CN114330974A - Robot scheduling method and device, electronic equipment and storage medium - Google Patents
Robot scheduling method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The application relates to the technical field of robot control, and discloses a robot scheduling method, a robot scheduling device, electronic equipment and a storage medium, wherein the method comprises the following steps: determining a target area of the robot according to the current task to be executed by the robot; acquiring the residual traffic resources of the target area according to the traffic resource occupation information of the target area; detecting whether the residual traffic resources meet the task execution conditions of the robot; and under the condition that the residual traffic resources meet the task execution conditions of the robot, instructing the robot to go to the target area to execute the task to be executed. The traffic resource occupation condition of a target area of the robot for executing the task is considered in advance, and the time when the robot is scheduled to start executing the task is determined according to whether the residual traffic resources meet the conditions or not, so that the problem that the robot fails to execute the task due to traffic jam in the task executing process is avoided, and the safety, integrity and robustness of the robot for executing the task under the scheduling of the unmanned support platform are improved.
Description
Technical Field
The embodiment of the application relates to the technical field of robot control, in particular to a robot scheduling method, a robot scheduling device, electronic equipment and a storage medium.
Background
With the continuous development and progress of science and technology, the robot technology also tends to mature day by day, and the robot is applied to different scenes of life to undertake different tasks, which has become the mainstream development trend. The mobile navigation function has been given more and more application scenarios as a core function of the service robot. On one hand, the problem that the robot automatically calls the elevator and automatically takes the elevator out of the elevator is solved along with the elevator control system, and the mobile robot expands the vertical movement capacity on the basis of the original plane movement function by means of the elevator control system. On the other hand, in many commercial fields, a single robot often cannot meet the requirements, and the requirements of a multi-robot working scene are more and more. For example, in a hotel, a plurality of food delivery robots are required to deliver food to different guests on the same floor or different floors at the same time; it is also possible that different types of robots work simultaneously, such as supporting cleaning robot cleaning across floors and food delivery robot delivering food across floors simultaneously in a hotel scenario.
The combination of the requirements of a multi-robot working scene and a cross-floor working scene brings the problem of robot traffic management. When a plurality of robots simultaneously execute tasks, resource competition inevitably occurs, for example, the plurality of robots all request to use limited shared resources such as elevators (only one or two elevators are generally opened for the robots in a client scene), or the robots compete for passage in a narrow corridor which can only accommodate passage of a single robot, and the like. How to solve the problems that a plurality of robots compete for shared resources such as elevators, elevator room waiting points and the like, a plurality of robots simultaneously meet on a narrow road to cause traffic jam, a plurality of robots compete for a certain interest point in different task processes, and the like, and the realization of efficient scheduling of the robots is the most urgent problem to be solved in robot application.
In order to solve the problem of robot scheduling, a plurality of robots are generally made to sequentially utilize shared traffic resources to reach destinations to execute tasks when the robots are scheduled, but although the passing order of the robots is sequenced, the plurality of robots are still prone to task conflicts and traffic resource competition during task execution, and therefore the robots are jammed during task execution or movement.
Disclosure of Invention
The embodiment of the application mainly aims to provide a robot scheduling method, a robot scheduling device, electronic equipment and a storage medium, and aims to improve the efficiency and effect of robot scheduling, avoid the problem of task execution failure caused by traffic congestion in the process of executing tasks by a robot, and improve the safety, integrity and robustness of the tasks executed by the robot under the autonomous unmanned support platform scheduling.
In order to achieve the above object, an embodiment of the present application provides a robot scheduling method, including: determining a target area of the robot according to the current task to be executed by the robot; acquiring the residual traffic resources of the target area according to the traffic resource occupation information of the target area; detecting whether the residual traffic resources meet the task execution conditions of the robot; and under the condition that the residual traffic resources meet the task execution conditions of the robot, instructing the robot to go to the target area to execute the task to be executed.
