CN112520643A - Controller gear detection method and system for practical operation examination and coaching of forklift driver - Google Patents

Controller gear detection method and system for practical operation examination and coaching of forklift driver Download PDF

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CN112520643A
CN112520643A CN202011368426.4A CN202011368426A CN112520643A CN 112520643 A CN112520643 A CN 112520643A CN 202011368426 A CN202011368426 A CN 202011368426A CN 112520643 A CN112520643 A CN 112520643A
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gear
forklift
camera
image
coordinate
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CN112520643B (en
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刘桂雄
周介祺
李伟
黄坚
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South China University of Technology SCUT
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66F—HOISTING, LIFTING, HAULING OR PUSHING, NOT OTHERWISE PROVIDED FOR, e.g. DEVICES WHICH APPLY A LIFTING OR PUSHING FORCE DIRECTLY TO THE SURFACE OF A LOAD
    • B66F9/00—Devices for lifting or lowering bulky or heavy goods for loading or unloading purposes
    • B66F9/06—Devices for lifting or lowering bulky or heavy goods for loading or unloading purposes movable, with their loads, on wheels or the like, e.g. fork-lift trucks
    • B66F9/075—Constructional features or details
    • B66F9/0759—Details of operating station, e.g. seats, levers, operator platforms, cabin suspension
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16H—GEARING
    • F16H63/00—Control outputs from the control unit to change-speed- or reversing-gearings for conveying rotary motion or to other devices than the final output mechanism
    • F16H63/40—Control outputs from the control unit to change-speed- or reversing-gearings for conveying rotary motion or to other devices than the final output mechanism comprising signals other than signals for actuating the final output mechanisms
    • F16H63/42—Ratio indicator devices
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/70—Determining position or orientation of objects or cameras
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/10—Image acquisition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/10—Image acquisition
    • G06V10/12—Details of acquisition arrangements; Constructional details thereof
    • G06V10/14—Optical characteristics of the device performing the acquisition or on the illumination arrangements
    • G06V10/147—Details of sensors, e.g. sensor lenses
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B9/00—Simulators for teaching or training purposes
    • G09B9/02—Simulators for teaching or training purposes for teaching control of vehicles or other craft
    • G09B9/04—Simulators for teaching or training purposes for teaching control of vehicles or other craft for teaching control of land vehicles

Abstract

The invention discloses a controller gear detection method for forklift driver practical operation examination and coaching, which comprises the following steps: adjusting a camera to an alignment position and fixing, adjusting each gear handle of the forklift to different gears, capturing corresponding gear images, and acquiring and storing a bounding box R of the gear handles by using a Mask R-CNN target identification and image segmentation frameworkbdCoordinate information
Figure DDA0002805735970000011
Calculating and storing the centroid coordinates thereof
Figure DDA0002805735970000012
The camera acquires an image in the driving process of the forklift, and the coordinate information of the gear handle at the moment is acquired and stored by utilizing a Mask R-CNN target identification and image segmentation framework
Figure DDA0002805735970000013
The centroid coordinates of the data are calculated and stored
Figure DDA0002805735970000014
And respectively calculating the distances between the gear coordinate at the current moment and the calibration gear coordinate, and comparing the distances to ensure that the gear with the minimum distance is the gear at the moment.

Description

Controller gear detection method and system for practical operation examination and coaching of forklift driver
Technical Field
The invention relates to the field of practical operation examination and coaching of forklift drivers, in particular to a method and a system for detecting controller gears for the practical operation examination and coaching of the forklift drivers.
Background
The forklift refers to a special motor industrial vehicle used in a specific area of a factory, and the like, and comprises a balance weight type forklift, a forward moving type forklift, a side type forklift, a leg inserting type forklift, a pallet stacker, a three-way stacker and the like. The system is widely applied to various carrying scenes and is a main force for carrying logistics. The forklift accidents not only cause serious property loss to the equipment, the surrounding environment and the equipment, but also often cause casualty accidents. Along with the continuous rising of goods freight volume, the holding capacity of fork truck also constantly increases, how to reduce the fork truck accident from the source, becomes the problem that awaits a urgent need to solve. In order to reduce the occurrence of forklift accidents, the driving capability of a forklift driver needs to be improved, and the actual operation examination and coaching process of the forklift needs to be standardized. The driver realizes the operation of the forklift and the fork frame by controlling the forklift gear, and the forklift gear can well reflect the state of the forklift.
