CN116047920A - Parameter optimization method and system for high-precision butt joint of multiple robots and multiple wharfs - Google Patents
Parameter optimization method and system for high-precision butt joint of multiple robots and multiple wharfs Download PDFInfo
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Abstract
The invention discloses a parameter optimization method and a system for high-precision butt joint of multiple robots and multiple wharfs, wherein the method comprises the following steps: inputting the ID of the mobile robot, the ID of the wharf, the control result P and the feedback result generated after each docking, inputting a designed parameter optimization model, outputting the sensor external parameter errors PL of all the optimized mobile robots and the calibration errors PT of all wharf target points, and meeting the following conditions: according to the sensor external parameter errors PL of all the mobile robots and the calibration errors PT of the wharf target points, the calculated real control result Pr corresponding to the obtained control result P is in the precision interval [ P1, P2], and all the feedback results are successful. According to the invention, the sensor external parameters of each mobile robot and the target point calibration result of each docking wharf are optimized and calculated, so that the docking positioning precision is improved.
Description
Technical Field
The invention relates to the technical field of docking of mobile robots, in particular to a parameter optimization method and system for high-precision docking of multiple robots and multiple wharfs.
Background
When the mobile robot is applied to the photovoltaic industry, the photovoltaic panels in each process need to be subjected to machine station circulation. The material conveying device is specifically realized in such a way that materials are conveyed to a conveying belt arranged on a robot through the conveying belt of each machine wharf, the robot moves to the machine wharf of the next process, and the materials are conveyed to the machine of the next process. Each robot can realize the material loading and unloading actions among all the machines, and any robot can be assigned by a task system to realize the current required material circulation action. Similar applications also result in production line flows in the 3C industry, the automotive industry, various intelligent manufacturing industries, etc., production line to warehouse flows, etc.
Because of the wide application of mobile robots and the demands of users for high efficiency, the requirements for high-precision docking of mobile robots are increasingly high, while the sensor precision is limited, and in order to realize the requirements for high-precision docking of mobile robots with limited sensor precision, the rest of errors need to be compressed.
The existing butt joint positioning algorithm of the mobile robot is mainly focused on aspects of improving the sensor data precision to acquire more real sensing data, improving the sensing positioning precision through multi-sensor data fusion and the like. However, improving the accuracy of sensor data necessarily increases the cost of components; the adoption of multi-sensor fusion also increases the material cost of the mobile robot, and simultaneously increases the requirement for calculation force, and the material cost of a processor can also increase.
At present, no related method for improving the docking accuracy by optimizing a large amount of docking data and acquiring a more reasonable parameter value is available.
Disclosure of Invention
First, the technical problem to be solved
In view of the above-mentioned drawbacks and shortcomings of the prior art, the present invention provides a parameter optimization method and system for high-precision docking of multiple robots and multiple wharfs, which solves the technical problem that the cost of the existing docking positioning algorithm of mobile robots is high by improving the data precision of sensors or adopting multi-sensor fusion to improve the docking precision.
(II) technical scheme
In order to achieve the above purpose, the main technical scheme adopted by the invention comprises the following steps:
in a first aspect, an embodiment of the present invention provides a parameter optimization method for high-precision docking of multiple robots and multiple wharfs, including the following steps:
receiving a corresponding control result P generated after each butt joint of the mobile robot and a feedback result of the executing mechanism, wherein the feedback result comprises success or failure;
taking the ID of the mobile robot, the ID of the wharf, the control result P and the feedback result as information of each docking task, inputting a designed parameter optimization model, and outputting the optimized sensor external parameter errors PL of all the mobile robots and the calibration errors PT of all the wharf target points, wherein the optimized sensor external parameter errors PL of all the mobile robots and the calibration errors PT of all the wharf target points meet the following conditions:
according to the sensor external parameter error PL and the calibration error PT of the wharf target point, the calculated real control result Pr corresponding to the obtained control result P is in the precision interval [ P1, P2], and all feedback results are successful.
The precision interval [ p1, p2] refers to the requirement of the docking precision of the mobile robot when the docking system is designed. For example, the robot belt and the machine belt are abutted, and the left-right deviation of the two belts is required to be not more than 5mm. The interval is thus given according to the actual project, and if the control result is within the interval after the optimization is completed (the positioning error is eliminated), the feedback result must be successful.
