Robot dynamic task management method

Abstract

The invention discloses a robot dynamic task management method, which comprises the following steps: S1, a task manager of a scheduling management system receives a task, and places the task in a task pool to wait for distribution; s2, the task manager dynamically calculates the allocation priority of the tasks; s3, candidate robots capable of executing tasks are screened, and the moving cost of the robots for executing the tasks with the highest distribution priority is calculated; s4, distributing the task with the highest distribution priority to the robot with the lowest moving cost; s5, the task manager sets distributed tasks as running and undistributed to-be-run tasks to update waiting time in the task pool, and continues to dynamically calculate distribution priorities in the task pool, and S6, after the robot with the tasks obtains new tasks, the execution priorities of the tasks are calculated in combination with the initial task priorities and the compensation coefficients, and the tasks are distributed to the task pool. Reordering according to the execution priority; and S7, the robot executes the task according to the reordered task queue. Through multi-factor dynamic task allocation, the task allocation efficiency, the reasonability and the resource utilization rate are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of robot task management, and in particular to a robot dynamic task management method. Background Art

[0002] Mobile robots rely on autonomous navigation algorithms to plan their own paths and perform tasks autonomously. When multiple robots are running multiple tasks, all tasks need to be managed and allocated in a unified manner. In the field of multi-robot task management, existing technologies and patents have many limitations. On the one hand, some systems only allocate tasks based on fixed priorities, ignoring factors such as task waiting time, which may cause urgent tasks to miss the best execution time due to long waiting times. On the other hand, some methods do not fully consider key factors such as the actual position and moving speed of the robot when allocating tasks, which may cause tasks to be allocated to robots at a distance, thereby extending the task execution cycle. In addition, when the robot already has tasks, most of the existing technologies lack an effective mechanism to comprehensively consider the addition of new tasks and the adjustment of the execution order of the original tasks, making it difficult to achieve orderly execution of tasks, and there is no effective dynamic allocation mechanism for similar orders and on-the-way orders. Although existing patents have proposed some improvement plans, most of them focus on the optimization of a single factor, and have not formed a complete dynamic management process. It is difficult to cope with complex and changeable robot task scenarios and cannot meet the comprehensive requirements for efficiency, real-time and rationality of task allocation.

[0003] Therefore, it is necessary to develop a robot dynamic task management method to solve the above defects. Summary of the invention

[0004] In response to the technical problems existing in the above-mentioned prior art, the purpose of this application is to provide a mobile robot navigation method and system based on deep learning.

[0005] To achieve the purpose of the present invention, the present invention proposes a technical solution for a robot dynamic task management method, which manages the task allocation among multiple robots through a scheduling management system, and the robots execute the tasks autonomously after obtaining them. The specific steps are as follows: S1: The task manager of the scheduling management system receives the task and places it in the task pool waiting for allocation; S2: The task manager dynamically calculates the task allocation priority by combining at least the longest waiting time, the waiting time, the initial task priority, and the subsidy coefficient of each task; S3: Screening candidate robots that can execute tasks, calculating the time cost based on at least the current position, maximum moving speed, and task destination of the candidate robots, and combining the starting cost, moving coefficient, and time cost to calculate the moving cost of the candidate robots to execute the task with the highest assigned priority; S4: Assign the task with the highest assigned priority to the robot with the lowest movement cost; S5: The task manager sets the assigned tasks as running in the task pool, updates the waiting time of the unassigned tasks to be run, and continues to dynamically calculate the assigned priority in the task pool. Assign tasks according to the above steps S2, S3, and S4 until there are no tasks or no robots that can execute tasks; S6: After a robot with existing tasks obtains a new task, calculate the execution priority of the task by combining the initial task priority and the compensation coefficient, and reorder according to the execution priority; S7: The robot executes tasks according to the reordered task queue; The subsidy coefficient is the subsidy cost coefficient for the waiting time of the tasks to be run, the starting cost is the cost for an idle robot to start executing tasks from an idle state, the movement coefficient is the time cost coefficient for the robot to execute tasks, and the compensation coefficient is the compensation cost coefficient for the delay in executing the original tasks when a robot with existing tasks obtains a new task.