In order to achieve the above object, an embodiment of the present application further provides a robot scheduling apparatus, including: the determining module is used for determining a target area of the robot according to the current task to be executed of the robot; the acquisition module is used for acquiring the residual traffic resources of the target area according to the traffic resource occupation information of the target area; the control module is used for detecting whether the residual traffic resources meet the task execution conditions of the robot or not; and under the condition that the residual traffic resources meet the task execution conditions of the robot, instructing the robot to go to the target area to execute the task to be executed.
In order to achieve the above object, an embodiment of the present application further provides an electronic device, where the electronic device includes: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the robot scheduling method as above.
In order to achieve the above object, an embodiment of the present application further provides a computer-readable storage medium, which stores a computer program, and the computer program, when executed by a processor, implements the robot scheduling method as above.
According to the robot scheduling method provided by the embodiment of the application, in the process of executing the task by the robot, the target area of the task executed by the robot is determined, the residual traffic resources in the target area are obtained according to the resource occupation condition of the target area, and the robot is instructed to move to the target area to execute the task to be executed under the condition that the residual traffic resources can meet the task execution condition of the robot. When the robot is scheduled to execute the task, the occupation condition of traffic resources in a target area where the robot executes the task is considered in advance, and the time when the robot is scheduled to start executing the task is determined according to whether the residual traffic resources meet the conditions or not, so that the robot is prevented from starting executing the task under the condition that the residual traffic resources cannot meet the task execution conditions, the task execution process of the robot is not affected by the limitation of the traffic resources, the failure of the robot in task execution due to traffic jam is avoided, the safety, the integrity and the robustness of the robot in task execution under the autonomous unmanned support platform scheduling are improved, and the functions and the application scenes of the robot are further expanded.
Drawings
One or more embodiments are illustrated by way of example in the accompanying drawings, which correspond to the figures in which like reference numerals refer to similar elements and which are not to scale unless otherwise specified.
FIG. 1 is a flow chart of a robot scheduling method in an embodiment of the present application;
fig. 2 is a schematic structural diagram of a cloud service in an embodiment of the present application;
fig. 3 is a schematic structural diagram of a robot scheduling device in another embodiment of the present application;
fig. 4 is a schematic structural diagram of an electronic device in another embodiment of the present application.
Detailed Description
As known from the background art, in order to solve the problem of robot scheduling, a plurality of robots are generally allowed to sequentially use shared traffic resources to reach a destination to execute tasks when the robots are scheduled, but although the passing order of the robots is sequenced, the plurality of robots are still prone to task conflicts and traffic resource competition during task execution, which leads to the robot being jammed during task execution or movement. Therefore, how to improve the efficiency and effect of robot scheduling and avoid the task execution failure caused by traffic jam in the task execution is a problem which needs to be solved urgently.
In order to solve the above problem, some embodiments of the present application provide a robot scheduling method, including: determining a target area of the robot according to the current task to be executed by the robot; acquiring the residual traffic resources of the target area according to the traffic resource occupation information of the target area; detecting whether the residual traffic resources meet the task execution conditions of the robot; and under the condition that the residual traffic resources meet the task execution conditions of the robot, instructing the robot to go to the target area to execute the task to be executed.
According to the robot scheduling method provided by the embodiment of the application, in the process of executing the task by the robot, the target area of the task executed by the robot is determined, the residual traffic resources in the target area are obtained according to the resource occupation condition of the target area, and the robot is instructed to move to the target area to execute the task to be executed under the condition that the residual traffic resources can meet the task execution condition of the robot. When the robot is scheduled to execute the task, the occupation condition of traffic resources in a target area where the robot executes the task is considered in advance, and the time when the robot is scheduled to start executing the task is determined according to whether the residual traffic resources meet the conditions or not, so that the robot is prevented from starting executing the task under the condition that the residual traffic resources cannot meet the task execution conditions, the task execution process of the robot is not affected by the limitation of the traffic resources, the failure of the robot in task execution due to traffic jam is avoided, the safety, the integrity and the robustness of the robot in task execution under the autonomous unmanned support platform scheduling are improved, and the functions and the application scenes of the robot are further expanded.