According to the parameter optimization method for high-precision butt joint of the multiple robots and the multiple wharfs, which is provided by the embodiment of the invention, data fusion is not needed for the multiple sensors, and the precision of the sensors is not needed to be improved, so that the control parameters can be optimized on the basis of the existing equipment and sensors to improve the butt joint precision, and the success rate of butt joint positioning can be remarkably improved.
Optionally, the parameter optimization model is designed by the following steps:
acquiring historical data:
collecting historical information of multiple docking tasks, including: the mobile robot ID, the wharf ID, a corresponding control result P generated after the mobile robot is butted each time in a historical period of time and a feedback result of an executing mechanism, wherein the feedback result comprises success or failure; the corresponding different sensor external parameter errors PL and the corresponding different wharf target point calibration errors PT and the corresponding real control results Pr of the control results P;
taking information of each docking task as input, taking sensor external parameter errors PL of all mobile robots and calibration errors PT of all wharf target points as output, and designing a parameter optimization model; the model is optimized in such a way that all feedback results are successful when the output real control result Pr is within the range of the precision interval [ p1, p2 ].
According to the embodiment of the invention, the factory calibration requirement of the sensor external parameters can be reduced, only one low-precision external parameter value is required to be calibrated, and the parameter optimization model can be updated through online operation data for optimization (in general, a good optimization result cannot be generated through one butt joint task, and a certain amount of history data of the butt joint tasks and feedback results need to be accumulated, for example, at least ten times, and the effect is better as the amount is larger, so that better optimization parameters can be obtained). On the other hand, the precision requirement of the deployment of the site station points is reduced, and as the actual actuating mechanism of the wharf cannot be used as a sensor to sense an observation object, in the high-precision butt joint process, the sensor needs to sense the characteristics of the station points, and the characteristics can be the original code heads or the manual auxiliary posting; the relative pose relation between the station characteristics and the actuating mechanism is error, and the accuracy error is difficult to manually determine, and even though the special tooling is relied on, the error can only be compressed to the mm level. By the method, only one low-precision wharf target point is required to be calibrated, and the parameter optimization model can be updated through online operation data for optimization.
Optionally, calibrating the sensor external parameters and the wharf target points by adopting the optimized sensor external parameter errors PL of all the mobile robots and the calibration errors PT of all the wharf target points;
when executing the butt joint task, if the number of failed feedback results received in a set period exceeds a number threshold; the statistical feedback result is the robot ID and the dock ID with highest failure frequency, and corresponding sensor alarm information or dock alarm information is generated; for informing the staff to check whether the mobile robot and the sensor are malfunctioning or whether the quay is changed.
In a second aspect, an embodiment of the present invention provides a parameter optimization system for high-precision docking of multiple robots and multiple docks, including:
the server is used for receiving a corresponding control result P generated after each butt joint of the mobile robot and a feedback result of the executing mechanism, wherein the feedback result comprises success or failure; the method is also used for taking the ID of the mobile robot, the ID of the wharf, the control result P and the feedback result as information of each docking task, inputting a designed parameter optimization model, outputting the optimized sensor external parameter errors PL of all the mobile robots and the calibration errors PT of all wharf target points, and meeting the conditions of the optimized sensor external parameter errors PL of all the mobile robots and the calibration errors PT of all the wharf target points: according to the sensor external parameter error PL and the calibration error PT of the wharf target point, the calculated real control result Pr corresponding to the obtained control result P is in the precision interval [ P1, P2], and all feedback results are successful;
the mobile robot is used for receiving the docking instruction from the server, executing docking with the target point, taking the error between the mobile robot and the target point, which is measured by the self-positioning device and the sensing device, as a control result P, and taking the successful or failed execution result of the execution mechanism as a feedback result, and sending the feedback result to the server.
According to the parameter optimization system for high-precision docking of multiple robots and multiple wharfs, provided by the embodiment of the invention, through the cooperation of the server and the mobile robot, the success rate of docking positioning can be remarkably improved by collecting the sensor external parameter of the mobile robot and the calibration result of each docking wharf target point through collecting the sensor external parameter of the mobile robot and the corresponding control result P and the successful or failed feedback result of the executing mechanism and designing a parameter optimization model.
Optionally, the parameter optimization model includes: a database for storing the following history data: the mobile robot ID, the wharf ID, a corresponding control result P generated after the mobile robot is butted each time in a historical period of time and a feedback result of an executing mechanism, wherein the feedback result comprises success or failure; the corresponding different sensor external parameter errors PL and the corresponding different wharf target point calibration errors PT and the corresponding real control results Pr of the control results P;
the parameter optimization model is designed based on historical data in a database, information of each docking task is taken as input, sensor external parameter errors PL of all mobile robots and calibration errors PT of all wharf target points are taken as output, and the parameter optimization model is designed; the model is optimized in such a way that all feedback results are successful when the output real control result Pr is within the range of the precision interval [ p1, p2 ].