The controller gear detection oriented to forklift driver practical operation examination and coaching mainly comprises a camera system and a gear identification method based on deep learning. The camera system, as in patent CN111594729A, uses mechanical mechanisms such as a fixing clamp, a nut, a threaded cylinder, etc. to implement the installation and fixation and pose adjustment of the camera. The gear identification method is disclosed in patents CN101813495A and CN107725768A, etc., and the current gear information of the vehicle gear shift lever is detected by adopting a circuit design and a sensor detection method.
The specific patent reference documents are as follows:
1) "micromotion gear recognizer for field test", patent No. CN 101813495A. The invention provides a jogging gear recognizer for a field test, which comprises the following parts: printed circuit board, installation fixed bolster and activity guide block. The printed circuit board is provided with a microswitch and an outgoing cable interface; one ends of the microswitches are connected together, and the other ends of the microswitches are respectively connected to the gear decoder through an automobile connector and an automobile cable by leading out a cable interface; the mounting and fixing bracket is a circular, square or octagonal plate with 4 limiting sliding grooves formed in four opposite corners; the movable guide block is a square or octagonal plate, and a central round hole slightly larger than the outer diameter of the clapper rod is formed in the middle of the plate; the printed circuit board is fixed under the mounting and fixing bracket; the installation fixing support is sleeved with the gear beating rod and is fixedly connected with the gearbox or the cab through a strip-shaped fixing foot plate, and the movable guide block is positioned on the fixing support and is fixedly connected with the gear beating rod through 3 or 4L-shaped angle codes. The identification method is different from the identification method, the gear images in the cab are collected through the camera, the position of the current gear handle is identified by adopting a deep learning technology, and gear judgment is carried out through calculating and calibrating the gear distance.
2) "a gear position identifying device for a vehicle and a vehicle", patent No. CN 107725768A. The invention provides a gear recognition device for a vehicle and the vehicle, wherein the vehicle comprises a gearbox with a shifting fork, the gear recognition device comprises a sensor, a control unit and a control unit, the sensor is arranged in the gearbox of the vehicle and is provided with a trigger switch, the sensor is configured to determine the gear position of the shifting fork according to the state of the trigger switch, and outputs a voltage signal matched with the gear position of the shifting fork; the controller is in communication connection with the sensor and is configured to receive the voltage signal output by the sensor and output an indication signal for representing the actual position of the parking mechanism gear of the vehicle according to the voltage signal; the gear positions include a parking gear and a non-parking gear. The gear identification method is different from the gear identification method, realizes extraction of gear position information by using machine vision and deep learning, realizes gear judgment by comparing coordinates of a calibration gear, has low implementation requirement and wide application range, and can still accurately identify the gear and judge the gear state under the condition that the position and the angle are changed to a certain extent.
3) An adjustable camera support is disclosed in patent No. CN 111594729A. According to the camera supporting column, a hollow upright column is arranged at the top of the camera supporting column, transmission is carried out in the hollow upright column through a threaded rod, a lifting disc is sleeved outside the threaded rod and is fixedly connected with a lifting supporting plate, and the camera can be lifted by adjusting a threaded cylinder; the threaded cylinder is rotatably connected with the lifting supporting plate through the rotating shaft, so that the camera mounting base can rotate and can be locked through the locking knob, and the camera posture before the shooting process is adjusted and the camera in the shooting process is fixed. The invention is different from the invention, adopts deep learning to overcome the identification problems of gear position information extraction, gear judgment and the like, has low implementation requirement and wide application range, and can accurately identify the gear and judge the gear state under the condition of certain changes of position and angle.
Disclosure of Invention
In order to solve the technical problems, the invention aims to provide a controller gear detection method and system for actual operation examination and coaching of a forklift driver.
The purpose of the invention is realized by the following technical scheme:
the controller gear detection method for forklift driver practical operation examination and coaching comprises the following steps:
a, adjusting a camera to an alignment position and fixing, adjusting each gear handle of the forklift to different gears, capturing corresponding gear images, and acquiring and storing a bounding box R of the gear handles by utilizing a Mask R-CNN target identification and image segmentation frameworkbdCoordinate information
Figure BDA0002805735950000031
Calculating and storing the centroid coordinates thereof
Figure BDA0002805735950000032
As a calibration gear coordinate;
b, acquiring an image in the driving process of the forklift, and acquiring and storing coordinate information of the gear handle at the moment by using a Mask R-CNN target identification and image segmentation framework
Figure BDA0002805735950000033
Calculating the centroid coordinates thereof
Figure BDA0002805735950000034
And storing;
and C, respectively calculating the distance between the handle coordinates and the calibration gear coordinates in the real-time forklift driving image, and comparing the distances to obtain the minimum calibration gear.