To make the objects, technical solutions and advantages of the embodiments of the present application clearer, the embodiments of the present application will be described in detail below with reference to the accompanying drawings. However, it will be appreciated by those of ordinary skill in the art that in the examples of the present application, numerous technical details are set forth in order to provide a better understanding of the present application. However, the technical solution claimed in the present application can be implemented without these technical details and various changes and modifications based on the following embodiments. The following embodiments are divided for convenience of description, and should not constitute any limitation to the specific implementation manner of the present application, and the embodiments may be mutually incorporated and referred to without contradiction.
The following description will specifically describe implementation details of the robot scheduling method described in the present application with reference to specific embodiments, and the following description is only provided for facilitating understanding of the implementation details and is not necessary for implementing the present solution.
A first aspect of the embodiments of the present application provides a robot scheduling method, which is applied to a robot control system or a cloud service for performing task allocation and scheduling on a robot, where the embodiment takes the cloud service as an example for description. Flow chart of the robot scheduling method referring to fig. 1, comprising the steps of:
Specifically, after the robot is put into use, the robot is in communication connection with a cloud service which is responsible for robot scheduling, management, monitoring and information storage, and the cloud service allocates tasks to at least one of the communicatively connected robots according to factors such as the function, size and task execution capacity of the robot. After the task is distributed to one robot, the cloud service determines the target area of the robot according to the current task to be executed by the robot, so that the traffic resource information of the target area of the task executed by the robot is accurately and efficiently acquired in the subsequent scheduling process, and the efficiency of path planning and robot scheduling is improved.
Further, before the cloud service determines the target area of the robot according to the current task to be executed by the robot, the cloud service further includes: acquiring tasks distributed by the robot; splitting the tasks to generate a plurality of tasks to be executed; and acquiring the current task to be executed according to the task execution sequence and the task execution state. After the cloud service issues the tasks to the robot, the tasks distributed by the robot are split, the complex tasks are split into simple tasks, the robot is dynamically scheduled according to the split task execution sequence, and the current tasks to be executed are executed one by one. By means of task splitting, complexity of robot scheduling in the task execution is simplified, occupation of traffic resources involved in the robot scheduling process is further refined, the traffic resource utilization rate in the robot scheduling process is improved, and then the robot scheduling efficiency is improved.
In one example, a schematic diagram of the cloud service is shown in fig. 2, and includes a cloud robot system 201 and a cloud elevator control system 202. The cloud robot system 201 comprises a cloud intelligent map center, a robot task scheduling center, a traffic flow scheduling center and a robot elevator control service center. In the process of scheduling the robot to execute the task, the cloud robot system 201 issues a reasonable instruction and a task to the robot according to the self state information and the device event reported by the robot in real time through the wireless network, controls the robot to execute the task, and monitors and manages the task state during the execution of the robot and the real-time state of the robot.
The task scheduling center of the robot has the functions of distributing tasks to the robot, statically decomposing a complex task executed by the robot, and decomposing a multi-point navigation task into a plurality of single-point navigation tasks, for example, if the robot needs to reach a second floor from a first floor to execute the task, the task scheduling center decomposes the task into a first subtask reaching a waiting point from a current position, a second subtask reaching the second floor by taking a staircase, and a third subtask reaching a designated area of the second floor to execute the task. And sending a plurality of subtasks to be executed of the robot to a traffic flow control center for unified planning and management in a resource competition scene. The method includes the steps of monitoring and recording task execution conditions of the robot when the robot executes tasks, maintaining and maintaining robot task target data and task execution instances and executing data.
