CN116795087A - Scheduling method, scheduling system, electronic equipment and storage medium of autonomous mobile robot - Google Patents
Scheduling method, scheduling system, electronic equipment and storage medium of autonomous mobile robot Download PDFInfo
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Abstract
The application provides a dispatching method, a dispatching system, electronic equipment and a storage medium of an autonomous mobile robot, and relates to the technical field of robots. A dispatching method of autonomous mobile robots is applied to a plurality of workplaces where the robots work cooperatively, and comprises the following steps: acquiring a map of the workplace, and dividing a plurality of subareas in the map; calculating the congestion factor of each subarea; determining at least one subarea as a congestion key point according to the congestion factor; and carrying out scheduling control on the traffic of a plurality of robots at the congestion key points based on the road information of the congestion key points. According to the embodiment of the application, the problem of road blockage and difficult traffic caused by space constraint when multiple robots work cooperatively can be solved.
Description
Technical Field
The application relates to the technical field of robots, in particular to a scheduling method, a scheduling system, electronic equipment and a storage medium of an autonomous mobile robot.
Background
Along with the development of science and technology, the autonomous mobile robot is widely applied to operations such as picking, sorting and carrying in storage, and can replace a manual cart, reduce manual invalid walking, maximize human efficiency, liberate human resources and improve accuracy.
In a scene of cooperative work of multiple robots, each robot performs path planning and movement according to received tasks, and performs avoidance among the robots by means of a single obstacle avoidance function; this often leaves the robot with an impending road blockage in a situation where the work environment space is relatively tight.
Disclosure of Invention
The application provides a dispatching method, a dispatching system, electronic equipment and a storage medium of an autonomous mobile robot, wherein a working place of the robot is divided into a plurality of subareas, congestion key points are arranged, road traffic of the congestion key points is controlled according to rules, so that the problem that the robot is not smooth in passing under a relatively limited working scene is solved, and the working efficiency is improved.
According to an aspect of the present application, there is provided a scheduling method of an autonomous mobile robot applied to a workplace where a plurality of robots work cooperatively, comprising: acquiring a map of the workplace, and dividing a plurality of subareas in the map; calculating the congestion factor of each subarea; determining at least one subarea as a congestion key point according to the congestion factor; and carrying out scheduling control on the traffic of a plurality of robots at the congestion key points based on the road information of the congestion key points.
According to some embodiments, the plurality of sub-regions are distributed throughout a robot-travelable region of the map and are in communication with one another.
According to some embodiments, the congestion factor is an average value of total time for a plurality of the robots to pass through the sub-areas respectively in a predetermined time.
According to some embodiments, the total time for the plurality of robots to respectively pass through the sub-areas comprises: time to normally pass the subregion; passive deceleration and/or time to park while passing through the sub-area.
According to some embodiments, determining at least one of the sub-regions as a congestion keypoint according to the congestion factor comprises: calculating a median or average value of the congestion factors of all the subregions in the plurality of subregions; and for each subarea, if the ratio of the congestion factor of the subarea to the median or average value of the congestion factors of all the subareas is greater than a preset threshold value, determining the subarea as the congestion key point.
According to some embodiments, if the plurality of sub-regions within the preset range of the map are respectively determined as the congestion key points, the congestion key points corresponding to the plurality of sub-regions may be combined into at least one congestion key point.
According to some embodiments, the scheduling control of traffic of the congestion key point includes: allowing only a predetermined number of said robots to be scheduled to pass said congestion keypoints; only a predetermined number of said robots are allowed to be dispatched into roads passing by said congestion key point; only the robots with the same scheduling travelling direction are allowed to enter the road containing the congestion key point.
According to some embodiments, only a predetermined number of the robots are allowed to be scheduled to pass the congestion keypoints, including: and controlling a preset number of robots to pass through the congestion key point, and not scheduling the robots to enter the congestion key point before the preset number of robots all leave the congestion key point.
