CN115145233B - Multi-stage small-granularity movement scheduling control method, device and equipment for robot - Google Patents

Abstract

The invention discloses a multi-level small-grained motion scheduling control method, device and equipment for a robot. The motion scheduling tasks of a robot are sequentially divided into tasks, action groups and actions from top to bottom. Each task includes an action group. An action group includes several actions, and an action is the smallest executable unit that can be split into tasks; the preemptive high-priority priority scheduling method HPF is used in motion scheduling control, and high-priority tasks are periodically queried in the current task. If the detected high priority task is higher than the currently running task, save the parameters and status of the current task to execute the high priority task and execute the action group under the task. If the queried high priority task is lower than or equal to the currently running task, then continue to execute the currently running task, sleep for a set time after the currently running task ends, and then re-query the priority task. The invention supports the scheduling of complex motion scenes.

Description

A multi-level small-grained motion scheduling control method, device and equipment for a robot

technical field

The invention belongs to a task scheduling control method, in particular to a robot multi-level small granularity motion scheduling control method, device and equipment.

Background technique

Task scheduling is the focus and difficulty of orbital robot motion control. The current task scheduling mainly includes the switching of manual tasks and inspection tasks and the task pool for managing multiple tasks. This method can only solve the robot motion control of simple motion scenes. In the face of various scenarios such as low battery charging, fixed-point triggering actions, etc., the motion scheduling cannot be satisfied. Under this simple scheduling mechanism, it can only be solved by special processing, which leads to serious code coupling.

The robot motion scheduling method in complex scenes solves the robot motion scheduling in complex scenes through task priority, time slice, action group and tree data structure, improves code reusability, and greatly reduces code coupling. The existing scheduling algorithm is relatively complicated, and the code is not easy to read. Tasks are managed through a tree structure. In order to ensure the consistency of multi-threading, the granularity of locking is relatively large.

Contents of the invention

Aiming at the problems existing in the prior art, the present invention provides a robot multi-level small-grained motion scheduling control method, device and equipment, which supports the scheduling of complex motion scenes, and does not increase the complexity and coupling of code while solving task scheduling sex.

In order to solve the above technical problems, the present invention is achieved through the following technical solutions:

A multi-level small-grained motion scheduling control method for a robot, comprising:

The robot's motion scheduling tasks are divided into tasks, action groups and actions from top to bottom. Each task includes action groups, and each action group includes several actions. Actions are the smallest executable units that can be split into tasks. ;

The preemptive high-priority priority scheduling method HPF is used in motion scheduling control, and the high-priority task is periodically queried in the current task. If the queried high-priority task is higher than the currently running task, the parameters and parameters of the current task are saved. state, to execute the high priority task, and execute the action group under the task, if the queried high priority task is lower than or equal to the currently running task, continue to execute the currently running task, the currently running task Sleep for a set time after the task ends, and then re-query the priority task.

Further, when inquiring about high-priority tasks, if the current highest-level task is a manual control task, tasks with the same priority will be scheduled according to the deprivation-style last-first-served order, and all other child tasks under the manual control task will be cleared at the same time. Task, execute the current latest subtask.

Further, when inquiring about high-priority tasks, if the current highest-level task is a non-manual control task, tasks with the same priority are scheduled in the order of first-come-first-served, and then searched according to the depth left query method of the tree data structure. Find the task with the highest priority.

Further, when executing each action group, each action in the action group is executed according to the first-in-first-out principle, as follows:

Query whether the task to which the action group belongs is interrupted. If there is no interruption, the current action will be executed from the beginning of the action list index of the action group, and the next action will be queried at the same time; The status is set to execute successfully;

Try to execute the next action queried, and the number of attempts is not more than 3. If the attempt is successful, the current task status will be set as executing. If there is no response after 3 attempts, it will be judged as a blocking action. Set the action status to execution failure;

Returns the current task after traversing the action list of the action group.

Furthermore, after each task is executed, the task will be deleted from the task bucket. After an action group in the task is executed, the action group will be deleted from the task. The action group is the task switching to save the task running scene The smallest unit of granularity.