The cloud intelligent map center has the functions of supporting the creation of a map of a target area where each robot executes tasks, and creating and maintaining shared traffic resource information on the map. For example, in a multi-robot multi-elevator scenario, the shared traffic resources in the target areas corresponding to different robots are generally composed of different types of traffic resource groups, such as the same elevator group, the same elevator outside-waiting elevator hall group, and the same elevator inside-boarding elevator hall group. And the cloud intelligent map center creates and sets different types of traffic resource groups in the map according to the application scenes and functions. Under the scene that N robots share the same elevator, a candidate elevator resource point group comprising M standby points is arranged in an elevator room, on the basis of ensuring no space congestion, the robots are allowed to work in parallel as much as possible, and the number of the standby points can be generally set as the number of the robots.
In addition, the cloud intelligent map center can also set the traffic resource capacity according to the specific scene of the current target area, for example, the current scene is a first-floor hall, 4 common service robots can be allowed to pass and work simultaneously according to the calculation of the first-floor hall, and then the traffic resource capacity of the first-floor hall is set to be 4. The second floor is a living area with a narrow corridor, only one service type robot can be accommodated in the corridor to pass and execute tasks, and the traffic resource capacity of the second floor is set to be 1. The traffic resource capacity of each area on the map is accurately calculated, so that the robot can be conveniently and accurately scheduled according to the traffic resource capacity.
The traffic flow scheduling center has the functions of monitoring and maintaining the occupation and release conditions of the traffic resources in the map according to the traffic resource information in the map, and performing dynamic path planning on the robot under the condition of resource competition according to the occupation conditions of the traffic resources so as to avoid traffic jam. For example, in a multi-robot scenario, a task of predicting traffic flow is undertaken, and under the condition that a navigation task has traffic competition, the execution of part of robot tasks is suspended through a message mechanism until the task execution is resumed after resources are released, and the robots are enabled to queue and compete for the use of traffic resources to prevent traffic jam in a task waiting mode. When the robot carries out a complex single-point moving task, for example, the robot takes the elevator to carry out a cross-floor task, and the path of the robot is dynamically planned according to the waiting condition of the elevator room and the real-time state of the elevator, so that the elevator taking efficiency is improved. By adding the traffic flow scheduling center, the occupation of traffic resources in a target area in the task execution process of the robot is evaluated and managed, so that whether the traffic resources meet task execution conditions or not can be fully considered in the robot scheduling process, and the problems of traffic jam and task execution failure caused by improper robot scheduling are avoided as far as possible.
The robot elevator control service center has the function of supporting integration and butt joint of different cloud elevator control systems 202, and under the condition that the robot needs to take an elevator to execute a cross-floor task, the robot elevator control service center communicates with the specific cloud elevator control system 202 through a cloud docking protocol, and sends an elevator taking instruction of the robot to the cloud elevator control system 202. After receiving the elevator taking instruction of the robot, the cloud elevator control system 202 issues basic elevator control instructions such as calling, opening, closing, setting floors and the like to the terminal elevator control module through the cloud elevator control platform so as to control the operation of the elevator. Meanwhile, the robot elevator control service center can automatically acquire information such as opening and closing of the elevator door, the current floor and the running direction and report the information to the cloud server, so that the cloud robot system 201 can acquire the current running state of the elevator from the cloud server, and the robot can be dynamically dispatched. And the robots are controlled to take the elevator to go out of the elevator by combining the path planning result in the robot scheduling process, so that the elevator taking competition among the robots is avoided, and the problem of space congestion inside and outside the elevator caused by the elevator taking competition between the robots and users is solved.
The function of the cloud elevator control system 202 is to control the operation of the elevator to cooperate with the robot to execute tasks according to the received instructions, and simultaneously upload the current state information of the elevator, so that the cloud robot system 201 can perform efficient dynamic scheduling on the robot.
And 102, acquiring the residual traffic resources of the target area according to the traffic resource occupation information of the target area.
Specifically, after determining a target area for the robot to execute the task according to the current task to be executed by the robot, the cloud service calculates the current residual traffic resources of the target area according to the current traffic resource occupation information of the target area, and acquires the residual traffic resources of the target area.