According to some embodiments, only a predetermined number of said robots are allowed to be scheduled into roads passing said congestion keypoints, comprising: controlling a predetermined number of robots to enter the congestion key point, and not scheduling robots to enter the road before the predetermined number of robots all leave the road passing through the congestion key point.
According to some embodiments, only allowing the robots with the same dispatch travel direction to enter a road containing the congestion keypoints comprises: and if the road passes through the congestion key point and the robot in the road travels, only the robot in the same direction as the robot is scheduled to enter the road until the existing robot and the scheduled robot all leave the road.
According to an aspect of the present application, there is provided a scheduling system of an autonomous mobile robot, including: the acquisition module is used for acquiring time and/or position information of each robot in the travelling process in a workplace where a plurality of robots work cooperatively; the storage module is used for storing time and/or position information in the travelling process of each robot and a map of the workplace of the robot; the planning module is used for dividing a plurality of subareas in the map according to the map; the calculation module is used for calculating the congestion factor of each subarea according to the time and/or position information in the advancing process of each robot and determining at least one congestion key point based on the congestion factors of all subareas; and the scheduling module is used for sending scheduling instructions to the robots so as to schedule and control the traffic of the robots at the congestion key points according to the map.
According to some embodiments, the time and/or position information during travel of each of the robots comprises: time and/or position information reported by each robot to the dispatching system; and/or the scheduling system monitors the acquired time and/or position information through video.
According to some embodiments, the time and/or location information reported by each robot to the scheduling system includes: the total time for each robot to pass through each sub-area; positional information of travel of each robot between different ones of the sub-areas.
According to some embodiments, the scheduling system obtains time and/or location information by video monitoring, including: the total time for a plurality of robots to pass through each subarea respectively; positional information of the plurality of robots traveling between the different sub-areas.
According to an aspect of the present application, there is provided an autonomously movable robot including: a vehicle body; the camera is arranged on the vehicle body and used for acquiring time and/or position information in the running process of the robot; the communication device is used for reporting time and/or position information in the running process of the robot to the scheduling system and receiving a scheduling instruction of the scheduling system; a memory; a processor; and the driving device drives the vehicle body to travel.
According to an aspect of the present application, there is provided an electronic apparatus including: one or more processors; a storage means for storing one or more programs; the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the methods as described above.
According to an aspect of the present application, there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method as described above.
According to the embodiment of the application, the congestion key points are set and the traffic of the congestion key points is managed, so that the congestion problem of a plurality of robots in the same point set is effectively reduced, and the working efficiency of the robots is improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application as claimed.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present application.
Fig. 1 shows a scheduling architecture diagram of an autonomous mobile robot according to an example embodiment of the application.
Fig. 2 shows a flow chart of a scheduling method of an autonomous mobile robot according to an exemplary embodiment of the present application.
Fig. 3 shows a schematic diagram of the relationship of congestion keypoints to sub-areas according to an example embodiment of the application.
Fig. 4 shows a schematic diagram of travel of an autonomous mobile robot in a workplace according to an example embodiment of the application.
Fig. 5 illustrates a travel time and location information acquisition schematic of an autonomous mobile robot according to an exemplary embodiment of the present application.
Fig. 6 shows a block diagram of an autonomous mobile robot dispatch system in accordance with an exemplary embodiment of the present application.
Fig. 7 shows a block diagram of an electronic device according to an example embodiment of the application.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments can be embodied in many forms and should not be construed as 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 concept of the example embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar parts, and thus a repetitive description thereof will be omitted.
The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the disclosed aspects may be practiced without one or more of the specific details, or with other methods, components, materials, devices, operations, etc. In these instances, well-known structures, methods, devices, implementations, materials, or operations are not shown or described in detail.
The flow diagrams depicted in the figures are exemplary only, and do not necessarily include all of the elements and operations/steps, nor must they be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the order of actual execution may be changed according to actual situations.