A multi-level small-grained motion scheduling control device for a robot, comprising:

The motion scheduling task division module is used to divide the robot's motion scheduling tasks into tasks, action groups and actions from top to bottom. Each task includes action groups, and each action group includes several actions. Actions are tasks The smallest executable unit that can be split;

The task query module is used for motion scheduling control and uses the preemptive high-priority priority scheduling method HPF to periodically query high-priority tasks in the current task. If the queried high-priority task is higher than the currently running task, then Save the parameters and status of the current task to execute the high-priority task and the action group under the task. If the queried high-priority task is lower than or equal to the currently running task, continue to execute the currently running task task, the currently running task sleeps for a set time after the end, and then re-queries the priority task.

Further, the task query module is also used for inquiring about high priority tasks, if the current highest level task is a non-manual control task, tasks of the same priority will be scheduled according to the first-come-first-served order, and then according to the tree data The structure's deep left query method to find the highest priority task.

Further, the task query module is also used for inquiring about high priority tasks, if the current highest level task is a non-manual control task, tasks of the same priority will be scheduled according to the first-come-first-served order, and then according to the tree data The structure's deep left query method to find the highest priority task.

A device comprising a memory, a processor, and a computer program stored in the memory and operable on the processor, when the processor executes the computer program, a multi-level small-grained motion scheduling control of a robot is realized method steps.

A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of a multi-level small-grained motion scheduling control method for a robot are realized.

Compared with the prior art, the present invention has at least the following beneficial effects:

(1) The present invention supports the scheduling of complex motion scenes, and does not increase the complexity and coupling of the code while solving task scheduling;

(2) The present invention has wide versatility. The present invention only needs to care about the division of action groups and action tasks, and does not care about the business itself, and realizes the decoupling from the motion business;

(3) The scheduling response of the present invention is fast, and the time slice is at the millisecond level;

(4) The granularity of the present invention is smaller, the action is used as the minimum scheduling unit, and the cost of scheduling is smaller.

In order to make the above-mentioned objects, features and advantages of the present invention more comprehensible, preferred embodiments will be described in detail below together with the accompanying drawings.

Description of drawings

In order to more clearly illustrate the technical solutions in the specific embodiments of the present invention, the drawings that need to be used in the description of the specific embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are some embodiments of the present invention , for those skilled in the art, other drawings can also be obtained according to these drawings on the premise of not paying creative work.

Fig. 1 is a task organization chart of the present invention;

Fig. 2 is a schematic diagram of the task scheduling strategy of the present invention;

Fig. 3 is a schematic diagram of a task flow diagram of querying the highest priority in the present invention;

Fig. 4 is a flowchart of action execution within an action group in the present invention.

Detailed ways

In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of them. the embodiment. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

As shown in Figures 1 and 2, a multi-level small-grained motion scheduling control method for a robot of the present invention divides the robot's motion scheduling tasks into tasks, action groups, and actions from top to bottom, and each task includes Action group, each action group includes several actions, the action is the smallest executable unit that can be divided into tasks; the preemptive high priority priority scheduling method HPF is used in the motion scheduling control, that is, the priority is periodically queried in the current task Priority task, if the queried high-priority task is higher than the currently running task, save the parameters and status of the current task to execute the high-priority task, and execute the action group under the task, if the queried If the high-priority task is lower than or equal to the currently running task, continue to execute the currently running task, sleep for a period of time, such as 200ms, after the currently running task ends, and then query the priority task again. For example, an action group is a set of actions that can output results (such as inspection to a certain point), and a task is a sequential task composed of a set of action groups (such as an inspection task).

As shown in Figure 3, when querying high-priority tasks, if the current highest-level task is a manual control task, tasks with the same priority will be scheduled according to the order of deprivation-based service, and all tasks under the manual control task will be cleared at the same time. For other subtasks, execute the current latest subtask.

When querying high-priority tasks, if the current highest-level task is a non-manual control task, among tasks of the same priority, follow the first-come-first-serve scheduling order, and then use the deep left query method of the tree data structure to find the priority highest task.