Further, the traffic resource includes any one or any combination of the following: elevator resources, path resources, and area space resources. In the process of dispatching the robot, whether the occupation condition of one or more traffic resources meets the requirement of the task to be executed or not can be considered according to the actual condition, and traffic jam in the process of dispatching the robot is avoided as much as possible.
For example, the robot currently waits for a task to be executed to arrive at a landing from the current position, and the cloud service queries the occupancy of the landing point (area space resource) at the landing position of the target elevator according to the target elevator of the robot and calculates the remaining available landing points at the landing position. And under the condition that the available elevator waiting points exist, acquiring the resource occupation condition of the path from the current position to the elevator waiting position of the robot, and acquiring the residual capacity of the path.
And 103, detecting whether the residual traffic resources meet the task execution conditions of the robot, and instructing the robot to move to the target area to execute the task to be executed under the condition that the residual traffic resources meet the task execution conditions of the robot.
Specifically, the cloud service detects whether the remaining traffic resources in the target area meet the task execution conditions that need to be met when the robot executes the task in the target area before instructing the robot to go to the target area to execute the current task to be executed. Under the condition that the residual traffic resources are detected to be incapable of meeting the task execution conditions of the robot, the robot is instructed to wait in situ; and in the case of detecting that the residual traffic resources meet the task execution conditions of the robot, instructing the robot to move from the current position to the target area to execute the task to be executed.
In one example, before detecting whether the remaining traffic resources satisfy the task execution condition of the robot, the cloud service further includes: acquiring resource occupation requirements of a robot for executing tasks; detecting whether the remaining traffic resources satisfy the task execution condition of the robot, including: and under the condition that the residual traffic resources can meet the resource occupation requirement, judging that the residual traffic resources meet the task execution condition. The cloud service acquires the traffic resource occupation requirement when the robot executes the task after acquiring the residual traffic resources in the target area, and judges that the residual traffic resources can meet the task execution condition under the condition that the total amount of the residual traffic resources can meet the resource occupation requirement of the robot. For example, when the cloud service control robot a executes a cleaning task on the second floor, the traffic resource capacity occupied by the robot a when executing the task is 1, and the total traffic resource capacity on the second floor is 3. At this time, if 1 robot B occupying 1 traffic resource capacity is executing the food delivery task on the second floor and the remaining traffic resource capacity is 2 and can satisfy the resource occupation demand of the robot a, it is determined that the second floor can satisfy the task execution condition of the robot a. The cloud service instructs robot a to begin cleaning tasks in floor 2. When 3 robots occupying 1 in traffic resource capacity execute tasks simultaneously on the second floor, the remaining traffic resource capacity of the second floor is 0, and the resource occupation requirement of the robot A cannot be met, the second floor is judged to be incapable of meeting the task execution condition of the robot A, and the robot A is instructed to wait in place. The robot scheduling in the same region is controlled according to the traffic resource capacity of the target region and the resource occupation requirement of the robot, so that the time when the robot starts to execute the task is accurately controlled, traffic jam and task execution failure caused by conflict in the task execution process of the robot are avoided, the possibility of manual intervention is greatly reduced, and unmanned robot self-operation is realized.
Further, before detecting whether the remaining traffic resources satisfy the task execution condition of the robot, the cloud service further includes: acquiring the resource occupation priority of the robot; acquiring actual occupiable resources of the robot according to the resource occupancy priority and the residual traffic resources; detecting whether the remaining traffic resources satisfy the task execution condition of the robot, including: and under the condition that the actual occupiable resources can meet the resource occupation requirement, judging that the residual traffic resources meet the task execution condition. The number of the robots in the cloud service management can be multiple, and under the condition that target areas of a plurality of robots for executing tasks are overlapped, traffic resource competition can occur among the robots. In order to avoid task conflict of the robot, the cloud service calculates the current and actually occupied traffic resource capacity of the robot according to the resource occupation priority of the robot and the residual traffic resources before detecting whether the residual traffic resources meet the task execution conditions of the robot. When detecting whether the residual traffic resources meet the task execution conditions of the robot, when detecting that the capacity of the actual occupiable resources of the robot is larger than the resource occupation requirement when the robot executes the task, judging that the residual traffic resources meet the task execution conditions. The residual traffic resources are distributed according to the priority, and whether the residual traffic resources meet the task execution condition or not is judged according to the actual occupiable resources of the robots, so that the robots are reasonably scheduled to execute the tasks in the same area, and task conflicts caused by the fact that the robots cannot occupy enough traffic resources in the task execution process are avoided as much as possible.