The terms first, second and the like in the description and in the claims and in the above-described figures are used for distinguishing between different objects and not necessarily for describing a sequential or chronological order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements but may include other steps or elements not listed or inherent to such process, method, article, or apparatus.
The application provides a dispatching method, a dispatching system, electronic equipment and a storage medium of an autonomous mobile robot, which can effectively solve the problem that road blockage which cannot be solved by only relying on the obstacle avoidance function of a single robot cannot pass under a relatively limited working environment scene by setting a congestion key point and controlling traffic of the congestion key point.
A scheduling method, system, electronic device, and storage medium of an autonomous mobile robot according to an embodiment of the present application will be described in detail with reference to the accompanying drawings.
Fig. 1 shows a scheduling architecture diagram of an autonomous mobile robot according to an example embodiment of the application.
As shown in fig. 1, the dispatch hierarchy of autonomous mobile robots includes a dispatch system 101, a video surveillance system 102, robots 103, and a network 104.
It should be understood that the number of systems, networks, and robots in fig. 1 are merely illustrative. Any number of systems, networks, and robots may be provided as desired.
The dispatching system 101 interacts with the robot 103 in real time through the network 104 to acquire the travel time of the robot and/or the position information in the map of the robot workplace, and is connected with the video monitoring system 102 through the network 104 to acquire the travel time and/or the position information of all robots in the whole map.
According to some embodiments, the scheduling system 101 divides the workplace map into a plurality of sub-areas and calculates the congestion factor of each sub-area from the travel time and location information of the robot.
Further, the scheduling system 101 determines a congestion key point according to the congestion factor of each sub-area, and sends a scheduling instruction to the robot 103 according to a rule to control the robot traffic at the congestion key point.
The video monitoring system 102 acquires travel time and/or position information of all robots in the whole map through cameras distributed in the robot workplace, and sends the travel time and/or position information to the scheduling system 101.
The robot 103 obtains its own travel time and/or real-time position information in the map through a camera mounted on the vehicle body, sends the travel time and/or real-time position information to the dispatching system 101, receives a dispatching instruction issued by the dispatching system, and travels in the map according to the dispatching instruction.
The network 104 may include various connection types, such as fiber optic cables, wireless communication links, etc., that may be used as a medium to provide a network communication link between the dispatch system 101, the video surveillance system 102, and the robot 103.
Fig. 2 shows a flow chart of a scheduling method of an autonomous mobile robot according to an exemplary embodiment of the present application.
As shown in fig. 2, at S201, a map of a workplace is acquired, and a plurality of sub-areas are divided in the map.
Generally, a map of a workplace includes place distribution information and road information, and may be stored in a server (e.g., a server where a scheduling system is located) or a robot that performs cooperative work in the workplace, whereby map information may be acquired by the server or the robot and a plurality of roads on which the robot may travel may be laid in advance on the map.
Further, the map of the workplace may be updated according to a change in the layout of the workplace and the traveling movement of the robot such that the map information acquired by the server or the robot is the latest updated map information.
According to some embodiments, the map of the workplace is divided into a plurality of sub-areas identical to the shape of the robot body circumscribed polygon according to the shape of the body circumscribed polygon of the autonomous mobile robot.
Alternatively, the shape of the sub-region may be changed according to the requirement of the accuracy of the robot scheduling control, and if the scheduling control with high accuracy is required, the shape of the sub-region may be the same as the shape of the circumscribed polygon of the robot body.
In addition, the area of each sub-area is larger than the area of the circumscribed polygon of the robot body, each sub-area is communicated with each other, and a plurality of sub-areas are distributed in the movable area of the robot in the map.
At S203, a congestion factor for each sub-area is calculated.
According to some embodiments, the congestion factor n of a subarea is an average value of times of a plurality of robots in a map passing through the subarea within a predetermined time, wherein the predetermined time is an empirical parameter and can be set according to actual requirements.
