Agv carrying tray error calibration method and system, computer and storage medium

Abstract

The application discloses an AGV carrying tray error calibration method and system, a computer and a storage medium, and the method comprises the following steps: acquiring first point cloud data detected by a fork laser radar in real time and acquiring second point cloud data detected by a vehicle body laser radar in real time; optimizing and adjusting AGV path data according to a path optimization checking rule, the first point cloud data and the second point cloud data, so that the AGV travels to a picking and placing target site according to an optimal path; when the picking and placing target site is reached, performing a goods location coordinate checking process according to the first point cloud data and the second point cloud data; judging whether the goods location coordinate checking result is a preset checking result, if the judgment is yes, it indicates that the goods location coordinate checking is successful, and the picking and placing work is performed, if the judgment is no, it indicates that the goods location coordinate checking is unsuccessful, and the alarm work is performed. The application can reduce the problems of picking and placing abnormalities or failures caused by the cumulative error of the tray, and has high carrying precision and stability.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of warehouse management, and particularly relates to an AGV pallet carrying error calibration method and system, a computer and a storage medium. BACKGROUND

[0002] In the current modern intelligent warehouse system, AGV is a key device for realizing automatic carrying of goods, and its efficient and accurate operation capacity is crucial for improving the operation efficiency of the entire warehouse system. However, in actual application, AGV faces various factors leading to pallet accumulation error problems, affecting the carrying operation precision and stability. These errors mainly come from the mechanical processing error of AGV, the positioning relative error between AGVs, uneven ground and other unknown error sources. The above errors always exist and have certain accumulation properties, so in order to realize accurate carrying of AGV, the following schemes are usually adopted at present:

[0003] 1. Manual intervention: manually push the pallet on the work station, or manually operate to assist in taking away the pallet.

[0004] 2. Camera recognition: take a photo of the pallet before taking the goods, calculate the relative position offset, and regenerate the trajectory to take the goods.

[0005] 3. Two-dimensional code correction: install two-dimensional codes at the bottom of all shelves, and AGV uses a camera to shoot the two-dimensional code upward to obtain offset data for posture correction.

[0006] However, the above pallet error correction methods have certain limitations:

[0007] 1. Manual intervention has certain learning cost and labor cost, and if the manual processing is not timely, the AGV operation efficiency will be greatly reduced.

[0008] 2. The cost of the camera and its algorithm is high, and it often only supports standard pallets on the market, and there is a high development cost for non-standard pallets, and the final correction effect cannot be guaranteed. Moreover, the camera is limited by the calibration process. When the camera calculates the relative position, if the AGV cannot guarantee accuracy during the operation on the regenerated path, it will also lead to failure of taking and placing goods. At the same time, the camera is easily disturbed by light, affecting the detection and calculation accuracy.

[0009] 3. Two-dimensional code correction is commonly used for AGV, and forklift AGV often cannot install such sensors. All pallets at the bottom need to be pasted with two-dimensional codes, which is not friendly to the site with many pallets. Moreover, the pasting accuracy is required, and the installation efficiency and cost are high.

[0010] In addition, the error correction scheme of the above tray can only detect the target tray position, and cannot detect whether the tray obtained by the current AGV has an error. SUMMARY

[0011] The technical problem to be solved by the present application is to provide an AGV carrying tray error calibration method, system, computer and storage medium, which can reduce the problems of abnormal or failed picking and placing caused by tray cumulative error, effectively improve the carrying operation precision, efficiency and stability, and has strong overall adaptability.

[0012] To solve the above technical problems, the present application provides an AGV carrying tray error calibration method, which comprises: acquiring first point cloud data detected by a fork laser radar in real time and acquiring second point cloud data detected by a vehicle body laser radar in real time, wherein the first point cloud data is the point cloud data of the tray legs of a target tray placed on the fork, and the second point cloud data is the point cloud data of the tray legs of an auxiliary tray at a target storage location; optimizing and adjusting AGV path data according to a path optimization verification rule, the first point cloud data and the second point cloud data, so that the AGV travels to a picking and placing target site according to an optimal path; when the picking and placing target site is reached, performing a storage location coordinate verification process according to the first point cloud data and the second point cloud data; judging whether the storage location coordinate verification result is a preset verification result, if yes, indicating that the storage location coordinate verification is successful, and performing a picking and placing operation, if no, indicating that the storage location coordinate verification is unsuccessful, and performing an alarm operation.

[0013] As an improvement of the above scheme, before the AGV travels, it further comprises: calculating a detection area of the tray legs according to preset tray leg parameters; judging whether all the tray legs in the first point cloud data are in the detection area, if yes, indicating that the target tray is correctly placed on the fork, if no, indicating that the tray placed on the fork is abnormal, and performing an alarm operation.

