CN116310287A - Container truck loading and unloading operation positioning and guiding system and method based on vision - Google Patents
Container truck loading and unloading operation positioning and guiding system and method based on vision Download PDFInfo
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- CN116310287A CN116310287A CN202310192129.6A CN202310192129A CN116310287A CN 116310287 A CN116310287 A CN 116310287A CN 202310192129 A CN202310192129 A CN 202310192129A CN 116310287 A CN116310287 A CN 116310287A
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- 238000013135 deep learning Methods 0.000 claims abstract description 6
- 239000013307 optical fiber Substances 0.000 claims description 6
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
- B66C13/00—Other constructional features or details
- B66C13/18—Control systems or devices
- B66C13/22—Control systems or devices for electric drives
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
- B66C13/00—Other constructional features or details
- B66C13/18—Control systems or devices
- B66C13/48—Automatic control of crane drives for producing a single or repeated working cycle; Programme control
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/24—Aligning, centring, orientation detection or correction of the image
- G06V10/245—Aligning, centring, orientation detection or correction of the image by locating a pattern; Special marks for positioning
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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Abstract
The invention discloses a visual-based container truck loading and unloading operation positioning and guiding system which comprises a digital camera, a rear end control device, a signal trigger and an indication guiding device, wherein the digital camera is arranged on a cross beam above a field bridge crane, the rear end control device is connected with the signal trigger, the digital camera is connected with the rear end control device, and the rear end control device is connected with the indication guiding device. The technical scheme is adopted to manufacture a visual container truck loading and unloading operation positioning and guiding system, a overlook camera arranged above a loading and unloading operation container truck is adopted to collect operation scene images, an image inclination correction algorithm and a deep learning feature detection technology are combined, on the basis of guaranteeing a visual field, the camera is flexible in mounting position, the system is little influenced by external environment factors, data are visual, management is convenient, pixel level detection and positioning are accurate, operation mode identification can be combined, self-adaptive decision positioning is conducted, the loading and unloading operation container truck is guided to accurately stop, and accurate box grabbing and placing of a lifting appliance is realized.
Description
Technical Field
The invention relates to the field of machine vision automation using intelligent image processing algorithms, in particular to a positioning and guiding system and method for container truck loading and unloading operation based on vision.
Background
The collecting card positioning and guiding system is mainly used for identifying whether the left-right deviation of a collecting truck (in the direction of a trolley) and the front-back deviation of the collecting truck (in the direction of a cart) meet the requirements or not when equipment such as a field bridge crane, a shore bridge crane and the like is used for loading and unloading, so that a collecting card driver or an unmanned collecting card control system is guided to adjust the position, and the purpose of accurately and rapidly placing the container on the inner collecting truck and the outer collecting truck or accurately and rapidly grabbing the container on the collecting card is realized. The collecting card guiding system detects and positions the operation collecting card by using the scanning device, and displays the information such as the advancing or retreating direction, the distance and the like of the collecting truck through the collecting card position to guide a collecting card driver to stop to the operation position. In addition, in the process of loading and unloading the port container, the method has important significance for accurately calculating the stop position of the collection card and guiding the collection card in real time. If the parking position is inaccurate during operation, on one hand, a serious safety accident that the container truck is crashed can be caused; on the other hand, when the container and the truck container tray are handled, the container and the truck container tray are deformed due to inaccurate alignment, and potential safety hazards exist.
The traditional integrated card positioning and guiding system mainly uses a laser radar, utilizes a laser scanning ranging principle and is assisted by a rotating mechanism to process and analyze the obtained scanning data, and a template is required to be manually designed for template matching so as to judge the position of a working container truck. However, in practical situations, the laser radar data is not intuitive, the abstract data is processed, and all template data are designed manually, so that more development cost is required for a developer, and difficulties exist for a manager and later operation and maintenance, and more effort is required. In addition, the laser radar is easily influenced by external environment change factors due to the working principle, the resolution is insufficient, the detail characteristics such as an external collecting card lock head and the like can not be positioned, other objects can not appear in the scanning range, and the scanning range can not be blocked; in addition, the rotating mechanism is used, the installation position is strictly required, the data refreshing frequency is low, and the operation efficiency is greatly reduced.
Disclosure of Invention
In order to solve the problems, the invention provides a positioning and guiding system and a method for the loading and unloading operation of a container truck based on vision, which can solve the problems existing in the prior art.