Optionally, calibrating the sensor external parameters and the wharf target points by adopting the optimized sensor external parameter errors PL of all the mobile robots and the calibration errors PT of all the wharf target points;
the server is also used for when the number of the failed feedback results received exceeds a threshold value during the execution of the docking task; the statistical feedback result is the robot ID and the dock ID with highest failure frequency, and corresponding sensor alarm information or dock alarm information is generated; for informing the staff to check whether the mobile robot and the sensor are malfunctioning or whether the quay is changed.
In a third aspect, embodiments of the present invention provide a computer system comprising a memory and a processor; a memory for storing a computer program; and the processor is used for realizing the parameter optimization method of the high-precision butt joint of the multi-robot multi-wharf when executing the computer program.
(III) beneficial effects
The beneficial effects of the invention are as follows: according to the parameter optimization method and system for high-precision docking of multiple robots and multiple wharfs, the sensor external parameters of each mobile robot and the target point calibration result of each docking wharf are optimized and calculated through the docking feedback result, namely the success/failure signals fed back by the execution mechanism, so that the docking positioning precision is improved.
The factory calibration requirement of the sensor external parameters can be reduced, only one low-precision external parameter value needs to be calibrated, and the parameter optimization model can be updated through online operation data for optimization.
The accuracy requirement of the deployment of the site station point can be reduced, the actual actuating mechanism of the wharf cannot be a sensor to sense an observation object, in the high-accuracy butt joint process, the sensor needs to sense the station point characteristics (the characteristics can be original code heads or manually assisted, and the relative pose relation of the station characteristics and the actuating mechanism is error, and the accuracy error is difficult to manually determine, even though the accuracy error depends on a special tool, the accuracy error can only be compressed to the mm level. By the method, only one low-precision wharf target point is required to be calibrated, and the parameter optimization model can be updated through online operation data for optimization.
Drawings
FIG. 1 is a flow chart of a parameter optimization method for high-precision docking of multiple robots and multiple docks according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a parameter optimization system for high-precision docking of multiple robots and multiple docks according to an embodiment of the present invention.
Detailed Description
The invention will be better explained by the following detailed description of the embodiments with reference to the drawings.
According to the parameter optimization method and system for high-precision docking of multiple robots and multiple wharfs, the sensor external parameters of each mobile robot and the target point calibration result of each docking wharf are optimized and calculated through the docking feedback result, namely the success/failure signals fed back by the executing mechanism, so that the docking positioning precision is improved. The factory calibration requirement of the sensor external parameters and the deployment precision requirement of the site work site can be reduced, only one low-precision initial value is required to be calibrated, and the parameter optimization model can be updated through online operation data for optimization.
In order that the above-described aspects may be better understood, exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
The wharf provided by the embodiment of the invention is any docking target point, including wharf, machine, goods shelf, pallet and other stations.
The robot or the mobile robot in the embodiment of the invention is any executing mechanism capable of completing the butt joint task, including a mobile robot, a mobile docking vehicle, a transporting or conveying mechanism, a mechanical arm, other executing mechanisms capable of controlling the butt joint, and the like.
Example 1
Referring to fig. 1, an embodiment of the invention is a parameter optimization method for high-precision docking of multiple robots and multiple wharfs, comprising the following steps:
s1: receiving a corresponding control result P generated after each butt joint of the mobile robot and a feedback result of the executing mechanism, wherein the feedback result comprises success or failure;
s2: taking the ID of the mobile robot, the ID of the wharf, the control result P and the feedback result as information of each docking task, inputting a designed parameter optimization model, and outputting the optimized sensor external parameter errors PL of all the mobile robots and the calibration errors PT of all the wharf target points, wherein the optimized sensor external parameter errors PL of all the mobile robots and the calibration errors PT of all the wharf target points meet the following conditions:
according to the sensor external parameter errors PL of all mobile robots and the calibration errors PT of all wharf target points, the calculated real control result Pr corresponding to the obtained control result P is in the precision interval [ P1, P2], and all feedback results are successful
The precision interval [ p1, p2] refers to the requirement of the docking precision of the mobile robot when the docking system is designed. For example, the robot belt and the machine belt are abutted, and the left-right deviation of the two belts is required to be not more than 5mm. The interval is thus given according to the actual project, and if the control result is within the interval after the optimization is completed (the positioning error is eliminated), the feedback result must be successful.