[0014] As an improvement of the above scheme, during the travel of the AGV, it further comprises: performing a transfer tray position verification process according to the first point cloud data; when the transfer tray position verification is unsuccessful, performing an alarm operation.

[0015] As an improvement of the above scheme, the step of optimizing and adjusting the AGV path data according to the path optimization verification rule, the first point cloud data and the second point cloud data, so that the AGV vehicle travels to the picking and placing target site according to the optimal path, comprises: calculating the relative position data of the target pallet and the AGV motion center according to the first point cloud data, and calculating the relative position data of the auxiliary pallet and the AGV motion center according to the second point cloud data; calculating the difference between the relative position data of the target pallet and the AGV motion center and the relative position data of the auxiliary pallet and the AGV motion center in real time to obtain a position offset value; optimizing and adjusting the current AGV path data according to the position offset value to obtain optimal AGV path data; and controlling the AGV vehicle to travel to the picking and placing target site according to the AGV path data.

[0016] As an improvement of the above scheme, the step of performing storage location coordinate verification processing according to the first point cloud data and the second point cloud data when the picking and placing target site is reached comprises: calculating the relative position data of the target pallet and the AGV motion center according to the first point cloud data, and calculating the relative position data of the auxiliary pallet and the AGV motion center according to the second point cloud data; calculating the offset difference between the relative position data of the target pallet and the AGV motion center and the relative position data of the auxiliary pallet and the AGV motion center; and determining whether the offset difference is within a preset storage location error range, wherein if the determination is positive, it indicates that the storage location coordinate verification is successful, and if the determination is negative, it indicates that the storage location coordinate verification is unsuccessful.

[0017] As an improvement of the above scheme, the step of performing the transfer pallet position verification processing according to the first point cloud data comprises: when the target pallet is placed on the forks, calculating the initial relative position data of the target pallet and the AGV motion center according to the first point cloud data; during transportation, calculating the current relative position data of the target pallet and the AGV motion center according to the first point cloud data obtained in real time; calculating the difference between the current relative position data of the target pallet and the AGV motion center and the initial relative position data of the target pallet and the AGV motion center to obtain a pallet position offset difference value; and determining whether the pallet position offset difference value is within a preset offset value range, wherein if the determination is negative, it indicates that the transfer pallet position verification is unsuccessful.

[0018] Correspondingly, the application also provides an AGV carrying tray error calibration system, comprising an AGV, an error calibration controller, a fork laser radar, a vehicle body laser radar and a target tray, the fork laser radar is arranged below the fork of the AGV, the vehicle body laser radar is arranged at the lower part of the AGV, and the target tray is placed on the fork; the error calibration controller is connected with the AGV, the fork laser radar and the vehicle body laser radar respectively, and the error calibration controller comprises: an acquisition module, which is used for acquiring first point cloud data detected by the fork laser radar in real time and acquiring second point cloud data detected by the vehicle body laser radar in real time, wherein the first point cloud data is point cloud data of tray legs of the target tray placed on the fork, and the second point cloud data is point cloud data of tray legs of an auxiliary tray at a target storage and taking position; a path optimization module, which is used for optimizing and adjusting AGV path data according to a path optimization checking rule, the first point cloud data and the second point cloud data, so that the AGV travels to a target station for taking and placing goods according to an optimal path; a storage position checking module, which is used for performing storage position coordinate checking processing according to the first point cloud data and the second point cloud data when the target station for taking and placing goods is reached; and a storage position processing module, which is used for judging whether the storage position coordinate checking result is a preset checking result, if the result is the preset checking result, it is indicated that the storage position coordinate checking is successful, and taking and placing work is performed, and if the result is not the preset checking result, it is indicated that the storage position coordinate checking is not successful, and alarm work is performed.

[0019] As an improvement of the above-mentioned scheme, the error calibration controller further comprises: a tray calculation module, which is used for calculating a detection area of the tray legs according to preset tray leg parameters before the AGV travels; a tray confirmation module, which is used for judging whether all the tray legs in the first point cloud data are in the detection area, if the result is yes, it is indicated that the target tray is correctly placed on the fork, and if the result is no, it is indicated that the tray placed on the fork is abnormal, and alarm work is performed; a transfer tray checking module, which is used for performing transfer tray position checking processing according to the first point cloud data during the AGV travels; and a transfer tray processing module, which is used for performing alarm work when the transfer tray position checking is not successful.

[0020] Correspondingly, the application also provides a computer device, comprising a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above-mentioned method when executing the computer program.