The invention relates to a visual container truck loading and unloading operation positioning and guiding system which comprises a digital camera, a rear end control device, a signal trigger and an indication guiding device, wherein the digital camera is arranged on a cross beam above a field bridge crane, the rear end control device is connected with the signal trigger, the digital camera is connected with the rear end control device, and the rear end control device is connected with the indication guiding device.
In the scheme, the digital camera is connected with the back-end control equipment through the optical fiber.
In the above scheme, the back-end control device is a computer.
The container truck loading and unloading operation positioning and guiding method based on vision includes that an operation lane container truck image acquired by a digital camera is processed by adopting an image inclination correction algorithm, and the deviation between the position of the camera and the direction of a truck collecting lane is corrected; and calculating the operation image of the collecting card after the inclination correction in real time, and further quantitatively calculating the position of the operation collecting card and the deviation from the standard position, so as to realize the positioning and guiding of the loading and unloading operation container truck.
In the above scheme, the method comprises the following steps in detail:
s1: powering up the system and automatically starting software;
s2: the high-speed camera overlooks the shooting card collecting lane;
s3: the acquired image is processed by an image inclination correction algorithm;
s4: the corrected image is processed by a deep learning image feature detection algorithm;
s5: detecting the characteristic areas of lock holes of various containers, edges of the pallet of the collecting card or the baffle plates of the pallet;
s6: calculating the center position of each characteristic region;
s7: calculating the average value of one or more central points of all areas of each class at the front end and the rear end;
s8: averaging the obtained average value of the front end and the rear end to obtain the position of the card;
s9: obtaining the position deviation of the lifting appliance trolley direction according to the X direction of the calculated collector card position;
s10: according to the Y direction of the calculated collector card position, obtaining the real-time position of the collector card in the running direction;
s11: identifying a working mode;
s12: outputting positioning guide information;
s13: and guiding the display device to display.
In the above scheme, S14 is further included: recording the position reference of each operation mode, detecting and positioning according to the characteristics of different types of containers, container collecting tray locks, corners, baffles and the like, and realizing automatic judgment of operation conditions so as to determine the positioning reference; s14 goes to S12.
In the scheme, the rear-end control equipment analyzes the output card guide information in real time, and the LED display equipment is used for displaying the quantized guide information according to the current operation card state and the operation working condition.
An electronic device, wherein the electronic device comprises: a processor and a memory storing a computer executable program which when executed causes the processor to perform the method of any of claims 4-7.
A computer readable storage medium, wherein the computer readable storage medium stores one or more programs which, when executed by a processor, implement the method of any of claims 4-7.
The invention has the advantages and beneficial effects that: the invention provides a visual container truck loading and unloading operation positioning and guiding system and a visual container truck loading and unloading operation positioning and guiding method, which adopt a overlook camera arranged above a loading and unloading operation container truck to collect operation scene images, combine an image inclination correction algorithm and a deep learning feature detection technology, have flexible camera installation positions on the basis of guaranteeing visual fields, have small influence by external environment factors, can adapt to partial shielding conditions in the visual fields, have visual data, are convenient to manage and maintain, have accurate pixel-level detection and positioning, can combine operation mode identification and self-adaptive decision positioning, display humanized collection card guiding information, guide the loading and unloading operation container truck to stop accurately, and realize accurate box grabbing and placing of a lifting appliance. Compared with the traditional laser radar system, the invention has wider application range, higher degree of freedom and higher cost performance.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the invention, and that other drawings can be obtained according to these drawings without inventive faculty for a person skilled in the art.
FIG. 1 is a schematic diagram of the circuit principle of the present invention;
FIG. 2 is a schematic flow chart of the method of the present invention;
FIG. 3 is a schematic view of a track mounted crane according to an embodiment;
fig. 4 is a schematic structural view of a second embodiment of a crane mounted on a shore bridge.
In the figure: 1. digital camera 2, back-end control device 3, signal trigger 4, instruction guiding device 5, track crane 6, shore bridge crane
Detailed Description
The following describes the embodiments of the present invention further with reference to the drawings and examples. The following examples are only for more clearly illustrating the technical aspects of the present invention, and are not intended to limit the scope of the present invention.