Controller gear detection system towards fork truck driver's real operation examination and coach includes: the camera fixing support, the camera and the upper computer are arranged on the camera fixing support; the following steps:
the camera fixing support is used for mounting and fixing a camera on the forklift and can be finely adjusted;
the camera is used for capturing images of positions of all the gear bundles in real time and uploading the images to the upper computer;
and the upper computer is used for identifying each gear in the uploaded image, distinguishing the gears and judging the gears.
One or more embodiments of the present invention may have the following advantages over the prior art:
before the forklift runs, a camera of the fixed machine position acquires a position image of a gear lever in the forklift and transmits the position image to an upper computer, coordinate information of different gears of each gear is identified and stored through Mask R-CNN, centroid coordinates of different gears are calculated to serve as calibration gear coordinates, and a basis is provided for gear judgment. In the running process of the forklift, the camera collects image information in a cab in real time, a gear handle in a current image is identified through Mask R-CNN, position coordinate information of the gear handle is stored, and a centroid coordinate of the gear handle is calculated. And respectively calculating the distances between the current gear coordinate and the calibration gear coordinate, and comparing the distances to enable the gear with the minimum distance to be used as the current gear, so that gear identification in the running process of the forklift is realized.
Drawings
FIG. 1 is a flow chart of a controller gear detection method for forklift driver performance assessment and coaching.
FIG. 2 is a schematic diagram of a controller gear detection method for forklift driver performance assessment and coaching;
FIGS. 3a and 3b are front and left side views of the controller gear detection system for forklift driver performance and coaching;
FIG. 4 is a three-dimensional structure diagram of a controller gear detection system for forklift driver performance assessment and coaching.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the following embodiments and accompanying drawings.
As shown in fig. 1 and fig. 2, a flow chart and a schematic diagram of a detection method of controller gear positions facing a forklift driver practice test and a trainer are respectively shown, and the detection method comprises the following steps:
step 10 the system requires equipment installation prior to initial use. One end of the camera fixing support is required to be fixed on the top of the forklift, and the other end of the camera fixing support is connected with the camera. Adjusting the position of the camera, adjusting each gear of the forklift to different gears, and capturing corresponding gear images. Bounding box 12R for acquiring and storing file handle by using Mask R-CNN target recognition and image segmentation frameworkbdCoordinate information
Figure BDA0002805735950000041
Calculating and storing centroid 11 coordinates
Figure BDA0002805735950000042
As the basis for judging the subsequent gears;
20, when the system is used subsequently, the camera acquires an image of the forklift in the driving process, and the Mask R-CNN target recognition and image segmentation framework is used for acquiring and storing the coordinate information of the gear handle at the moment
Figure BDA0002805735950000051
Calculating and storing the centroid coordinates thereof
Figure BDA0002805735950000052
And 30, respectively calculating the distance between the gear coordinate at the current moment and the original gear coordinate, and comparing the distances to obtain the gear at the current moment.
Example 1: parking brake lever shift position determination
The step 10 includes: a camera is arranged right above a steering wheel, an image pixel coordinate system is established, a coordinate origin O is the top left vertex of an image, the positive direction of a u axis is horizontal to the right, and the positive direction of a v axis is vertical to the down.