[0021] Correspondingly, the application also provides a computer readable storage medium, which stores a computer program, and the computer program implements the steps of the above-mentioned method when executed by a processor.

[0022] The beneficial effects of the application are as follows:

[0023] The present application can reduce the problem of abnormal or failure of picking and placing caused by accumulated errors of the tray, effectively improve the precision, efficiency and stability of the carrying operation, has strong overall adaptability, and can reduce the probability of manual intervention and carrying cost. At the same time, compared with the existing camera recognition method, the present application has stronger adaptability to light interference, and the automatic calibration can greatly reduce the failure rate, further improving the overall efficiency of the warehouse system. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 is a flowchart of the AGV carrying tray error calibration method of the present application;

[0025] Figure 2 is a structural schematic diagram of the AGV carrying tray error calibration system of the present application Figure 1 ;

[0026] Figure 3 is a structural schematic diagram of the AGV carrying tray error calibration system of the present application Figure 2 ;

[0027] Figure 4 is a structural schematic diagram of the target tray of the present application;

[0028] Figure 5 is a structural schematic diagram of the error calibration controller of the present application Figure 1 ;

[0029] Figure 6 is a structural schematic diagram of the path optimization module of the present application;

[0030] Figure 7 is a structural schematic diagram of the storage location verification module of the present application;

[0031] Figure 8 is a structural schematic diagram of the error calibration controller of the present application Figure 2 ;

[0032] Figure 9 is a structural schematic diagram of the error calibration controller of the present application Figure 3 ;

[0033] Figure 10 is a structural schematic diagram of the transfer tray verification module of the present application. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical scheme and advantages of the present application clearer, the present application will be further described in detail below with reference to the drawings.

[0035] As Figure 1 shown, the embodiment of the present application provides an AGV carrying tray error calibration method, characterized in that it comprises:

[0036] S101. Acquire the first point cloud data detected in real time by the fork lidar and acquire the second point cloud data detected in real time by the vehicle lidar. The first point cloud data is the point cloud data of the pallet legs of the target pallet placed on the forks, and the second point cloud data is the point cloud data of the pallet legs of the auxiliary pallet at the target storage and retrieval location.

[0037] It should be noted that when the target pallet is placed on the forks of the AGV, the four pallet legs of the target pallet will be located below the forks. The fork lidar located below the forks can detect the four pallet legs of the target pallet within its detection horizontal plane. The vehicle body lidar located at the bottom of the AGV can detect the pallet legs of the bottom pallet (i.e., the auxiliary pallet for auxiliary calibration) among the pallets stacked at the target storage location within its horizontal detection range.

[0038] The first point cloud data includes the three-dimensional coordinate data (X, Y, Z coordinate data) of the pallet legs of the target pallet, and the second point cloud data includes the three-dimensional coordinate data (X, Y, Z coordinate data) of the pallet legs of the auxiliary pallet.

[0039] S102. Optimize and adjust the AGV path data according to the path optimization verification rules, the first point cloud data and the second point cloud data, so that the AGV can travel to the target station for picking up and placing goods according to the optimal path.

[0040] Specifically, the step of optimizing and adjusting the AGV path data according to the path optimization verification rules, the first point cloud data, and the second point cloud data so that the AGV can travel to the target pick-up and drop-off station along the optimal path includes:

[0041] Step 1: Calculate the relative position data between the target pallet and the AGV motion center based on the first point cloud data, and calculate the relative position data between the auxiliary pallet and the AGV motion center based on the second point cloud data;

[0042] It should be noted that both the first point cloud data and the first point cloud data can be converted into coordinates with the AGV vehicle's motion center as the origin of the coordinate system, thereby obtaining the relative position data between the target pallet and the AGV motion center, as well as the relative position data between the auxiliary pallet and the AGV motion center.

[0043] Step 2: Calculate the difference between the relative position data of the target pallet and the AGV motion center and the relative position data of the auxiliary pallet and the AGV motion center in real time to obtain the position offset value;

[0044] It should be noted that by calculating the difference between the relative position data of the target tray and the AGV motion center and the relative position data of the auxiliary tray and the AGV motion center, the current position of the AGV motion trolley and the position offset value of the target access location can be obtained, such as the coordinate offset value in the X direction and the Y direction in the horizontal plane.

[0045] Step 3, optimizing and adjusting the current AGV path data according to the position offset value to obtain optimal AGV path data;

[0046] Step 4, controlling the AGV trolley to travel to the target site according to the AGV path data.

[0047] It should be noted that the current AGV path data can be optimized and adjusted according to the position offset value to obtain optimal AGV path data, and the AGV trolley can be accurately moved to the target access location by controlling the AGV trolley along the AGV path data, thereby improving the precision of the cargo handling operation.