For example, 10 robots in total pass through one sub-area in the map within a predetermined time, and the passing time is n respectively 1 、n 2 、......n 10 The congestion factor n= (n) for this sub-area 1 +n 2 +......+n 10 )/10。
Generally, the time for each robot to pass through the subarea only comprises normal passing time and passive deceleration and/or parking time due to automatic obstacle avoidance in the process of passing through the subarea, and does not comprise active parking control time due to tasks.
According to some embodiments, the robot is controlled to travel from one sub-area in the map, and when leaving this sub-area and reaching an adjacent sub-area, the robot is considered to pass through this sub-area.
Further, time and position information of each robot in the running process are obtained through a camera and a video monitoring system which are arranged on the vehicle body.
At S205, at least one sub-area is determined to be a congestion key point according to the congestion factor.
And calculating the median or average value m of the congestion factors of all the subareas according to the congestion factors of each subarea.
If the congestion factor of a sub-area is n and the ratio of n to m is greater than a predetermined threshold, the sub-area is the congestion key point.
The setting of the preset threshold is adjusted according to the completion time of all tasks of the robot and the average completion time of a single task.
Generally, since tasks completed by the robot in a period of time are concurrent, the completion time of all tasks and the average completion time of a single task are not in a direct proportion, i.e. the completion time of all tasks is short, the average completion time of a single task is not necessarily short, and therefore, the predetermined threshold value can be adjusted according to different project requirements.
For example, if the project to which the task belongs pursues the maximum throughput, the shorter the completion time of all tasks is, the more reasonable the threshold is; if the item to which the task belongs pursues timeliness, the shorter the average completion time of a single task is, the more reasonable the threshold value is.
According to some embodiments, there are a plurality of sub-areas determined as congestion keypoints within a preset range, respectively, and then the congestion keypoints corresponding to the plurality of sub-areas within the preset range are combined into one congestion keypoint.
For example, in a map of a workplace, a rectangular area having the number of subareas of 3×3 is set, and as shown in fig. 3, subareas 210 to 218, and roads, shelves, and the like (not shown in the figure) passing through each subarea are included in this area.
Wherein the sub-areas 215 and 218 are determined as congestion keypoints 215 and 218, respectively, according to their own congestion factors.
The congestion keypoints 215 and 218 are located in the preset rectangular area as shown in fig. 3, so that the congestion keypoints 215 and 218 can be combined into a congestion keypoint 219, and the scheduling control of the robot in the preset rectangular area is facilitated while the congestion keypoints are reduced.
In S207, traffic of the plurality of robots at the congestion key point is scheduled and controlled based on the road information of the congestion key point.
Typically, at least one road in the map of the workplace is routed past a congestion key point.
According to some embodiments, the scheduling system is only allowed to schedule a predetermined number of robots to pass the congestion keypoints until the predetermined number of robots all leave the congestion keypoints. That is to say,
and controlling the preset number of robots to pass through the congestion key point along the scheduling path, and enabling the scheduling system to not schedule robots beyond the preset number to enter the congestion key point before the preset number of robots leave the congestion key point.
According to some embodiments, the scheduling system is only allowed to schedule a predetermined number of robots to enter the roads passing through the congestion keypoint area until the predetermined number of robots all leave the roads passing through the congestion keypoint. That is to say,
and controlling the preset number of robots to enter the road passing through the congestion key point along the dispatching path, and before the preset number of robots all leave the road passing through the congestion key point, the dispatching system does not dispatch the robots beyond the preset number to enter the road passing through the congestion key point.
According to some embodiments, only robots with the same direction of travel are allowed to be scheduled by the scheduling system to enter the road containing the congestion key point until all existing robots and scheduled robots in the road containing the congestion key point leave the road containing the congestion key point. That is to say,
if one road of the map passes through the congestion key point and the existing robot in the road is travelling, the dispatching system only dispatches the robot in the same direction as the robot to enter the road until the robot and the dispatched robot all leave the road.
Fig. 4 shows a schematic diagram of travel of an autonomous mobile robot in a workplace according to an example embodiment of the application.