As shown in fig. 1, the invention relates to a positioning and guiding system for a loading and unloading operation of a container truck based on vision, which comprises a digital camera 1, a rear end control device 2, a signal trigger 3 and an indicating and guiding device 4, wherein the digital camera 1 is arranged on a cross beam above a field bridge crane, the rear end control device 2 is connected with the signal trigger 3, the digital camera 1 is connected with the rear end control device 2, and the rear end control device 2 is connected with the indicating and guiding device 4.
The digital camera 1 is connected to a back-end control device 2 via an optical fiber. The back-end control device 2 is a computer.
The digital camera 1 is arranged at the high position of a side support column of the integrated card lane, and shoots a container truck (an integrated card for short) on the lane in a downward overlooking mode to obtain an integrated card operation scene image, and the digital camera is connected with the rear-end control equipment through an optical fiber; the rear end control device is connected with the guiding display device and the lifting appliance trolley PLC.
The container truck loading and unloading operation positioning and guiding method based on vision includes that an operation lane container truck image acquired by a digital camera is processed by adopting an image inclination correction algorithm, and the deviation between the position of the camera and the direction of a truck collecting lane is corrected; and calculating the operation image of the collecting card after the inclination correction in real time, and further quantitatively calculating the position of the operation collecting card and the deviation from the standard position, so as to realize the positioning and guiding of the loading and unloading operation container truck.
As shown in fig. 2, in the above scheme, the method includes the following steps:
s1: powering up the system and automatically starting software;
s2: the high-speed camera overlooks the shooting card collecting lane;
s3: the acquired image is processed by an image inclination correction algorithm;
s4: the corrected image is processed by a deep learning image feature detection algorithm;
s5: detecting the characteristic areas of lock holes of various containers, edges of the pallet of the collecting card or the baffle plates of the pallet;
s6: calculating the center position of each characteristic region;
s7: calculating the average value of one or more central points of all areas of each class at the front end and the rear end;
s8: averaging the obtained average value of the front end and the rear end to obtain the position of the card;
s9: obtaining the position deviation of the lifting appliance trolley direction according to the X direction of the calculated collector card position;
s10: according to the Y direction of the calculated collector card position, obtaining the real-time position of the collector card in the running direction;
s11: identifying a working mode;
s12: outputting positioning guide information;
s13: and guiding the display device to display.
Further comprising S14: recording the position reference of each operation mode, detecting and positioning according to the characteristics of different types of containers, container collecting tray locks, corners, baffles and the like, and realizing automatic judgment of operation conditions so as to determine the positioning reference; s14 goes to S12.
And for the card guide information which is analyzed and output by the back-end control equipment in real time, the LED display equipment is used, and the display equipment can display the quantized guide information according to the current operation card state and the operation working condition.
The system adopts a digital camera arranged at the high position of the side of a truck collecting lane of a field bridge crane/shore bridge crane, a truck of an operation container on the lane is shot downwards in overlooking mode, an image of the truck collecting operation scene is obtained, the digital camera can change the installation position according to the use scene, the premise is that the truck collecting area of the loading and unloading box operation is completely brought into the view field range, the length of the truck collecting operation scene occupies more than 90% of the same-directional length of the view field, the acquired operation scene is transmitted to a rear-end control device, and the rear-end control device carries out a series of processing on the image so as to realize the position calculation and the guide information output of the operation truck collecting. The rear end control equipment corrects the inclined collecting card operation image acquired by the camera into a front-view calculated pose image through an image inclination correction algorithm so as to facilitate the subsequent position calculation; the image inclination correction algorithm is used for correcting the mounting pose of the camera to the actual processing calculation pose. The position of the camera after being installed is calibrated, the mapping relation from the calibrated image to the corrected image is utilized, so that the transformation relation from the shooting pose of the camera to the positioning calculation pose is obtained, the original image collected by the camera can be subjected to inclination correction transformation, the image capable of carrying out quantitative calculation on the position of the collector card normally is obtained, further, the detection of the interested characteristic region of the image is realized, and the position of the collector card is calculated.