In addition, when the actual occupiable resources are allocated according to the resource occupancy priority, the remaining traffic resources which can be actually occupied can be allocated for each robot according to different proportions according to different resource occupancy priorities, and the remaining traffic resources which can be occupied are also allocated for the robot with the higher resource occupancy priority preferentially, and the remaining traffic resources which can be occupied are not allocated for the robot with the lower priority under the condition that the remaining traffic resources which can be actually occupied by the robot with the higher priority cannot meet the resource occupancy requirement. The method for allocating the remaining traffic resources according to the resource occupation priority may be selected as needed, which is not limited in this embodiment.
Further, when determining the resource occupation priority of the robot, the cloud service determines the resource occupation priority by any one of the following factors or any combination thereof: the method comprises the steps of creating time of a task to be executed, the emergency degree of the task to be executed and the preset priority of the robot. The method has the advantages that the resource occupation priority is distributed to the robot according to the creation time of the task to be executed, the task emergency degree and the self priority of the robot, so that the emergency task can be processed preferentially while the task execution efficiency is guaranteed.
The cloud service instructs the robot to go to the target area and execute the task to be executed, and the method further comprises the following steps: and allocating traffic resources matched with the resource occupation requirements for the robot, identifying the traffic resources allocated to the robot as occupied resources, and updating the remaining occupied resources. For example, the cloud service instructs the robot to execute a transportation task from a point a to a point B, allocates traffic resources matched with resource occupation requirements to the robot when the path capacity reaching the point B can support the robot to move from the point a to the point B, identifies the traffic resources allocated to the robot as occupied resources, instructs the robot to occupy the allocated traffic resources, moves to the point B to execute the transportation task, and updates the remaining path capacity according to the resource occupation of the robot. The traffic resource capacity of the target area is managed in a resource occupation mode, the robot is prevented from entering the target area to execute tasks under the condition that the residual traffic resources in the target area are insufficient, and the possibility of task conflict in the task execution process of the robot is reduced.
Further, after instructing the robot to go to the target area to execute the task to be executed, the cloud service further includes: detecting the execution state of a task to be executed; and under the condition that the task to be executed is completely executed, identifying the traffic resources occupied by the robot as unoccupied resources, and updating the residual occupied resources. For example, in the process that the cloud service instructs the robot to execute the task from the first floor to the second floor, the robot is instructed to occupy an idle waiting point according to the waiting task of the robot, then the occupied path resource moves from the current position to the occupied waiting point, after the waiting point is reached, the completion of the task execution is judged, and the path resource occupied by the robot is released. And then updating the current task to be executed of the robot into an elevator entering task, triggering the cloud elevator control service center to initiate an elevator right of use and call an elevator, and planning a task entering the elevator from an elevator waiting point after the elevator arrives. Judging whether the robot can enter the elevator or not according to the resource occupation priority of the robot and the residual capacity of the elevator, and instructing the robot to wait in situ to continue calling the elevator under the condition that the capacity of the elevator is full or the occupied capacity of the robot cannot meet the resource occupation requirement; and under the condition that the occupied capacity of the robot meets the occupation requirement of the robot, the robot is instructed to occupy the elevator capacity meeting the requirement, and the robot enters the elevator to move to the appointed floor according to the elevator waiting sequence. After the elevator is closed, the elevator entering task is judged to be completed, the cloud elevator control module marks the elevator waiting points occupied by the robot as unoccupied elevator waiting points, the occupation of the elevator waiting points is released, and the number of the remaining elevator waiting points capable of being occupied is updated. The robot triggers an elevator leaving task after arriving at the second floor, the traffic resource dispatching center dynamically plans the elevator leaving task of the robot at a target floor, the robot is instructed to enter a waiting area of the second floor or go to a designated position to execute the task according to the path capacity and the area space capacity, after the robot leaves an elevator, the elevator task is judged to be completely executed, the occupation of the robot on the elevator capacity is released, and the elevator capacity is updated. Through the resource occupation and release modes, the elevator taking and task execution of the robot are efficiently and orderly coordinated, the task execution failure caused by task conflict in the task execution process of the robot is avoided, and the robot scheduling efficiency and robustness are improved.