[0006] Further, before generating tasks, preset task parameters and robot parameters. The task parameters at least include the initial task priority, the longest waiting time, and the subsidy coefficient of each task. The robot parameters at least include the maximum load capacity, the maximum movement speed, the starting cost, the compensation coefficient, and the movement coefficient, and are set to be adjustable.

[0007] Further, before the scheduling management system assigns tasks, collect all robot information, at least including the robot's status, current location, remaining battery power, maximum load capacity, remaining load capacity, running status of existing tasks, running map, and running path.

[0008] Preferably, S2a: The task manager can be set to merge similar tasks, specifically including: clustering the tasks to be run in the task pool. For example, cluster the subtasks within the starting clustering radius and the ending clustering radius, and combine with the current maximum remaining load capacity of the robot to generate a batch task group. Calculate the assigned priority of the task group based on the minimum value of the longest waiting time, the maximum value of the waiting time, and the highest priority of the initial task priority within the subtasks in the task group, and combine with the subsidy coefficient. Assign the task group with the highest assigned priority to the robot with the lowest movement cost.

[0009] Preferably, S2b: Dynamically calculate the urgency of the subtasks in the task group to be run. The urgency = waiting time / longest waiting time. Set the urgency threshold for the stripping mechanism. When the urgency is greater than or equal to the threshold, trigger the stripping mechanism, and the task manager strips the subtask from the task group and forcibly assigns it to the robot with the lowest movement cost for priority execution.

[0010] Preferably, S3a: for the task allocation of transportation between different floors, the elevator time cost is calculated by at least combining the robot's current floor, the floor where the task destination is located, the elevator interaction time, the elevator speed, the robot's current position, the maximum moving speed, and the task destination; and the starting cost, the moving coefficient, and the time cost are combined to calculate the elevator movement cost of the candidate robot to perform the task with the highest assigned priority.

[0011] Preferably, S3b: the scheduling management system marks the congested nodes according to the traffic conditions in the operating area, calculates the traffic time cost based on at least the robot's current position, maximum moving speed, task destination, and number of congested nodes, and combines the starting cost, moving coefficient, and time cost to calculate the traffic movement cost of the candidate robot to perform the task with the highest assigned priority.

[0012] Preferably, S4a: when there are two or more candidate robots with the same comprehensive score, tasks are allocated in combination with other robot parameters such as remaining battery power and cumulative number of completed tasks.

[0013] Preferably, S4b: the task manager can be configured to assign a along-the-way task to the robot after it obtains the task with the highest assigned priority, specifically including: determining whether the current robot is fully loaded. If it is fully loaded, the along-the-way task will not be calculated; if it is not fully loaded, the path for the robot to execute the currently assigned task with the highest assigned priority will be calculated, the distance difference between the destination point of the task to be run and the current task path will be calculated, and whether the along-the-way condition is met. If there is an along-the-way task, the along-the-way task will be assigned to the robot. After the robot obtains the along-the-way task, it will be bound to the aforementioned task with the highest assigned priority for execution.