Collecting images I of different gears of the parking brake gear, namely 5 images, identifying the parking brake gear by using Mask R-CNN, acquiring and storing a boundary frame R of the parking brake gearbdCoordinate information of
Figure BDA0002805735950000053
Establishing a gear shift handle boundary frame R with the gear shift number mbd-nSet Hm：
Figure BDA0002805735950000054
In the formula
Figure BDA0002805735950000055
The position of the centroid 11 of the m gear position of the parking brake gear is obtained through calibration
Figure BDA0002805735950000056
Comprises the following steps:
Figure BDA0002805735950000057
in the formula (I), the compound is shown in the specification,
Figure BDA0002805735950000058
is composed of
Figure BDA0002805735950000059
The mean values of (a) are:
Figure BDA00028057359500000510
then the parking brake gear sets the coordinate set H of the calibration gear positionpos-nComprises the following steps:
Figure BDA00028057359500000511
the step 20 specifically includes: the camera of the fixed machine position collects videos in a cockpit in the advancing process of the forklift and inputs the videos into the upper computer, the upper computer extracts pictures according to a certain time interval, and the Mask R-CNN is used for identifying a boundary frame of each gear in the current picture
Figure BDA00028057359500000512
And stores bounding box coordinates
Figure BDA00028057359500000513
The centroid coordinate of the parking brake lever at the current moment is obtained through calculation
Figure BDA0002805735950000061
Comprises the following steps:
Figure BDA0002805735950000062
the step 30 specifically includes: in the current image, recognizing and obtaining the centroid coordinates of the current time of n files
Figure BDA0002805735950000063
Set of calibration gear coordinates in combination with parking brake gear
Figure BDA0002805735950000064
Calculating to minimize Euclidean distance
Figure BDA0002805735950000065
As the parking brake gear, the gear at the current time is:
Figure BDA0002805735950000066
the current parking brake position will be in gear position number 2, i.e. in the brake released state.
Example 2: forklift gear judgment for fast and slow control gear lever
The step 10 includes: a camera is arranged right above a steering wheel, an image pixel coordinate system is established, a coordinate origin O is the top left vertex of an image, the positive direction of a u axis is horizontal to the right, and the positive direction of a v axis is vertical to the down.
Collecting 5 images I of different gears of the forklift speed control gear handle, identifying the forklift speed control gear handle by using Mask R-CNN, acquiring and storing a boundary frame R of the forklift speed control gear handlebdCoordinate information of
Figure BDA0002805735950000067
Establishing a gear shift handle boundary frame R with the gear shift number mbd-nSet Hm：
Figure BDA0002805735950000068
In the formula
Figure BDA0002805735950000069
Then the position of the centroid of the gear of the fork truck speed control gear lever m is obtained through calibration
Figure BDA00028057359500000610
Comprises the following steps:
Figure BDA00028057359500000611
in the formula (I), the compound is shown in the specification,
Figure BDA00028057359500000612
is composed of
Figure BDA00028057359500000613
The mean values of (a) are:
Figure BDA00028057359500000614
then the fork truck controls the set H of coordinates of the calibration gear of the gear leverpos-nComprises the following steps:
Figure BDA0002805735950000071
the step 20 specifically includes: the camera collects the gear handle images in the driving process and inputs the images into the upper computer in real time, the upper computer extracts pictures according to a certain time interval, and a Mask R-CNN is used for identifying a boundary frame of each gear handle in the current picture
Figure BDA0002805735950000072
And stores bounding box coordinates
Figure BDA0002805735950000073
The centroid coordinate of the current moment of the forklift speed control gear handle is obtained through calculation
Figure BDA0002805735950000074
Comprises the following steps:
Figure BDA0002805735950000075
Figure BDA0002805735950000076
the step 30 specifically includes: in the current imageIn the method, the centroid coordinate of the current moment of the forklift speed control gear handle is obtained by identification
Figure BDA0002805735950000077
Set of calibration gear coordinates in combination with parking brake gear
Figure BDA0002805735950000078
Calculating to minimize Euclidean distance
Figure BDA0002805735950000079
As the parking brake gear, the gear at the current time is:
Figure BDA00028057359500000710
therefore, the speed control gear of the current forklift is located at the No. 2 gear, namely, the fast gear.
As shown in fig. 3a, 3b and 4, the embodiment further provides a controller gear detection system for practical operation examination and coaching of a forklift driver, which comprises a camera fixing support, a camera and an upper computer; the following steps: the camera fixing support is used for mounting and fixing a camera on the forklift and can be finely adjusted; the camera is used for capturing images of positions of all the gear bundles in real time and uploading the images to the upper computer; and the upper computer is used for identifying each gear in the uploaded image, distinguishing the gears and judging the gears.
The camera is arranged on a fixed bracket at the top of the cab, and the horizontal position of the camera is just above the steering wheel and is 25-35 cm away from a front cross beam frame of the roof of the forklift; the main optical axis of the camera forms an included angle of 85-95 degrees with the plane of the steering wheel and is parallel to the side view.