The image inclination correction can avoid a plurality of troubles of adjusting the mounting pose of the camera in the earlier stage, and the mounting position is flexible; the correction of the image inclination requires calibrating the camera to determine the camera parameters and the pose relationship, and the essence of the correction of the image inclination is to generate a projection transformation matrix, wherein the algorithm steps are as follows:
1) judging whether the source image and the calibration plate source image have the same size when in use, if so, continuing to step 2), otherwise, continuing to step 3);
2) Respectively scaling four reference coordinate points (stored in srcPoints) of the calibration plate in equal proportion;
3) Solving a bounding box rect of four reference coordinate points (srcPoints) of the calibration plate;
4) Solving half delta of the diagonal length of the bounding box rect;
5) Calculating corresponding four target points (stored in dstPoints) after transformation according to the diagonal length;
6) Calculating a projective transformation matrix from srcPoints to dstPoints, namely an original projective transformation matrix perspective Mat0;
7) Computing four vertices (stored in boundPoints) of the image boundary;
8) Calculating bounding box vertexes (stored in dstBuoundPts) after original projection transformation of the image vertexes;
9) Respectively solving the maximum value xmax and the minimum value xmin of x and y coordinates of the vertex of the bounding box, zeroing the origin of the vertex of the bounding box, and solving a new dstBundPts;
10 Calculating a projective transformation matrix from boundPoints to dstBundPts, namely a final projective transformation matrix perspective Mat;
11 From xmax, ymax, xmin, the size dstSz of the target image is determined.
In practical application, the projection transformation matrix and the image obtained by the algorithm are required to be recorded, when the image correction is required, the transformation matrix is read in, the acquired oblique view angle image can be corrected into a non-oblique positive view angle image, and then the deep learning image interesting characteristic detection is carried out on the corrected image, so that the position of the collector card is calculated.
Calculating the positions of interested objects such as containers, card collecting trays and the like in the images in real time, and further quantitatively calculating the positions of the operation cards and the deviation from the standard positions; the step of calculating the position of the operation set card is as follows: 1) Adopting a deep neural network image example segmentation algorithm to detect and identify characteristic areas such as container buttonholes, pallet corners of the collection card, pallet lock heads or pallet baffles in the image; 2) For the detected multiple characteristic areas, sequentially and respectively calculating the central point positions of the central lines of the upper edge, the lower edge, the left edge and the right edge of each area; 3) For the calculated central point positions of each characteristic region, respectively calculating the average value of the central points of one or more regions at the front end (in the direction of the vehicle head) and the rear end (in the direction of the vehicle tail) of each category according to different categories, then calculating the average value of the average values of the front end and the rear end, and then referring to the position average value of the corresponding category according to a self-adaptive decision positioning algorithm according to the working condition to obtain the working card position, wherein the card position is divided into the trolley direction and the cart direction position according to the x direction and the y direction of the image;
the self-adaptive decision positioning algorithm can detect and position according to the characteristics of different types of containers, card collecting trays and the like under the condition of recording the position reference of each working condition, and realize automatic judgment of the working condition, thereby determining the positioning reference without manual specification of a driver;
the guide indication equipment of the system can display the card guide information which is output by the back-end control equipment in real time through the specific positioning guide display method, and the quantized guide information display is carried out according to the current operation card status and the operation working condition.
Preferably, the calculation of the position deviation of the container truck by the system is better in precision and real-time than the visual measurement result of drivers or bystanders, and can accurately provide guiding indication for the container handling operation container truck, so that the potential safety hazard of the container handling operation is effectively reduced, the safety production is ensured, and the handling efficiency is improved.
Embodiment one:
a vision-based integrated card positioning and guiding system installed on a track crane comprises a back-end control device 2 and two digital cameras 1.
As shown in fig. 3, at the high positions of the lane side support posts on both sides of the whole track crane 5, digital cameras 1 for photographing downwards are respectively installed; the field of view of the digital camera 1 should be capable of covering the operation area of the truck and the operation area should occupy a larger range, so that the embodiment is applicable to the image tilt correction, the detection of the interesting characteristic areas such as the container and the truck tray, and the like, and the operation mode identification and the truck position calculation are realized.
The rear end control equipment 2 is arranged in an electric room of the track crane 5 and the field bridge crane, the rear end control equipment 2 is connected with the two digital cameras 1 through optical fibers so as to transmit image data of the collector card in an operation area, the rear end control equipment 2 is connected with the field bridge crane PLC in the electric room through a network cable so as to correct the direction position deviation of the lifting appliance trolley, and the other side of the rear end control equipment is connected with the lane guiding indication equipment 4 at two sides through the optical fibers so as to display guide indication information of the collector card and guide a driver of the collector card to stop accurately.