[0048] S103, when reaching the target site, performing a location coordinate checking process according to the first point cloud data and the second point cloud data;

[0049] Specifically, the step of performing a location coordinate checking process according to the first point cloud data and the second point cloud data when reaching the target site includes:

[0050] Step 1, calculating the relative position data of the target tray and the AGV motion center according to the first point cloud data and the relative position data of the auxiliary tray and the AGV motion center according to the second point cloud data;

[0051] Step 2, calculating the offset difference between the relative position data of the target tray and the AGV motion center and the relative position data of the auxiliary tray and the AGV motion center;

[0052] Step 3, judging whether the offset difference is within a preset location error range, if the judgment is yes, it means that the location coordinate checking is successful, if the judgment is no, it means that the location coordinate checking is unsuccessful.

[0053] It should be noted that when the AGV moves to the target picking and placing position, the relative position data of the target pallet and the AGV movement center and the relative position data of the auxiliary pallet and the AGV movement center can be calculated respectively by the current first point cloud data and the first point cloud data, and the offset difference value between the two, that is, the offset coordinate difference value in the X direction and the Y direction, can be calculated. When the offset difference value is in the preset position error range, it means that the offset difference value is in the acceptable range, the position coordinate verification is successful, the offset degree is very low, the positioning is accurate, and it does not affect the accurate picking or storage work, thereby improving the stability of the carrying operation; when the offset difference value is not in the preset position error range, it means that the offset difference value has exceeded the acceptable range, the position coordinate verification is not successful, the offset degree is too high, and it will affect the accuracy of the picking or storage work, and even cause the picking and placing work to fail, thereby reducing the stability of the carrying operation.

[0054] S104, judge whether the position coordinate verification result is a preset verification result, if yes, it means that the position coordinate verification is successful, and the picking and placing work is performed, if not, it means that the position coordinate verification is not successful, and the alarm work is performed.

[0055] It should be noted that the preset verification result is a verification success threshold, when the position coordinate verification result is the preset verification result, it means that the position coordinate verification is successful, and the picking and placing work is performed; when the position coordinate verification result is not the preset verification result, it means that the position coordinate verification is not successful, and the alarm work is performed, so as to timely notify the staff to maintain and process, and re-verify the position coordinate twice or multiple times, if the verification result is still unsuccessful, the staff processes the maintenance, so as to ensure the subsequent carrying operation precision and stability.

[0056] Further, the AGV further comprises the following before the AGV travels:

[0057] Step 1, calculate the detection area of the pallet leg according to the preset pallet leg parameter;

[0058] It should be noted that the preset pallet leg parameter includes the shape of the leg, the size of the leg, the interval size between the legs, and the position of the leg, etc. The entire layout area of the four pallet legs, that is, the detection area, can be calculated by the parameter.

[0059] Step 2, judge whether all the pallet legs in the first point cloud data are in the detection area, if yes, it means that the target pallet is correctly placed on the fork, if not, it means that the pallet placed on the fork is abnormal, and the alarm work is performed.

[0060] It should be noted that the actual detection area of all the tray legs in the first point cloud data is determined according to the coordinate data, and when the actual detection area is in the preset detection area, it indicates that the target tray is correctly placed on the fork, so as to facilitate subsequent carrying work; when the actual detection area is not in the preset detection area, it indicates that the tray placed on the fork is abnormal, such as misplacement of the tray or placement of a non-target tray type or a non-tray, etc. At this time, an alarm is performed to timely inform the staff to check and maintain the processing, so as to put into carrying work as soon as possible and improve the carrying work efficiency.

[0061] Preferably, the present application can also be marked by pasting reflective paper on the tray legs for marker recognition, thereby improving the radar recognition accuracy.

[0062] In order to avoid the influence of the fork tray position error on the subsequent carrying work in the driving process of the AGV, such as the fork tray position error caused by uneven road surface or other factors. For this purpose, the present application further comprises: performing a transfer tray position verification process according to the first point cloud data during driving of the AGV; and performing an alarm when the transfer tray position verification is unsuccessful.

[0063] Specifically, the step of performing a transfer tray position verification process according to the first point cloud data comprises:

[0064] Step 1: When the target tray is placed on the fork, the initial relative position data between the target tray and the AGV motion center is calculated according to the first point cloud data;

[0065] Step 2: During transportation, the current relative position data between the target tray and the AGV motion center is calculated according to the real-time acquired first point cloud data;

[0066] Step 3: The difference between the current relative position data between the target tray and the AGV motion center and the initial relative position data between the target tray and the AGV motion center is calculated to obtain a tray position offset difference value;

[0067] Step 4: It is judged whether the tray position offset difference value is in a preset offset value range, and if the judgment is no, it indicates that the transfer tray position verification is unsuccessful.