As shown in Figure 4, when executing each action group, each action in the action group is executed according to the principle of first-in first-out, as follows:

Query whether the task to which the action group belongs is interrupted. If there is no interruption, the current action will be executed from the beginning of the action list index of the action group, and the next action will be queried at the same time; The status is set to execute successfully;

Try to execute the next action queried, and the number of attempts is not more than 3 times. If the attempt is successful, the current task status will be set as being executed. If there is no response after three attempts, it will be judged as a blocking action, and the The action status is set to execution failure;

Returns the current task after traversing the action list of the action group.

After each task is executed, the task will be deleted from the task bucket. After an action group in the task is executed, the action group will be deleted from the task. The action group is the minimum granularity for task switching to save the running scene of the task unit.

The present invention also provides a multi-level small-grained motion scheduling control device for a robot, which is used to realize a multi-level small-granularity motion scheduling control method for a robot of the present invention, including:

The motion scheduling task division module is used to divide the robot's motion scheduling tasks into tasks, action groups and actions from top to bottom. Each task includes action groups, and each action group includes several actions. Actions are tasks The smallest executable unit that can be split;

The task query module is used for motion scheduling control and uses the preemptive high-priority priority scheduling method HPF to periodically query high-priority tasks in the current task. If the queried high-priority task is higher than the currently running task, then Save the parameters and status of the current task to execute the high-priority task and the action group under the task. If the queried high-priority task is lower than or equal to the currently running task, continue to execute the currently running task task, the currently running task sleeps for a set time after the end, and then re-queries the priority task.

The task query module is also used to query high-priority tasks. If the current highest-level task is a non-manual control task, tasks with the same priority will be scheduled in the order of first-come-first-served, and then search left according to the depth of the tree data structure method to find the task with the highest priority.

The task query module is also used to query high-priority tasks. If the current highest-level task is a non-manual control task, tasks with the same priority will be scheduled in the order of first-come-first-served, and then search left according to the depth of the tree data structure method to find the task with the highest priority.

In one embodiment of the present invention, a computer device is provided, the computer device includes a processor and a memory, the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the computer The program instructions stored in the storage medium. The processor may be a central processing unit (Central Processing Unit, CPU), or other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable GateArray, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc., which are the computing core and control core of the terminal, which are suitable for implementing one or more instructions, specifically for Load and execute one or more instructions to realize the corresponding method flow or corresponding functions; the processor described in the embodiment of the present invention can be used for the operation of a multi-level small-grained motion scheduling control method for a robot.

In one embodiment of the present invention, if a multi-level small-grained motion scheduling control method for a robot is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention realizes all or part of the processes in the methods of the above embodiments, and can also be completed by instructing related hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer When the program is executed by the processor, the steps in the above-mentioned various method embodiments can be realized. Wherein, the computer program includes computer program code, and the computer program code may be in the form of source code, object code, executable file or some intermediate form. Computer-readable storage media includes both volatile and non-permanent, removable and non-removable media by any method or technology for storage of information. Information may be computer readable instructions, data structures, modules of a program, or other data.

The computer storage medium can be any available medium or data storage device that can be accessed by a computer, including but not limited to magnetic storage (such as floppy disk, hard disk, magnetic tape, magneto-optical disk (MO), etc.), optical storage (such as CD, DVD, BD, HVD, etc.), and semiconductor memory (such as ROM, EPROM, EEPROM, non-volatile memory (NANDFLASH), solid state disk (SSD)) and the like.

Those skilled in the art should understand that the embodiments of the present application may be provided as methods, systems, or computer program products. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

The present application is described with reference to flowcharts and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present application. It should be understood that each procedure and/or block in the flowchart and/or block diagram, and a combination of procedures and/or blocks in the flowchart and/or block diagram can be realized by computer program instructions. These computer program instructions may be provided to a general purpose computer, special purpose computer, embedded processor, or processor of other programmable data processing equipment to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing equipment produce a An apparatus for realizing the functions specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to operate in a specific manner, such that the instructions stored in the computer-readable memory produce an article of manufacture comprising instruction means, the instructions The device realizes the function specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions can also be loaded onto a computer or other programmable data processing device, causing a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process, thereby The instructions provide steps for implementing the functions specified in the flow chart or blocks of the flowchart and/or the block or blocks of the block diagrams.