[0014] Compared with the prior art, the present invention utilizes the above robot dynamic task management method, which has the following main advantages or beneficial effects: (1) Optimize task allocation priority: Comprehensively consider the longest waiting time, waiting time, initial priority and subsidy coefficient of the task, dynamically calculate the task allocation priority, ensure that urgent tasks with long waiting time are allocated in time, and improve task processing efficiency; (2) Accurate robot selection: By calculating the movement cost of candidate robots, including starting cost, movement coefficient, and time cost, the task is assigned to the robot with the lowest movement cost, thereby improving task execution efficiency and reducing task completion time; Effectively manage multiple tasks: When a robot with existing tasks obtains a new task, the robot calculates the task execution priority and reorders it based on the initial task priority and compensation coefficient to ensure the orderly execution of tasks and improve the flexibility and adaptability of robot task management; (3) Improve the overall performance of the system: By merging similar tasks to generate batch task groups, the task allocation process is optimized to reduce the complexity of task allocation and resource waste; at the same time, a stripping mechanism is set up to ensure that emergency subtasks are executed in a timely manner, further improving the system's ability to respond to emergencies; (4) Adapting to complex environments: Considering the time cost of taking the elevator when transporting tasks on different floors and the time cost of traveling in traffic congestion, the task allocation is more in line with the actual scenario, improving the efficiency and reliability of the robot's task execution in complex environments; (5) Enhance the rationality of task allocation: When the comprehensive scores of robots are the same, task allocation is performed based on the remaining power and the cumulative number of completed tasks, further improving the rationality and fairness of task allocation; (6) Make full use of the robot's load capacity: Through the on-route task allocation mechanism, when the robot is not fully loaded, the on-route tasks are bound to the main task for execution, thereby improving the robot's load utilization and further optimizing the overall task execution efficiency of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 Shown is a schematic diagram of the process flow of the present application method; DETAILED DESCRIPTION

[0016] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0017] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should also be understood that when "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, parts or modules, components and / or their combinations.

[0018] It should be noted that the terms "including" and "having" and any variations thereof in the specification and claims of the present application and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or apparatuses.

[0019] It should be understood that the solution of the present invention can be implemented by a single or multiple combinations of hardware, software or other devices. In the description of the following embodiments, the methods and steps of the present invention can be implemented by being stored in a storage device including but not limited to a hard disk, a removable storage device, a magnetic disk, an optical disk, etc.

[0020] It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. Embodiment

[0021] As Figure 1 shown, the solution of the present invention provides a robot dynamic task management method, which manages the task allocation among multiple robots through a scheduling management system. After obtaining a task, the robot autonomously executes it. The specific steps are as follows: 1. Preset parameters: Preset task parameters and robot parameters. The task parameters at least include the initial task priority, the longest waiting time, and the subsidy coefficient of each task. The robot parameters at least include the maximum load capacity, the maximum moving speed, the starting cost, the compensation coefficient, and the movement coefficient, and are set to be adjustable according to actual operation needs.

[0022] 2. Communication between the scheduling management system and the robot: The scheduling management system collects all robot information, at least including the type, status, current position, remaining power, maximum load capacity, remaining load capacity, running status of existing tasks, running map, running path, etc. of the robot. It should be noted that the robot load capacity (including the maximum load capacity and the remaining load capacity) involved in this technical solution refers to the number of subtasks that the robot can receive. For example, a box-carrying robot can transport multiple boxes at the same time, and a roller robot can carry multiple materials at the same time.

[0023] 3. Task management and execution: S1: Task reception and storage: The task manager of the scheduling management system receives tasks from external tasks or submitted by this system, and places these tasks in the task pool waiting for allocation. Each task at least includes the following parameters: Initial task priority: The priority preset according to the importance and urgency of the task. The higher the value, the more important and urgent the task is; Longest waiting time: The longest time that the task can wait for allocation. If this time is exceeded, the task may not be completed or may affect subsequent operations; Waited time: The time that the task has waited for allocation in the task pool, with an initial value of 0 and gradually increasing over time.

[0024] S2: Task Assignment Priority Calculation: The task manager calculates the priority by combining at least the longest waiting time, the elapsed waiting time, the initial task priority, and the subsidy coefficient of each task. In other embodiments, other parameters can also be added for dynamic calculation. The dynamic calculation of the task assignment priority in this embodiment is as follows: , Formula 1; where, P t : The assignment priority of the task. The larger the value, the more priority the task has for being assigned. P t0 : The initial task priority of the task, which reflects the importance and urgency of the task itself. α: The subsidy coefficient, which is used to adjust the weight of tasks with a long waiting time in the assignment priority. The larger the subsidy coefficient, the greater the weight of tasks with a long waiting time for being assigned preferentially. T w : The elapsed waiting time of the task, that is, the time the task has waited in the task pool for assignment. T wmax : The longest waiting time of the task, that is, the longest time the task can wait for assignment.