When in implementation, the parameter optimization model can be designed by the following steps:
acquiring historical data:
collecting historical information of multiple docking tasks, including: the mobile robot ID, the wharf ID, a corresponding control result P generated after the mobile robot is butted each time in a historical period of time and a feedback result of an executing mechanism, wherein the feedback result comprises success or failure; the corresponding different sensor external parameter errors PL and the corresponding different wharf target point calibration errors PT and the corresponding real control results Pr of the control results P;
taking information of each docking task as input, taking sensor external parameter errors PL of all mobile robots and calibration errors PT of all wharf target points as output, and designing a parameter optimization model; the optimization mode (optimization direction) of the model is that when the output real control result Pr is within the range of the precision interval [ p1, p2], all feedback results are successful.
In the embodiment, a parameter optimization model is designed through an offline optimization method, and an optimization result is produced through a large number of parameter collection and is imported into a mobile robot database. In the implementation, the data can be accumulated continuously by an online optimization method, optimization calculation is performed continuously, and the optimization result is updated to the database continuously. The online optimization can be performed in a server, and the normal operation of the mobile robot is not affected. The parameter optimization model can be designed by adopting modes such as machine learning, neural network, mathematical function, fitting and the like, and is not limited to a fixed modeling mode.
Therefore, the embodiment of the invention can realize that the data fusion of multiple sensors is not needed, and the accuracy of the sensors is not needed to be improved, so that the control parameters can be optimized to improve the docking accuracy on the basis of the existing equipment and sensors, and the success rate of docking positioning can be obviously improved.
The parameter optimization method for high-precision butt joint of the multiple robots and the multiple wharfs can reduce the factory calibration requirement of the sensor external parameters, only one low-precision external parameter value needs to be calibrated, and the parameter optimization model can be updated through online operation data for optimization. On the other hand, the accuracy requirement of on-site station point deployment is reduced, because the actual actuating mechanism of the wharf cannot be a sensor to sense an observation object, in the high-accuracy butt joint process, the sensor needs to sense station point characteristics (the characteristics can be original code heads or manually assisted, and the relative pose relation of the station characteristics and the actuating mechanism is error, and the accuracy error is difficult to manually determine, even though the accuracy error depends on a special tool, the error can only be compressed to the mm level. By the method, only one low-precision wharf target point is required to be calibrated, and the parameter optimization model can be updated through online operation data for optimization.
When the method is implemented, the sensor external parameters and the wharf target points are calibrated by adopting the optimized sensor external parameter errors PL of all the mobile robots and the calibration errors PT of all the wharf target points;
when the docking task is executed, if the number of failed feedback results received in a set period exceeds a number threshold (in the embodiment, the number threshold is set according to different situations on the site, for example, the failure rate exceeds 5%); the statistical feedback result is the robot ID and the dock ID with highest failure frequency, and corresponding sensor alarm information or dock alarm information is generated; for informing the staff to check whether the mobile robot and the sensor are malfunctioning or whether the quay is changed.
The method can realize the on-line monitoring of the conditions of the sensor and the wharf of the mobile robot, and can timely identify the specific sensor or the wharf and give an alarm if the running result does not accord with the original external parameter calibration result.
Example two
Referring to fig. 2, an embodiment of the present invention is a parameter optimization system for high-precision docking of multiple robots and multiple docks corresponding to the method of the first embodiment, including a server and multiple mobile robots, where the server sends a command (or a path command includes docking) for docking or path to each mobile robot, and instructs each mobile robot to dock, that is, to dock a target point of the mobile robot.
The server is used for receiving a corresponding control result P generated after each butt joint of the mobile robot and a feedback result of the executing mechanism, wherein the feedback result comprises success or failure; the method is also used for taking the ID of the mobile robot, the ID of the wharf, the control result P and the feedback result as information of each docking task, inputting a designed parameter optimization model, outputting the optimized sensor external parameter errors PL of all the mobile robots and the calibration errors PT of all wharf target points, and meeting the conditions of the optimized sensor external parameter errors PL of all the mobile robots and the calibration errors PT of all the wharf target points: according to the sensor external parameter error PL and the calibration error PT of the wharf target point, the calculated real control result Pr corresponding to the obtained control result P is in the precision interval [ P1, P2], and all feedback results are successful;
the mobile robot is used for receiving the docking instruction from the server, executing docking with the target point, taking the error between the mobile robot and the target point, which is measured by the self-positioning device and the sensing device, as a control result P, and taking the successful or failed execution result of the execution mechanism as a feedback result, and sending the feedback result to the server.