Finally, it should be noted that: the above-described embodiments are only specific implementations of the present invention, used to illustrate the technical solutions of the present invention, rather than limiting them, and the scope of protection of the present invention is not limited thereto, although referring to the foregoing The embodiment has described the present invention in detail, and those of ordinary skill in the art should understand that any person familiar with the technical field can still modify the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention Changes can be easily thought of, or equivalent replacements are made to some of the technical features; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the scope of the present invention within the scope of protection. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims (7)

1. A multi-stage small-grained motion scheduling control method for a robot, characterized in that it comprises: The robot's motion scheduling tasks are divided into tasks, action groups and actions from top to bottom. Each task includes action groups, and each action group includes several actions. Actions are the smallest executable units that can be split into tasks. ; The preemptive high-priority priority scheduling method HPF is used in motion scheduling control, and the high-priority task is periodically queried in the current task. If the queried high-priority task is higher than the currently running task, the parameters and parameters of the current task are saved. state, to execute the high priority task, and execute the action group under the task, if the queried high priority task is lower than or equal to the currently running task, continue to execute the currently running task, the currently running task Sleep for a set time after the task is over, and then re-query the priority task; When inquiring about high-priority tasks, if the current highest-level task is a manual control task, then tasks with the same priority will be scheduled according to the deprivation-style service order, and all other subtasks under the manual control task will be cleared at the same time. the current latest subtask; When inquiring about high-priority tasks, if the current highest-level task is a non-manually controlled task, among tasks with the same priority, follow the first-come-first-serve scheduling order, and then search for the priority according to the depth left query method of the tree data structure. the highest level task; When executing each action group, each action in the action group is executed according to the first-in-first-out principle, as follows: Query whether the task to which the action group belongs is interrupted. If there is no interruption, the current action will be executed from the beginning of the action list index of the action group, and the next action will be queried at the same time; The status is set to execute successfully; Try to execute the next action queried, and the number of attempts is not more than 3. If the attempt is successful, the current task status will be set as executing. If there is no response after 3 attempts, it will be judged as a blocking action. Set the action status to execution failure; Returns the current task after traversing the action list of the action group. 2. The multi-level small-grained motion scheduling control method for a robot according to claim 1, wherein after each task is executed, the task is deleted from the task bucket, and a certain action group in the task is executed , the action group will be deleted from the task, and the action group is the smallest unit of granularity for task switching to save the running scene of the task. 3. A multi-stage small-grained motion scheduling control device for a robot, characterized in that it is used to realize the scheduling control method of claim 1 or 2, comprising: The motion scheduling task division module is used to divide the robot's motion scheduling tasks into tasks, action groups and actions from top to bottom. Each task includes action groups, and each action group includes several actions. Actions are tasks The smallest executable unit that can be split; The task query module is used for motion scheduling control and uses the preemptive high-priority priority scheduling method HPF to periodically query high-priority tasks in the current task. If the queried high-priority task is higher than the currently running task, then Save the parameters and status of the current task to execute the high-priority task and the action group under the task. If the queried high-priority task is lower than or equal to the currently running task, continue to execute the currently running task task, the currently running task sleeps for a set time after the end, and then re-queries the priority task. 4. A multi-level small-grained motion scheduling control device for a robot according to claim 3, wherein the task query module is also used for inquiring about high-priority tasks, if the current highest-level task is a non-manual control task , for tasks of the same priority, follow the first-come-first-serve scheduling order, and then search for the task with the highest priority according to the depth left query method of the tree data structure. 5. A multi-level small-grained motion scheduling control device for a robot according to claim 3, wherein the task query module is also used for inquiring about high-priority tasks, if the current highest-level task is a non-manual control task , for tasks of the same priority, follow the first-come-first-serve scheduling order, and then search for the task with the highest priority according to the depth left query method of the tree data structure. 6. A device comprising a memory, a processor, and a computer program stored in the memory and operable on the processor, wherein the computer program according to claim 1 is implemented when the processor executes the computer program Or the steps of a multi-level small-grained motion scheduling control method for a robot described in 2. 7. A computer-readable storage medium, the computer-readable storage medium is stored with a computer program, characterized in that, when the computer program is executed by a processor, it realizes a multi-stage small-grained movement of a robot as claimed in claim 1 or 2 The steps of the scheduling control method.