[0025] S2a: Merging Similar Tasks: The task manager can be set to merge similar tasks, or it can also not be set to merge according to the actual situation. Just calculate the task assignment priority according to step S2. The following are the specific steps for merging similar tasks: (1) Task Clustering: Cluster the tasks to be run in the task pool. For example, merge the subtasks within the starting point clustering radius range and the ending point clustering radius range to improve the efficiency of task assignment and reduce the number of movements and distances of the robot; (2) Generating Batch Task Groups: Combine the remaining maximum load of the robot at present to generate batch task groups. The remaining maximum load of the robot refers to the maximum amount of tasks that the robot can carry in the current state; (3) Calculating the Assignment Priority of the Task Group: Calculate the assignment priority of the task group with the minimum value of the longest waiting time, the maximum value of the elapsed waiting time, and the highest priority of the initial task priority among the subtasks within the task group, combined with the subsidy coefficient, to ensure that the assignment priority of the task group can reflect the most urgent task requirements within the group. The calculation principle is the same as that of S2 and will not be elaborated here; (4) Assigning the Task Group: Assign the task group with the highest assignment priority to the robot with the lowest movement cost.

[0026] S2b: Urgency Calculation and Stripping Mechanism: The task manager can set the task group to enable the stripping mechanism. In a specific embodiment, it can be set to monitor the urgency within a certain time. The specific steps are as follows: Urgency Calculation: Dynamically calculate the urgency of the subtasks in the task group to be run, as follows: , Formula 2; where, U: The urgency of the task. The larger the value, the more urgent the task. T w : The waiting time of the task. T wmax : The maximum waiting time of the task.

[0027] (2) Set the urgency threshold: Set the urgency threshold of the stripping mechanism according to actual requirements; (3) Trigger the stripping mechanism: When the urgency is greater than or equal to the threshold, trigger the stripping mechanism. The task manager strips the subtask from the task group and forcibly assigns it to the robot with the lowest movement cost for priority execution to ensure that urgent tasks are processed in a timely manner.

[0028] S3: Screen candidate robots for executable tasks and calculate the movement cost. The specific steps are as follows: Screen candidate robots for executable tasks according to the requirements of the task, the type and status of the robot, etc. Calculate the time cost according to the current position, maximum movement speed, and task destination point of the candidate robot. The calculation is as follows: , Formula Three; Among them, T d is the time cost for the robot to move from the current position to the task destination point. D: The path length from the current position of the robot to the task destination point. v is the maximum movement speed of the robot.

[0029] Combine the start-up cost, movement coefficient, and time cost to calculate the movement cost for the candidate robot to execute the task with the highest allocation priority: , Formula Four; Among them, C m : The movement cost for the candidate robot to execute the task, which is used to determine which robot the task is assigned to. C s : The start-up cost, which is the cost for the robot to start executing the task from the idle state. The larger the start-up cost, the smaller the weight assigned to the idle robot. β: The movement coefficient, which is the time cost coefficient for the robot to execute the task. The larger the movement coefficient, the smaller the weight of the robot to execute this task. T d is the time cost for the robot to move from the current position to the task destination point.

[0030] Preferably, in different application scenarios, such as when the robot transports tasks between multiple floors and there may be traffic congestion for the robot, etc., in these scenarios, more dynamically calculated factors can be added to make the task allocation more efficient and on time. The following takes taking the elevator and traffic congestion as examples. Those skilled in the art can refer to this technical solution for optimization in other working conditions. Improvements and optimizations within the scope of the principle of this invention are within the protection scope of this invention.