As shown in fig. 4, the workplace 30 includes a warehouse, a large warehouse supermarket shelf area, etc., including shelves 301, 302, and 303, roads 310, 311, 312, and 313, autonomous mobile robots 320, 321, and 322, congestion keypoints 330 and 331 determined according to congestion factors of respective sub-areas in the workplace 30.
Road 310 is the road between shelves 301 and 302, passing by congestion key point 330; road 311 is the road between shelves 302 and 303, passing by congestion key point 331.
The scheduling system performs scheduling control of travel of robots 320, 321, and 322 on roads 310 and 311.
Robot 320 enters road 310 along path 340 from road 312 and robot 321 enters road 311 along path 341 from road 313.
Embodiment one:
the dispatch system controls the robot 320 to travel on the link 310 and through the congestion keypoint 330, and before the robot 320 leaves the congestion keypoint 330, the robot 322 receives instructions from the dispatch system to perform a deceleration and/or parking operation without passing through the congestion keypoint 330.
Likewise, the dispatch system controls the robot 321 to travel on the road 311 and through the congestion keypoint 331, and before the robot 321 leaves the congestion keypoint 331, the robot 322 receives instructions from the dispatch system to perform operations of slowing down and/or stopping without passing through the congestion keypoint 331.
Embodiment two:
the dispatch system controls the robot 320 to travel on the link 310. As the link 310 passes by the congestion keypoints 330, the robot 322 receives instructions from the dispatch system to perform a deceleration and/or parking operation without entering the link 310 before the robot 320 leaves the link 310.
Similarly, the dispatch system controls the robot 321 to travel on the link 311, as the link 311 passes by the congestion key point 331, the robot 322 receives the instruction of the dispatch system before the robot 321 leaves the link 311, performs the operations of decelerating and/or stopping, and does not enter the link 311.
Embodiment III:
the dispatch system controls robots 320 to travel on roads 310. As roads 310 pass by congestion keypoints 330, robots 322 receive dispatch system instructions and may enter roads 310 to travel in the same direction as robots 320.
The dispatching system controls the robot 321 to travel on the road 311, and as the road 311 passes through the congestion key point 331, the robot 322 receives the instruction of the dispatching system and does not enter the road 311 until the robot 321 leaves the road 311 (as the traveling directions of the robots 321 and 322 on the road 311 are opposite to each other); after robot 321 leaves road 311, robot 322 may enter road 311.
Fig. 5 illustrates a travel time and location information acquisition schematic of an autonomous mobile robot according to an exemplary embodiment of the present application.
As shown in fig. 5, the autonomous mobile robot 410 travels in a road 430 passing in the left-right direction, and the road 430 passes through the sub-areas 420, 421 and 422, and a plurality of video monitoring cameras 440 are installed at one side of the road 430.
Generally, when dividing sub-areas in a map of a robot workplace, a scheduling system forms a planar coordinate system on the map with respect to each sub-area, i.e., coordinates of boundaries of each sub-area have been determined.
For example, the left boundary of sub-region 420 has an abscissa x 1 The abscissa of the right boundary of sub-region 422 is x 2 As shown in fig. 5.
According to some embodiments, the robot 410 is traveling if the interval of the subareas is delta x Can be arranged at fixed distance delta according to a preset rule x The position of the robot 410 in the coordinate system is reported to the dispatch system (i.e., as the robot passes the sub-region boundary).
Further, the robot 410 may report the time interval directly to the dispatching system according to its real-time position and vehicle speed in the coordinate system, so as to obtain the passing time.
The video monitoring cameras 440 may be disposed at one side or both sides of the road 430, and used for real-time identification and tracking of the robot 410, and transmitting the travel information of the robot 410 obtained by the identification and tracking to the video monitoring system, and the video monitoring system calculates the time of the robot 410 passing through a specific area (such as a congestion key point) according to the travel information of the robot 410, and sends the time to the dispatching system.