Although the embodiments of the present invention have been described above, the above descriptions are only for the convenience of understanding the present invention, and are not intended to limit the present invention. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.

Claims (6)

1. A controller gear detection method for forklift driver practical operation examination and coaching is characterized by comprising the following steps:
a, adjusting a camera to an alignment position and fixing, adjusting each gear handle of the forklift to different gears, capturing corresponding gear images, and acquiring and storing a bounding box R of the gear handles by utilizing a Mask R-CNN target identification and image segmentation frameworkbdCoordinate information
Figure FDA0002805735940000011
Calculating and storing the centroid coordinates thereof
Figure FDA0002805735940000012
As a calibration gear coordinate;
b, acquiring an image in the driving process of the forklift, and acquiring and storing coordinate information of the gear handle at the moment by using a Mask R-CNN target identification and image segmentation framework
Figure FDA0002805735940000013
Calculating the centroid coordinates thereof
Figure FDA0002805735940000014
And storing;
and C, respectively calculating the distance between the handle coordinates and the calibration gear coordinates in the real-time forklift driving image, and comparing the distances to obtain the minimum calibration gear.
2. The method for detecting the shift of the controller of the forklift driver practical experience assessment and training device as claimed in claim 1, wherein in the step A, a camera is installed right above the steering wheel, an image pixel coordinate system is established, the coordinate origin O is the top left vertex of the image, the positive direction of the u axis is horizontal to the right, and the positive direction of the v axis is vertical to the down;
collecting different gears of each gear handleEach image of (1) and identifying each file by using Mask R-CNN, acquiring and storing a bounding box R of each filebdCoordinate information of
Figure FDA0002805735940000015
Establishing a shift handle boundary frame R with the shift handle number of n and the shift handle number of mbd-nCollection
Figure FDA0002805735940000016
Figure FDA0002805735940000017
In the formula
Figure FDA0002805735940000018
Then the centroid position of the m gears of the n gears is obtained by calibration
Figure FDA0002805735940000019
Comprises the following steps:
Figure FDA00028057359400000110
in the formula (I), the compound is shown in the specification,
Figure FDA00028057359400000111
is composed of
Figure FDA00028057359400000112
The mean values of (a) are:
Figure FDA0002805735940000021
then n shift lever calibration gear coordinates
Figure FDA0002805735940000022
n shift handle calibration shift coordinate set Hpos-nRespectively as follows:
Figure FDA0002805735940000023
3. the method for detecting the shift of the controller oriented to the practical experience and training of the forklift driver as claimed in claim 1, wherein in the step B, the camera collects the images of the shift handles in the driving process and inputs the images into the upper computer in real time, the upper computer extracts the pictures according to a certain time interval, and the Mask R-CNN is used for identifying the boundary frame of each shift handle in the current picture
Figure FDA0002805735940000024
And stores bounding box coordinates
Figure FDA0002805735940000025
The centroid coordinate of the current moment of the n-gear shift is obtained through calculation
Figure FDA0002805735940000026
Comprises the following steps:
Figure FDA0002805735940000027
4. the method for detecting the controller gear position for the operator practice and training of the forklift as recited in claim 1, wherein in the step C,
in the current image, recognizing and obtaining the centroid coordinates of the current time of n files
Figure FDA0002805735940000028
Calibration gear coordinate set combined with n gear handle
Figure FDA0002805735940000029
Calculating to minimize Euclidean distance
Figure FDA00028057359400000210
As the n-gear, the gear at the current time:
Figure FDA00028057359400000211
in the formula:
Figure FDA00028057359400000212
5. the controller gear detection system for practical operation examination and coaching of a forklift driver is characterized by comprising a camera fixing support, a camera and an upper computer; the following steps:
the camera fixing support is used for mounting and fixing a camera on the forklift and can be finely adjusted;
the camera is used for capturing images of positions of all the gear bundles in real time and uploading the images to the upper computer;
and the upper computer is used for identifying each gear in the uploaded image, distinguishing the gears and judging the gears.
6. The controller gear detection system for the practical operation examination and coaching of the driver of the forklift as recited in claim 5, wherein the camera is mounted on a fixed bracket at the top of the cab, and the horizontal position of the camera is right above a steering wheel and is 25-35 cm away from a front cross beam frame of the top of the forklift; the main optical axis of the camera forms an included angle of 85-95 degrees with the plane of the steering wheel and is parallel to the side view.
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