[0068] It should be noted that when the target tray is placed on the fork, the initial relative position data between the target tray and the AGV motion center can be calculated according to the first point cloud data and saved; during transportation, the current relative position data between the target tray and the AGV motion center is calculated according to the real-time acquired first point cloud data.

[0069] According to the current relative position data of the target tray and the AGV motion center and the initial relative position data of the target tray and the AGV motion center, when the tray position offset difference is within the preset offset value range, it indicates that the jitter offset is less, and the tray position is in the safe range, at this time, the transfer tray position verification is successful, and the transfer tray position verification is continued; when the tray position offset difference is not within the preset offset value range, it indicates that the jitter offset is more, and the tray is prone to danger, at this time, the transfer tray position verification is not successful, an alarm is executed, and the AGV vehicle transportation is stopped, so as to avoid the abnormality or failure of the subsequent picking and placing caused by the accumulated error of the tray, and early notification of the staff for maintenance processing is realized, so as to accurately realize the picking and placing work and ensure the stability of the carrying work.

[0070] In order to improve the safety of the carrying work, the safety protection scanning areas of the fork laser radar and the vehicle body laser radar can be respectively arranged, when there is an obstacle in the safety protection scanning area of the double horizontal plane radar, the AGV vehicle can be controlled to stop moving, so as to avoid collision and accidents, and improve the safety of the carrying work.

[0071] As shown in Figures 2 to 5 The present application also provides an AGV carrying tray error calibration system, which comprises an AGV vehicle 1, an error calibration controller 2, a fork laser radar 3, a vehicle body laser radar 4 and a target tray 5, the fork laser radar 3 is arranged below the fork 11 of the AGV vehicle 1, the vehicle body laser radar 4 is arranged at the lower part of the AGV vehicle 1, and the target tray 5 is placed on the fork 11. The AGV vehicle 1 is a stack AGV vehicle, and the target tray 5 and the auxiliary tray are both heavy-load self-stacking trays containing four tray legs 51.

[0072] The error calibration controller 2 is connected with the AGV vehicle 1, the fork laser radar 3 and the vehicle body laser radar 4 respectively, and comprises:

[0073] The acquisition module 21 is used for acquiring the first point cloud data detected by the fork 11 laser radar 3 in real time and acquiring the second point cloud data detected by the vehicle body laser radar 4 in real time, wherein the first point cloud data is the point cloud data of the tray legs 51 of the target tray 5 placed on the fork 11, and the second point cloud data is the point cloud data of the tray legs of the auxiliary tray at the target storage and picking position;

[0074] It should be noted that the fork 11 laser radar 3 located below the fork 11 can detect the four tray legs 51 of the target tray 5 in its detection horizontal plane; and the vehicle body laser radar 4 located at the lower part of the AGV vehicle 1 can detect the tray legs of the lowermost tray (i.e. the auxiliary calibration auxiliary tray) in the stacked tray at the target storage and picking position in its horizontal detection range.

[0075] The first point cloud data includes three-dimensional coordinate data (X, Y, Z coordinate data) of the tray legs 51 of the target tray 5, and the second point cloud data includes three-dimensional coordinate data (X, Y, Z coordinate data) of the tray legs of the auxiliary tray.

[0076] The path optimization module 22 is configured to optimize and adjust AGV path data according to path optimization checking rules, the first point cloud data, and the second point cloud data, so that the AGV vehicle travels to the target storage and retrieval site along an optimal path.

[0077] Specifically, as shown in the figure, the path optimization module 22 includes: Figure 6

[0078] The first position calculation unit 221 is configured to calculate relative position data of the target tray 5 and the AGV motion center according to the first point cloud data, and calculate relative position data of the auxiliary tray and the AGV motion center according to the second point cloud data.

[0079] It should be noted that the first point cloud data and the first point cloud data can be converted into coordinates with the AGV vehicle motion center as the coordinate system origin, so that the relative position data of the target tray 5 and the AGV motion center and the relative position data of the auxiliary tray and the AGV motion center can be obtained.

[0080] The first difference calculation unit 222 is configured to calculate the difference between the relative position data of the target tray 5 and the AGV motion center and the relative position data of the auxiliary tray and the AGV motion center in real time, so as to obtain a position offset value.