Fig. 6 shows a block diagram of an autonomous mobile robot dispatch system in accordance with an exemplary embodiment of the present application.
As shown in fig. 6, the autonomous mobile robot scheduling system includes an acquisition module 501, a storage module 503, a planning module 505, a calculation module 507, and a scheduling module 509.
The acquisition module 501 is configured to acquire time and/or position information during traveling of each robot in a workplace where multiple robots cooperate.
According to some embodiments, the time and/or position information of each robot in the travelling process includes total time of each robot passing through each sub-area and position information of each robot travelling between different sub-areas, and the time and/or position information can be acquired through a camera installed on a body of each robot and sent to a dispatching system through a communication device, and also can be acquired through a video monitoring system to the dispatching system.
Further, the time and/or position information acquired by the scheduling system through the video monitoring system comprises total time for a plurality of robots in the map to respectively pass through each sub-area and position information for the plurality of robots to travel between different sub-areas.
The storage module 503 is used to store time and/or location information during travel of each robot, and a map of the workplace of the robot.
The map of the workplace may be pre-stored in the server and/or each robot and updated in real time according to changes in the workplace layout and the travel movements of the robots.
The planning module 505 is configured to divide a plurality of sub-areas in a map according to the map.
The shape of the subareas can be divided according to the accuracy requirement of the dispatching control of the robot, and if the dispatching control with high accuracy is required, the shape of the subareas can be the same as the shape of the circumscribed polygon of the robot body; if no requirement is made on accuracy, the method can be divided into any shape.
According to an embodiment of the application, the area of each sub-area is slightly larger than the area of the circumscribed polygon of the robot body.
Each sub-area in the map communicates with each other and fills the workplace where the robot can travel.
The calculating module 507 is configured to calculate a congestion factor of each sub-area according to time and/or position information during the traveling process of each robot, and determine at least one congestion key point based on the congestion factor of each sub-area.
The congestion key points in the map are determined by calculating the ratio of the congestion factor of the subarea obtained by the plurality of robots through the average value of the total time of one subarea in the map to the median or average value of the congestion factors of all subareas in the predetermined time, and at least one congestion key point in the map.
The scheduling module 509 is configured to send a scheduling instruction to a plurality of robots, so as to schedule and control the traffic of the robots at the congestion key points according to the map.
The robot receives a dispatching instruction issued by a dispatching system through a communication device, and controls a driving device to complete normal running, speed reduction or parking and other operations when running on a road passing through a congestion key point according to the dispatching instruction.
Fig. 7 shows a block diagram of an electronic device according to an example embodiment of the application.
As shown in fig. 7, the electronic device 600 is only an example, and should not be construed as limiting the functionality and scope of use of the embodiments of the present application.
As shown in fig. 7, the electronic device 600 is in the form of a general purpose computing device. Components of electronic device 600 may include, but are not limited to: at least one processing unit 610, at least one memory unit 620, a bus 630 connecting the different system components (including the memory unit 620 and the processing unit 610), a display unit 640, etc. In which a storage unit stores program codes that can be executed by the processing unit 610, so that the processing unit 610 performs the methods according to various exemplary embodiments of the present application described in the present specification. For example, the processing unit 610 may perform the method as shown in fig. 2.
The storage unit 620 may include readable media in the form of volatile storage units, such as Random Access Memory (RAM) 6201 and/or cache memory unit 6202, and may further include Read Only Memory (ROM) 6203.
The storage unit 620 may also include a program/utility 6204 having a set (at least one) of program modules 6205, such program modules 6205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment.
Bus 630 may be a local bus representing one or more of several types of bus structures including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or using any of a variety of bus architectures.
The electronic device 600 may also communicate with one or more external devices 700 (e.g., keyboard, pointing device, bluetooth device, etc.), one or more devices that enable a user to interact with the electronic device 600, and/or any device (e.g., router, modem, etc.) that enables the electronic device 600 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 650. Also, electronic device 600 may communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the Internet, through network adapter 660. The network adapter 660 may communicate with other modules of the electronic device 600 over the bus 630. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with electronic device 600, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.