Wherein, the parameter optimization model may include:
a database for storing the following history data: the mobile robot ID, the wharf ID, a corresponding control result P generated after the mobile robot is butted each time in a historical period of time and a feedback result of an executing mechanism, wherein the feedback result comprises success or failure; the corresponding different sensor external parameter errors PL and the corresponding different wharf target point calibration errors PT and the corresponding real control results Pr of the control results P;
the parameter optimization model is designed based on historical data in a database, information of each docking task is taken as input, sensor external parameter errors PL of all mobile robots and calibration errors PT of all wharf target points are taken as output, and the parameter optimization model is designed; the optimization mode (optimization direction) of the model is that when the output real control result Pr is within the range of the precision interval [ p1, p2], all feedback results are successful.
According to the parameter optimization system for high-precision docking of multiple robots and multiple wharfs, provided by the embodiment of the invention, through the cooperation of the server and the mobile robot, the success rate of docking positioning can be remarkably improved by collecting the sensor external parameter of the mobile robot and the calibration result of each docking wharf target point through collecting the sensor external parameter of the mobile robot and the corresponding control result P and the successful or failed feedback result of the executing mechanism and designing a parameter optimization model.
In the implementation, in order to monitor the conditions of the sensor and the wharf of the mobile robot on line, if the operation result does not accord with the original external parameter calibration result, the specific sensor or wharf can be identified in time, and an alarm is sent out.
Further, calibrating the sensor external parameters and the wharf target point by adopting the optimized sensor external parameter error PL and the calibration error PT of the wharf target point;
the server is also used for when the number of the failed feedback results received exceeds a threshold value during the execution of the docking task; the statistical feedback result is the robot ID and the dock ID with highest failure frequency, and corresponding sensor alarm information or dock alarm information is generated; for informing the staff to check whether the mobile robot and the sensor are malfunctioning or whether the quay is changed.
Since the system/device described in the foregoing embodiments of the present invention is a system/device used for implementing the method of the foregoing embodiments of the present invention, those skilled in the art will be able to understand the specific structure and modification of the system/device based on the method of the foregoing embodiments of the present invention, and thus will not be described in detail herein. All systems/devices used in the methods of the above embodiments of the present invention are within the scope of the present invention.
Example III
The embodiment of the invention provides a computer system, which comprises a memory and a processor; a memory for storing a computer program; and a processor for implementing the parameter optimization method of high-precision docking of the multi-robot multi-wharf of the above embodiment when executing the computer program.
According to the parameter optimization method and system for high-precision docking of multiple robots and multiple wharfs, the sensor external parameters of each mobile robot and the target point calibration result of each docking wharf are optimized and calculated through the docking feedback result, namely the success/failure signals fed back by the execution mechanism, so that the docking positioning precision is improved. The factory calibration requirement of sensor external parameters and the precision requirement of on-site station point deployment can be reduced. Only one sensor external parameter and a low-precision wharf target point need to be calibrated, and the parameter optimization model can be updated through online operation data for optimization.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions.
It should be noted that the word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the terms first, second, third, etc. are for convenience of description only and do not denote any order. These terms may be understood as part of the component name.
Furthermore, it should be noted that in the description of the present specification, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to a specific feature, structure, material, or characteristic described in connection with the embodiment or example being included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art upon learning the basic inventive concepts. It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention.
Claims (8)
1. The parameter optimization method for high-precision butt joint of the multiple robots and the multiple wharfs is characterized by comprising the following steps of:
receiving a corresponding control result P generated after each butt joint of the mobile robot and a feedback result of an executing mechanism, wherein the feedback result comprises success or failure;
taking the ID of the mobile robot, the ID of the wharf, the control result P and the feedback result as information of each docking task, inputting a designed parameter optimization model, and outputting the optimized sensor external parameter errors PL of all the mobile robots and the calibration errors PT of all the wharf target points, wherein the optimized sensor external parameter errors PL of all the mobile robots and the calibration errors PT of all the wharf target points meet the following conditions:
according to the sensor external parameter errors PL of all the mobile robots and the calibration errors PT of all the wharf target points, the calculated real control result Pr corresponding to the obtained control result P is in the precision interval [ P1, P2], and all the feedback results are successful.