[0081] It should be noted that by calculating the difference between the relative position data of the target tray 5 and the AGV motion center and the relative position data of the auxiliary tray and the AGV motion center, the current position of the AGV motion vehicle and the position offset value of the target storage and retrieval site can be obtained, such as the coordinate offset value in the X direction and the Y direction on the horizontal plane.

[0082] The path optimization unit 223 is configured to optimize and adjust the current AGV path data according to the position offset value, so as to obtain optimal AGV path data.

[0083] The path processing unit 224 is configured to control the AGV vehicle 1 to travel to the target storage and retrieval site according to the AGV path data.

[0084] It should be noted that the current AGV path data can be optimized and adjusted according to the position offset value to obtain optimal AGV path data, and the AGV vehicle 1 can be accurately moved to the target storage and retrieval site by controlling the AGV vehicle 1 to travel along the AGV path data, thereby improving the accuracy of the cargo handling operation.​

[0085] a storage location verification module 23, configured to perform a storage location coordinate verification process according to the first point cloud data and the second point cloud data when reaching the target picking and placing station;

[0086] Specifically, as shown in the figure, the storage location verification module 23 comprises: Figure 7 a second position calculation unit 231, configured to calculate relative position data of the target tray 5 and the AGV motion center according to the first point cloud data and calculate relative position data of the auxiliary tray and the AGV motion center according to the second point cloud data;

[0087] a second difference calculation unit 232, configured to calculate a deviation difference between the relative position data of the target tray 5 and the AGV motion center and the relative position data of the auxiliary tray and the AGV motion center;

[0088] a storage location verification unit 233, configured to determine whether the deviation difference is within a preset storage location error range, and if yes, it means that the storage location coordinate verification is successful, and if no, it means that the storage location coordinate verification is unsuccessful.

[0089] It should be noted that when the AGV 1 moves to the target picking and placing station, the relative position data of the target tray 5 and the AGV motion center and the relative position data of the auxiliary tray and the AGV motion center can be calculated respectively by the current first point cloud data and the first point cloud data, and the deviation difference between the two can be calculated, i.e. the deviation coordinate difference in X direction and Y direction.

[0090] When the deviation difference is within the preset storage location error range, it means that the deviation difference is within an acceptable range, the storage location coordinate verification is successful, the deviation degree is extremely low, the positioning is accurate, and it does not affect the accuracy of picking or storing work, thereby improving the stability of the carrying operation; when the deviation difference is not within the preset storage location error range, it means that the deviation difference has exceeded the acceptable range, the storage location coordinate verification is unsuccessful, the deviation degree is too high, which will affect the accuracy of the picking or storing work, and even cause the picking and placing work to fail, thereby reducing the stability of the carrying operation.

[0091] a storage location processing module 24, configured to determine whether the storage location coordinate verification result is a preset verification result, and if yes, it means that the storage location coordinate verification is successful, and the picking and placing work is performed, and if no, it means that the storage location coordinate verification is unsuccessful, and the alarm work is performed.

[0092]

[0093] ​It should be noted that the preset check result is a check success threshold, when the goods location coordinate check result is the preset check result, it means that the goods location coordinate check is successful, and the taking and placing work is executed; when the goods location coordinate check result is not the preset check result, it means that the goods location coordinate check is not successful, and the alarm work is executed, so as to timely inform the staff to maintain processing, and recheck the goods location coordinate for two or more times, if the check result is still unsuccessful, the staff carries out maintenance processing, so as to ensure the subsequent carrying operation precision and stability.

[0094] As shown in Figure 8 , the error calibration controller 2 further comprises:

[0095] The tray computing module 25 is used for calculating the detection area of the tray leg according to the preset tray leg parameters before the AGV car drives;

[0096] It should be noted that the preset tray leg parameters include the shape of the leg, the size of the leg, the interval size between the legs and the position of the leg, etc., and the entire layout area of the four tray legs, that is, the detection area, can be calculated through the parameters;

[0097] The tray confirmation module 26 is used for judging whether all the tray legs in the first point cloud data are in the detection area, if yes, it means that the target tray is correctly placed on the fork, if no, it means that the tray placed on the fork is abnormal, and the alarm work is executed;

[0098] It should be noted that the actual detection area of all the tray legs in the first point cloud data is determined according to the coordinate data of the tray legs, when the actual detection area is in the preset detection area, it means that the target tray is correctly placed on the fork, so as to carry out the subsequent carrying work; when the actual detection area is not in the preset detection area, it means that the tray placed on the fork is abnormal, such as misplacement of the tray, placement of a non-target tray type or non-tray, etc., at this time, the alarm work is carried out, so as to timely inform the staff to check and maintain processing, so as to put into carrying work as soon as possible and improve the carrying operation efficiency.

