574B2 (en) Method and system for guiding a vehicle with vision-based adjustment
CA2592977C (en) Vision-aided system and method for guiding a vehicle
CA2592715C (en) Vision-aided system and method for guiding a vehicle
CN101681168B (en) Method and system for guiding a vehicle with vision-based adjustment
CN100580689C (en) Vision-based system and method for adjusting and guiding vehicle
CN116719037A (en) Environment sensing method and system for intelligent mowing robot
KR102622584B1 (en) Apparatus for correcting position of vehicle and method thereof
US20220222851A1 (en) Moving body, position estimation method, and program
JP2023002082A (en) Map update device, map update method, and computer program for map update
US10964047B2 (en) Device for locating a target by stellar correction, intended to be on board a mobile carrier

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application
WWE Wipo information: entry into national phase

Ref document number: 808/MUMNP/2007

Country of ref document: IN

WWE Wipo information: entry into national phase

Ref document number: 2005854355

Country of ref document: EP

WWE Wipo information: entry into national phase

Ref document number: 2592996

Country of ref document: CA

Ref document number: 200580045916.8

Country of ref document: CN

NENP Non-entry into the national phase

Ref country code: DE

WWE Wipo information: entry into national phase

Ref document number: 2005323178

Country of ref document: AU

ENP Entry into the national phase

Ref document number: 2005323178

Country of ref document: AU

Date of ref document: 20051215

Kind code of ref document: A

WWP Wipo information: published in national office

Ref document number: 2005323178

Country of ref document: AU

WWP Wipo information: published in national office

Ref document number: 2005854355

Country of ref document: EP

ENP Entry into the national phase

Ref document number: PI0519300

Country of ref document: BR