In addition, it should be understood that the above steps of the various methods are divided for clarity, and the implementation may be combined into one step or split into some steps, and the steps are divided into multiple steps, so long as the same logical relationship is included in the protection scope of the present patent; it is within the scope of the patent to add insignificant modifications to the algorithms or processes or to introduce insignificant design changes to the core design without changing the algorithms or processes.
Another aspect of the embodiments of the present application relates to a robot scheduling apparatus, a schematic structural diagram of the robot scheduling apparatus is shown in fig. 3, and the robot scheduling apparatus includes:
the determining module 301 is configured to determine a target area of the robot according to a current task to be executed by the robot.
The obtaining module 302 is configured to obtain the remaining traffic resources of the target area according to the traffic resource occupation information of the target area.
The control module 303 is configured to detect whether the remaining traffic resources satisfy the task execution condition of the robot; and under the condition that the residual traffic resources meet the task execution conditions of the robot, instructing the robot to go to the target area to execute the task to be executed.
It should be understood that the present embodiment is an apparatus embodiment corresponding to the method embodiment, and the present embodiment can be implemented in cooperation with the method embodiment. The related technical details mentioned in the method embodiment are still valid in this embodiment, and are not described herein again in order to reduce repetition. Accordingly, the related art details mentioned in the present embodiment can also be applied in the method embodiment.
It should be noted that, all the modules involved in this embodiment are logic modules, and in practical application, one logic unit may be one physical unit, may also be a part of one physical unit, and may also be implemented by a combination of multiple physical units. In addition, in order to highlight the innovative part of the present application, a unit that is not so closely related to solving the technical problem proposed by the present application is not introduced in the present embodiment, but this does not indicate that there is no other unit in the present embodiment.
Another aspect of the embodiments of the present application further provides an electronic device, with reference to fig. 4, including: at least one processor 401; and a memory 402 communicatively coupled to the at least one processor 401; the memory 402 stores instructions executable by the at least one processor 401, and the instructions are executed by the at least one processor 401, so that the at least one processor 401 can execute the robot scheduling method described in any of the above method embodiments.
Where the memory 402 and the processor 401 are coupled by a bus, which may include any number of interconnected buses and bridges that couple one or more of the various circuits of the processor 401 and the memory 402 together. The bus may also connect various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface provides an interface between the bus and the transceiver. The transceiver may be one element or a plurality of elements, such as a plurality of receivers and transmitters, providing a means for communicating with various other apparatus over a transmission medium. The data processed by the processor 401 may be transmitted over a wireless medium via an antenna, which may receive the data and transmit the data to the processor 401.
The processor 401 is responsible for managing the bus and general processing and may provide various functions including timing, peripheral interfaces, voltage regulation, power management, and other control functions. And memory 402 may be used to store data used by processor 401 in performing operations.
Another aspect of the embodiments of the present application also provides a computer-readable storage medium storing a computer program. The computer program realizes the above-described method embodiments when executed by a processor.