[0099] Preferably, the present application can also mark the radar recognition precision by pasting reflective paper on the tray leg.

[0100] In order to avoid the influence of the fork tray position error on the subsequent carrying work in the driving process of the AGV car. Figure 9 As shown in

[0101] The transfer tray verification module 27 is configured to perform transfer tray position verification processing according to the first point cloud data during the driving of the AGV.

[0102] Specifically, as shown in Figure 10 The transfer tray verification module 27 includes:

[0103] The first transfer tray position calculation unit 271 is configured to calculate initial relative position data between the target tray and the AGV motion center according to the first point cloud data when the target tray is placed on the forks.

[0104] The second transfer tray position calculation unit 272 is configured to calculate current relative position data between the target tray and the AGV motion center according to the first point cloud data acquired in real time during the transportation.

[0105] The transfer tray difference calculation unit 273 is configured to calculate a difference between the current relative position data between the target tray and the AGV motion center and the initial relative position data between the target tray and the AGV motion center to obtain a tray position offset difference.

[0106] The transfer tray processing unit 274 is configured to determine whether the tray position offset difference is within a preset offset value range. If the determination result is negative, it indicates that the transfer tray position verification is unsuccessful.

[0107] It should be noted that when the target tray is placed on the forks, the initial relative position data between the target tray and the AGV motion center can be calculated according to the first point cloud data and saved. During the transportation, the current relative position data between the target tray and the AGV motion center can be calculated according to the first point cloud data acquired in real time.

[0108] The current relative position data between the target tray and the AGV motion center is compared with the initial relative position data between the target tray and the AGV motion center. When the tray position offset difference is within the preset offset value range, it indicates that the shaking offset is small, and the tray position is within a safe range. In this case, the transfer tray position verification is successful, and the transfer tray position verification continues. When the tray position offset difference is not within the preset offset value range, it indicates that the shaking offset is large, and the tray is prone to danger. In this case, the transfer tray position verification is unsuccessful, an alarm is executed, and the AGV transportation is stopped to avoid the situation that the subsequent picking and placing of goods fail due to the accumulated errors of the tray. At the same time, the staff can be notified early for maintenance processing, so as to accurately implement the picking and placing of goods and ensure the stability of the handling operation.

[0109] In order to improve the safety of the carrying work, the error calibration controller of the present application can also set the safety protection scanning area of the fork laser radar and the vehicle body laser radar respectively, when there is an obstacle in the safety protection scanning area of the double horizontal plane radar, the AGV trolley can be controlled to stop moving, so as to avoid collision and accident, and improve the safety of the carrying work.

[0110] Correspondingly, the present application also provides a computer device, comprising a memory and a processor, the memory stores a computer program, and the processor realizes the steps of the above method when executing the computer program.

[0111] Correspondingly, the present application also provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the steps of the above method.

[0112] In summary, the present application can reduce the problem of abnormal or failed picking and placing caused by the accumulation error of the tray, effectively improve the carrying operation precision, efficiency and stability, has high overall adaptability, and can reduce the probability of manual intervention and carrying cost. At the same time, compared with the existing camera recognition method, the present application has stronger adaptability to light interference, and the automatic calibration can greatly reduce the failure rate, and further improve the overall efficiency of the warehouse system.

[0113] The above is the preferred embodiment of the present application, it should be pointed out that for ordinary skilled in the art, without departing from the principles of the present application, can make a number of improvements and refinements, these improvements and refinements also regarded as the protection scope of the present application.

Claims

1. An AGV pallet transport error calibration method, characterized by, The method comprises the following steps: acquiring first point cloud data detected by a forklift laser radar in real time and acquiring second point cloud data detected by a vehicle body laser radar in real time, wherein the first point cloud data is point cloud data of a pallet leg of a target pallet placed on a forklift, and the second point cloud data is point cloud data of a pallet leg of an auxiliary pallet at a target storage site; optimizing and adjusting AGV path data according to a path optimization verification rule, the first point cloud data and the second point cloud data, so that the AGV travels to a target site for picking and placing goods according to an optimal path; when the AGV reaches the target site for picking and placing goods, performing site coordinate verification processing according to the first point cloud data and the second point cloud data; judging whether the site coordinate verification result is a preset verification result, if yes, indicating that the site coordinate verification is successful, and executing a picking and placing work, if no, indicating that the site coordinate verification is not successful, and executing an alarm work; wherein the step of optimizing and adjusting AGV path data according to a path optimization verification rule, the first point cloud data and the second point cloud data, so that the AGV travels to a target site for picking and placing goods according to an optimal path, comprises the following steps: calculating relative position data of the target pallet and an AGV motion center according to the first point cloud data, and calculating relative position data of the auxiliary pallet and the AGV motion center according to the second point cloud data; calculating a difference value between the relative position data of the target pallet and the AGV motion center and the relative position data of the auxiliary pallet and the AGV motion center in real time, to obtain a position offset value; optimizing and adjusting current AGV path data according to the position offset value, to obtain optimal AGV path data; controlling the AGV to travel to the target site for picking and placing goods according to the optimal AGV path data; the step of performing site coordinate verification processing according to the first point cloud data and the second point cloud data when the AGV reaches the target site for picking and placing goods, comprises the following steps: calculating relative position data of the target pallet and an AGV motion center according to the first point cloud data, and calculating relative position data of the auxiliary pallet and the AGV motion center according to the second point cloud data; calculating an offset difference value between the relative position data of the target pallet and the AGV motion center and the relative position data of the auxiliary pallet and the AGV motion center; judging whether the offset difference value is in a preset site error range, if yes, indicating that the site coordinate verification is successful, if no, indicating that the site coordinate verification is not successful.