From the description of the embodiments above, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or may be implemented in software in combination with the necessary hardware. The technical solution according to the embodiments of the present application may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, and includes several instructions to cause a computing device (may be a personal computer, a server, a mobile terminal, or a network device, etc.) to perform the method according to the embodiments of the present application.
The software product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection having one or more wires, a portable disk, a hard disk, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The computer readable storage medium may include a data signal propagated in baseband or as part of a carrier wave, with readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A readable storage medium may also be any readable medium that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., connected via the Internet using an Internet service provider).
The computer-readable medium carries one or more programs which, when executed by one of the devices, cause the computer-readable medium to perform the aforementioned functions.
Those skilled in the art will appreciate that the modules may be distributed throughout several devices as described in the embodiments, and that corresponding variations may be implemented in one or more devices that are unique to the embodiments. The modules of the above embodiments may be combined into one module, or may be further split into a plurality of sub-modules.
According to some embodiments of the application, the technical scheme of the application effectively solves the problem that the robot is easy to cause road blockage and cannot pass under a scene with relatively limited space by setting the congestion key points in the map of the working place of the autonomous mobile robot and controlling the road traffic of the congestion key points.
The foregoing detailed description of the embodiments of the application has been presented only to assist in understanding the method and its core ideas of the application. Meanwhile, based on the idea of the present application, those skilled in the art can make changes or modifications on the specific embodiments and application scope of the present application, which belong to the protection scope of the present application. In view of the foregoing, this description should not be construed as limiting the application.
Claims (17)
1. The dispatching method of the autonomous mobile robot is applied to a plurality of workplaces where the robots work cooperatively and is characterized by comprising the following steps:
acquiring a map of the workplace, and dividing a plurality of subareas in the map;
calculating the congestion factor of each subarea;
determining at least one subarea as a congestion key point according to the congestion factor;
and carrying out scheduling control on the traffic of a plurality of robots at the congestion key points based on the road information of the congestion key points.
2. The method of claim 1, wherein the plurality of sub-areas are spread over a robot-travelable area of the map and are in communication with one another.
3. The method of claim 1, wherein the congestion factor is an average of total times that a plurality of the robots respectively pass through the sub-areas within a predetermined time.
4. A method according to claim 3, wherein the total time for a plurality of said robots to individually pass through said sub-areas comprises:
time to normally pass the subregion;
passive deceleration and/or time to park while passing through the sub-area.
5. The method of claim 1, wherein determining at least one of the sub-regions as a congestion keypoint based on the congestion factor comprises:
calculating a median or average value of the congestion factors of all the subregions in the plurality of subregions;
and for each subarea, if the ratio of the congestion factor of the subarea to the median or average value of the congestion factors of all the subareas is greater than a preset threshold value, determining the subarea as the congestion key point.
6. The method as recited in claim 1, further comprising:
if the plurality of subareas within the preset range of the map are respectively determined to be the congestion key points, the congestion key points corresponding to the plurality of subareas can be combined to be at least one congestion key point.
7. The method of claim 1, wherein scheduling control of traffic of the congestion keypoints comprises:
allowing only a predetermined number of said robots to be scheduled to pass said congestion keypoints;
only a predetermined number of said robots are allowed to be dispatched into roads passing by said congestion key point;
only the robots with the same scheduling travelling direction are allowed to enter the road containing the congestion key point.
8. The method of claim 7, wherein only allowing a predetermined number of the robots to pass the congestion keypoints comprises:
and controlling a preset number of robots to pass through the congestion key point, and not scheduling the robots to enter the congestion key point before the preset number of robots all leave the congestion key point.
9. The method of claim 7, wherein only allowing a predetermined number of the robots to be dispatched into the route past the congestion keypoints comprises:
controlling a predetermined number of robots to enter the congestion key point, and not scheduling robots to enter the road before the predetermined number of robots all leave the road passing through the congestion key point.