Embodiment two:
as shown in fig. 4, the main difference between the present embodiment and the first embodiment is that, due to the large difference in the lane layout between the shore bridge crane 6 and the track crane 5: the digital cameras 1 for shooting downwards are respectively arranged at the high positions of the cross beams above the truck loading and unloading lanes of the shore bridge crane 6; the field of view of the digital camera 1 should be capable of covering the operation area of the truck and the operation area should occupy a larger range, so that the embodiment is also ensured to be applicable to the image tilt correction, the detection of the interesting characteristic areas such as the container and the truck tray, and the like, and the steps of operation mode identification and the calculation of the truck position are realized; and a guide indicating device 4 is arranged on a beam above the collection card loading and unloading lane of the shore bridge crane 6, so that the collection card guide information is ensured to be checked.
Through innovation and improvement of the invention, the invention can be suitable for common field bridge/quay bridge container loading and unloading equipment of container ports and wharfs, replaces manual observation or traditional laser radar positioning and guiding systems, reduces potential safety hazards in the process of container loading and unloading operation, and improves the operation efficiency.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (9)
1. The container truck loading and unloading operation positioning and guiding system based on vision is characterized by comprising a digital camera, a rear end control device, a signal trigger and an indication guiding device, wherein the digital camera is arranged on a cross beam above a field bridge crane, the rear end control device is connected with the signal trigger, the digital camera is connected with the rear end control device, and the rear end control device is connected with the indication guiding device.
2. The vision-based container truck loading and unloading operation positioning and guiding system according to claim 1, wherein said digital camera is connected with a back-end control device through an optical fiber.
3. A vision-based container truck loading and unloading operation positioning and guiding system according to claim 2, wherein said back-end control device is a computer.
4. A container truck loading and unloading operation positioning and guiding method based on vision is characterized in that an operation lane container truck image acquired by a digital camera is processed by adopting an image inclination correction algorithm, and the deviation between the position of the camera and the direction of a truck collecting lane is corrected; and calculating the operation image of the collecting card after the inclination correction in real time, and further quantitatively calculating the position of the operation collecting card and the deviation from the standard position, so as to realize the positioning and guiding of the loading and unloading operation container truck.
5. The vision-based container truck loading and unloading operation positioning and guiding method according to claim 4, characterized by comprising the following steps in detail:
s1: powering up the system and automatically starting software;
s2: the high-speed camera overlooks the shooting card collecting lane;
s3: the acquired image is processed by an image inclination correction algorithm;
s4: the corrected image is processed by a deep learning image feature detection algorithm;
s5: detecting the characteristic areas of lock holes of various containers, edges of the pallet of the collecting card or the baffle plates of the pallet;
s6: calculating the center position of each characteristic region;
s7: calculating the average value of one or more central points of all areas of each class at the front end and the rear end;
s8: averaging the obtained average value of the front end and the rear end to obtain the position of the card;
s9: obtaining the position deviation of the lifting appliance trolley direction according to the X direction of the calculated collector card position;
s10: according to the Y direction of the calculated collector card position, obtaining the real-time position of the collector card in the running direction;
s11: identifying a working mode;
s12: outputting positioning guide information;
s13: and guiding the display device to display.
6. The vision-based container truck loading and unloading operation positioning and guiding method according to claim 5, further comprising S14: recording the position reference of each operation mode, detecting and positioning according to the characteristics of different types of containers, container collecting tray locks, corners, baffles and the like, and realizing automatic judgment of operation conditions so as to determine the positioning reference; s14 goes to S12.
7. The visual container truck loading and unloading operation positioning and guiding method according to claim 6, wherein the rear-end control device analyzes the output card guide information in real time, and the display device can display the quantized guide information according to the current operation card state and the operation working condition by using the LED display device.
8. An electronic device, wherein the electronic device comprises: a processor and a memory storing a computer executable program which when executed causes the processor to perform the method of any of claims 4-7.
9. A computer readable storage medium, wherein the computer readable storage medium stores one or more programs which, when executed by a processor, implement the method of any of claims 4-7.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310192129.6A CN116310287A (en) | 2023-03-02 | 2023-03-02 | Container truck loading and unloading operation positioning and guiding system and method based on vision |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310192129.6A CN116310287A (en) | 2023-03-02 | 2023-03-02 | Container truck loading and unloading operation positioning and guiding system and method based on vision |
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| CN116310287A true CN116310287A (en) | 2023-06-23 |
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| CN202310192129.6A Pending CN116310287A (en) | 2023-03-02 | 2023-03-02 | Container truck loading and unloading operation positioning and guiding system and method based on vision |
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