2. The AGV pallet error calibration method of claim 1, wherein, Before the AGV travels, the method further comprises the following steps: calculating a detection area of a pallet leg according to a preset pallet leg parameter; judging whether all pallet legs in the first point cloud data are in the detection area, if yes, indicating that the target pallet is correctly placed on the forklift, if no, indicating that the pallet placed on the forklift is abnormal, and executing an alarm work.

3. The AGV pallet error calibration method of claim 2, wherein, During the travel of the AGV, the method further comprises the following steps: performing a transfer pallet position verification processing according to the first point cloud data; when the transfer pallet position verification is not successful, executing an alarm work.

4. The AGV pallet error calibration method of claim 3, wherein, The step of performing the transfer tray position verification processing according to the first point cloud data comprises: When the target tray is placed on the forks, the initial relative position data between the target tray and the AGV motion center is calculated according to the first point cloud data; During transportation, the current relative position data between the target tray and the AGV motion center is calculated according to the real-time acquired first point cloud data; The difference between the current relative position data between the target tray and the AGV motion center and the initial relative position data between the target tray and the AGV motion center is calculated to obtain a tray position offset difference value; It is judged whether the tray position offset difference value is within a preset offset value range, and if not, it is indicated that the transfer tray position verification is unsuccessful.

5. An AGV pallet handling error calibration system, characterized by, The system performs the steps of the method of any one of claims 1-4 when working, which comprises an AGV vehicle, an error calibration controller, a fork laser radar, a vehicle body laser radar and a target tray, the AGV vehicle is provided with the fork laser radar below the forks, the AGV vehicle is provided with the vehicle body laser radar at the lower part, and the target tray is placed on the forks; The error calibration controller is connected with the AGV vehicle, the fork laser radar and the vehicle body laser radar respectively, and the error calibration controller comprises: An acquisition module is configured to acquire first point cloud data detected by the fork laser radar in real time and second point cloud data detected by the vehicle body laser radar in real time, wherein the first point cloud data is point cloud data of tray legs of a target tray placed on the forks, and the second point cloud data is point cloud data of tray legs of an auxiliary tray at a target storage site; A path optimization module is configured to optimize and adjust AGV path data according to a path optimization verification rule, the first point cloud data and the second point cloud data, so that the AGV vehicle travels to a target site for picking and placing goods according to an optimal path. A storage site verification module is configured to perform storage site coordinate verification processing according to the first point cloud data and the second point cloud data when the target site for picking and placing goods is reached. A storage site processing module is configured to judge whether the storage site coordinate verification result is a preset verification result, if yes, it is indicated that the storage site coordinate verification is successful, and picking and placing work is performed, and if not, it is indicated that the storage site coordinate verification is unsuccessful, and alarm work is performed.

6. The AGV pallet error calibration system of claim 5, wherein, The error calibration controller further comprises: A tray calculation module is configured to calculate a detection area of the tray legs according to preset tray leg parameters before the AGV vehicle travels; A tray confirmation module is configured to judge whether all the tray legs in the first point cloud data are in the detection area, if yes, it is indicated that the target tray is correctly placed on the forks, and if not, it is indicated that the tray placed on the forks is abnormal, and alarm work is performed; A transfer tray verification module is configured to perform transfer tray position verification processing according to the first point cloud data during the travel of the AGV vehicle. A transfer tray processing module is configured to perform alarm work when the transfer tray position verification is unsuccessful. 7.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-6 when the computer program is executed by the processor. The computer program is executed by the processor to implement the steps of the method of any one of claims 1 to 4.

8. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method of any one of claims 1 to 4.

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