2. The parameter optimization method for high-precision docking of multiple robots and multiple wharfs according to claim 1, wherein: the parameter optimization model is obtained through the following steps:
acquiring historical data:
collecting historical information of multiple docking tasks, including: the method comprises the steps that a mobile robot ID, a wharf ID, a corresponding control result P generated after the mobile robot is in butt joint for each time in a historical period of time and a feedback result of an executing mechanism are generated, wherein the feedback result comprises success or failure; the corresponding different sensor external parameter errors PL and the corresponding different wharf target point calibration errors PT and the corresponding real control results Pr of the control results P;
taking information of each docking task as input, taking sensor external parameter errors PL of all mobile robots and calibration errors PT of all wharf target points as output, and designing a parameter optimization model; the model is optimized in such a way that all feedback results are successful when the output real control result Pr is within the range of the precision interval [ p1, p2 ].
3. The parameter optimization method for high-precision docking of multiple robots and multiple wharfs according to claim 1 or 2, wherein: the method further comprises the steps of:
calibrating the sensor external parameters and the wharf target points by adopting the optimized sensor external parameter errors PL of all the mobile robots and the calibration errors PT of all the wharf target points;
when executing the butt joint task, if the number of failed feedback results received in a set period exceeds a number threshold; the statistical feedback result is the robot ID and the dock ID with highest failure frequency, and corresponding sensor alarm information or dock alarm information is generated; for informing the staff to check whether the mobile robot and the sensor are malfunctioning or whether the quay is changed.
4. The parameter optimization method for high-precision docking of multiple robots and multiple wharfs according to claim 2, wherein: the precision intervals [ p1, p2] are set according to the requirement of the docking system on the docking precision of the mobile robot.
5. A parameter optimization system for high precision docking of multiple robots to multiple docks, comprising:
the server is used for receiving a corresponding control result P generated after each butt joint of the mobile robot and a feedback result of the executing mechanism, wherein the feedback result comprises success or failure; the method is also used for taking the ID of the mobile robot, the ID of the wharf, the control result P and the feedback result as information of each docking task, inputting a designed parameter optimization model, and outputting the optimized sensor external parameter errors PL of all the mobile robots and the calibration errors PT of all wharf target points, wherein the optimized sensor external parameter errors PL of all the mobile robots and the calibration errors PT of all the wharf target points meet the following conditions:
according to the sensor external parameter errors PL of all mobile robots and the calibration errors PT of all wharf target points, the calculated real control result Pr corresponding to the obtained control result P is in the precision interval [ P1, P2], and all feedback results are successful;
the mobile robot is used for receiving the docking instruction from the server, executing docking with the target point, taking the error between the mobile robot and the target point, which is measured by the self-positioning device and the sensing device, as a control result P, and taking the successful or failed execution result of the execution mechanism as a feedback result, and sending the feedback result to the server.
6. The multi-robot multi-dock high-precision docking parameter optimization system of claim 5, wherein: the parameter optimization model comprises:
a database for storing the following history data: the method comprises the steps that a mobile robot ID, a wharf ID, a corresponding control result P generated after the mobile robot is in butt joint for each time in a historical period of time and a feedback result of an executing mechanism are generated, wherein the feedback result comprises success or failure; the corresponding different sensor external parameter errors PL and the corresponding different wharf target point calibration errors PT and the corresponding real control results Pr of the control results P;
the parameter optimization model is designed based on historical data in the database, information of each docking task is taken as input, sensor external parameter errors PL of all mobile robots and calibration errors PT of all wharf target points are taken as output, and the parameter optimization model is designed; the model is optimized in such a way that all feedback results are successful when the output real control result Pr is within the range of the precision interval [ p1, p2 ].
7. The parameter optimization system of high precision docking of multiple robots and multiple docks of claim 5 or 6, wherein:
calibrating the sensor external parameters and the wharf target points by adopting the optimized sensor external parameter errors PL of all the mobile robots and the calibration errors PT of all the wharf target points;
the server is further used for when the number of the received feedback results is more than a threshold value when the received feedback results are that the number of the failures exceeds the threshold value during the execution of the docking task; the statistical feedback result is the robot ID and the dock ID with highest failure frequency, and corresponding sensor alarm information or dock alarm information is generated; for informing the staff to check whether the mobile robot and the sensor are malfunctioning or whether the quay is changed.
8. A computer system, characterized in that: comprising a memory and a processor; the memory is used for storing a computer program; the processor for implementing a parameter optimization method of high precision docking of multiple robots and multiple docks according to any of the claims 1-4 when executing the computer program.
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