That is, as can be understood by those skilled in the art, all or part of the steps in the method for implementing the embodiments described above may be implemented by a program instructing related hardware, where the program is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, or the like) or a processor (processor) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It will be understood by those of ordinary skill in the art that the foregoing embodiments are specific examples for carrying out the present application, and that various changes in form and details may be made therein without departing from the spirit and scope of the present application in practice.
Claims (11)
1. A robot scheduling method, comprising:
determining a target area of the robot according to a current task to be executed by the robot;
acquiring the residual traffic resources of the target area according to the traffic resource occupation information of the target area;
detecting whether the residual traffic resources meet task execution conditions of the robot;
and under the condition that the residual traffic resources meet task execution conditions of the robot, instructing the robot to go to the target area to execute the task to be executed.
2. The robot scheduling method of claim 1, further comprising, before the detecting whether the remaining traffic resources satisfy the task execution condition of the robot:
acquiring resource occupation requirements of the robot for executing tasks;
the detecting whether the remaining traffic resources meet the task execution condition of the robot includes:
and under the condition that the residual traffic resources can meet the resource occupation requirement, judging that the residual traffic resources meet the task execution condition.
3. The robot scheduling method of claim 2, further comprising, before the detecting whether the remaining traffic resources satisfy the task execution condition of the robot:
acquiring the resource occupation priority of the robot;
acquiring the actual occupiable resource of the robot according to the resource occupancy priority and the residual traffic resource;
the detecting whether the remaining traffic resources meet the task execution condition of the robot includes:
and under the condition that the actual occupiable resources can meet the resource occupancy requirement, judging that the residual traffic resources meet the task execution condition.
4. The robot scheduling method of claim 3, wherein the resource occupancy priority is determined by any one or any combination of the following factors:
the creating time of the task to be executed, the emergency degree of the task to be executed and the preset priority of the robot.
5. The robot scheduling method of claim 2, further comprising, before instructing the robot to travel to the target area to perform the task to be performed:
and allocating traffic resources matched with the resource occupation requirements for the robot, identifying the traffic resources allocated to the robot as occupied resources, and updating the residual available resources.
6. The robot scheduling method of claim 5, further comprising, after instructing the robot to travel to the target area to perform the task to be performed:
detecting the execution state of the task to be executed;
and under the condition that the task to be executed is completely executed, identifying the traffic resources occupied by the robot as unoccupied resources, and updating the residual occupied resources.
7. The robot scheduling method according to claim 1, further comprising, before determining the target area of the robot according to the current task to be performed by the robot:
acquiring tasks distributed by the robot;
splitting the task to generate a plurality of tasks to be executed;
and acquiring the current task to be executed according to the task execution sequence and the task execution state.
8. The robot scheduling method of any one of claims 1 to 7, wherein the traffic resource comprises any one or any combination of: elevator resources, path resources, and area space resources.
9. A robot scheduling apparatus, comprising:
the determining module is used for determining a target area of the robot according to the current task to be executed of the robot;
the acquisition module is used for acquiring the residual traffic resources of the target area according to the traffic resource occupation information of the target area;
the control module is used for detecting whether the residual traffic resources meet task execution conditions of the robot or not; and under the condition that the residual traffic resources meet task execution conditions of the robot, instructing the robot to go to the target area to execute the task to be executed.
10. An electronic device, comprising:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a robot scheduling method according to any one of claims 1 to 8.
11. A computer-readable storage medium, storing a computer program, wherein the computer program, when executed by a processor, implements the robot scheduling method of any of claims 1 to 8.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116330296A (en) * | 2023-04-11 | 2023-06-27 | 深圳市普渡科技有限公司 | Multi-stage door passing method, apparatus, robot, and storage medium |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116330296A (en) * | 2023-04-11 | 2023-06-27 | 深圳市普渡科技有限公司 | Multi-stage door passing method, apparatus, robot, and storage medium |
| CN116330296B (en) * | 2023-04-11 | 2024-04-09 | 深圳市普渡科技有限公司 | Multi-stage door passing method, apparatus, robot, and storage medium |
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