10. The method of claim 7, wherein only allowing the robots having the same dispatch travel direction to enter a link containing the congestion keypoints comprises:
and if the road passes through the congestion key point and the robot in the road travels, only the robot in the same direction as the robot is scheduled to enter the road until the existing robot and the scheduled robot all leave the road.
11. A dispatch system for an autonomous mobile robot, comprising:
the acquisition module is used for acquiring time and/or position information of each robot in the travelling process in a workplace where a plurality of robots work cooperatively;
the storage module is used for storing time and/or position information in the travelling process of each robot and a map of the workplace of the robot;
a planning module for dividing a plurality of subareas in the map;
the calculation module is used for calculating the congestion factor of each subarea according to the time and/or position information in the advancing process of each robot and determining at least one congestion key point based on the congestion factor of each subarea;
and the scheduling module is used for sending scheduling instructions to the robots so as to schedule and control the traffic of the robots at the congestion key points according to the map.
12. The scheduling system of claim 11, wherein the time and/or location information during travel of each robot comprises:
time and/or position information reported by each robot to the dispatching system; and/or
The scheduling system monitors the acquired time and/or position information through videos.
13. The scheduling system of claim 12, wherein the time and/or location information reported by each robot to the scheduling system comprises:
the total time for each robot to pass through each sub-area;
positional information of travel of each robot between different ones of the sub-areas.
14. Scheduling system according to claim 12, characterized in that the scheduling system acquires time and/or location information by video monitoring, comprising:
the total time for a plurality of robots to pass through each subarea respectively;
positional information of the plurality of robots traveling between the different sub-areas.
15. An autonomously movable robot, comprising:
a vehicle body;
the camera is arranged on the vehicle body and used for acquiring time and/or position information in the running process of the robot;
communication device, reporting time and/or position information of the robot in the travelling process to the dispatching system according to any one of claims 11-14, and receiving dispatching instructions of the dispatching system;
a memory;
a processor;
and the driving device drives the vehicle body to travel.
16. An electronic device, comprising:
one or more processors;
a storage means for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of any of claims 1-10.
17. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the method according to any of claims 1-10.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210251216.XA CN116795087A (en) | 2022-03-15 | 2022-03-15 | Scheduling method, scheduling system, electronic equipment and storage medium of autonomous mobile robot |
| PCT/CN2023/079999 WO2023174096A1 (en) | 2022-03-15 | 2023-03-07 | Method and system for dispatching autonomous mobile robots, and electronic device and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN202210251216.XA CN116795087A (en) | 2022-03-15 | 2022-03-15 | Scheduling method, scheduling system, electronic equipment and storage medium of autonomous mobile robot |
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| CN202210251216.XA Pending CN116795087A (en) | 2022-03-15 | 2022-03-15 | Scheduling method, scheduling system, electronic equipment and storage medium of autonomous mobile robot |
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| CN110231040B (en) * | 2018-03-05 | 2022-11-08 | 北京京东乾石科技有限公司 | Path planning method and device |
| CN110442121B (en) * | 2018-05-03 | 2022-08-12 | 北京京东乾石科技有限公司 | Method and device for selecting transport vehicle route |
| CN110967012B (en) * | 2018-09-30 | 2022-11-08 | 北京京东振世信息技术有限公司 | Path planning method and system, computer system and computer readable storage medium |
| CN108897330A (en) * | 2018-10-15 | 2018-11-27 | 河北工业大学 | A kind of logistics center's transfer robot paths planning method based on traffic congestion control |
| KR102280798B1 (en) * | 2019-06-18 | 2021-07-22 | 엘지전자 주식회사 | Cart robot and system for controlling robot |
| JP7476727B2 (en) * | 2020-08-26 | 2024-05-01 | トヨタ自動車株式会社 | Autonomous mobile robot control system, control method thereof, control program thereof, and autonomous mobile robot control device |
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