[0031] S3a: Calculation of the time cost of taking the elevator: For the task allocation between different floors, at least combine the current floor of the robot, the floor where the task destination point is located, the elevator interaction time, the elevator speed, the current position of the robot, the maximum moving speed, and the task destination point to calculate the time cost of taking the elevator. The specific calculation method can be modeled according to the actual situation. For example: , Formula Five; Among them, T etotal : The total time cost required for the robot to complete the process of taking the elevator. T r2e : The sum of the time cost for the robot to reach the elevator and the time cost from the elevator to the task destination position. The calculation formula is T r2e = D r2e / v, where D r2e is the sum of the distance from the current position of the robot to the elevator position and the path length from the elevator position to the task destination point. v is the maximum moving speed of the robot. T ew : The elevator waiting time cost, that is, the time cost for the elevator to reach the floor where the robot is located. T er : The elevator running time cost, that is, the time cost for the elevator to run from the floor where the robot is located to the floor where the task destination point is located. The calculation formula is , where F t is the floor where the task destination point is located, F r is the current floor where the robot is located, v e is the average running speed of the elevator.

[0032] S3b: Calculation of the traffic time cost: The scheduling and management system marks the congested nodes according to the traffic conditions in the operation area, and calculates the traffic time cost according to the current position of the robot, the maximum moving speed, the task destination point, and the number of congested nodes. It can be modeled according to the actual situation. For example: , Formula Six; Among them, T ttraffic : The total time cost required for the robot to complete the task in case of traffic congestion. T tnormal : The normal driving time cost, that is, the time cost required for the robot to move from the current position to the task destination point in the case of no congestion. The calculation formula is T tnormal = D / v, where D is the path length from the current position of the robot to the task destination point, and v is the maximum moving speed of the robot; T tdelay : The congestion delay time cost, that is, the additional time cost generated by the robot due to traffic congestion. The calculation formula is T tdelay = N congestion × T dper , where N congestion is the number of congested nodes on the path, Tdper is the average delay cost of each congested node.

[0033] Comprehensive calculation of movement cost: replace the original time cost with the elevator time cost or traffic time cost, combine the starting cost and the movement coefficient, and calculate the elevator movement cost or traffic movement cost of the candidate robot to perform the task with the highest priority. The principle is the same as S3 and will not be repeated here.

[0034] S4: Task allocation: Assign the task with the highest priority to the robot with the lowest movement cost, ensure that the task is assigned to the robot most suitable for execution, and improve the efficiency of task execution.

[0035] S4a: Task allocation when comprehensive scores are the same: When there are two or more candidate robots with the same comprehensive scores, tasks are allocated based on other robot parameters such as remaining power and cumulative number of completed tasks. For example, robots with higher remaining power are given priority in tasks because they have longer working time, ensuring that tasks are completed and other robots with lower remaining power have enough time to charge. For example, robots with fewer cumulative number of completed tasks are given priority in tasks to balance the workload of the robots.

[0036] S4b: Allocation of on-the-way tasks: The task manager can be set to allocate on-the-way tasks to the robot after it obtains the task with the highest priority, according to actual usage needs. The specific steps are as follows: (1) Determine the robot load: Determine whether the current robot is fully loaded. If it is fully loaded, the en-route task will not be calculated; if it is not fully loaded, the subsequent operation will continue; (2) Calculate the current task path: Calculate the path for the robot to execute the task with the highest priority currently assigned; (3) Calculate the distance difference: Calculate the distance difference between the destination point of the task to be run and the current task path, reflecting the degree of proximity between the destination point of the task to be run and the current task path; (4) Determine the on-the-go condition: Determine whether the on-the-go condition is met based on the distance difference. For example, a distance threshold may be set. If the distance difference is less than or equal to the threshold, the on-the-go condition is considered to be met. (5) Allocating en-route tasks: If there are en-route tasks, assign them to the robot. After the robot obtains the en-route task, it executes it in conjunction with the previously assigned task with the highest priority. For example, the en-route task can be executed directly after the main task to ensure that the en-route task is not queued up by other tasks.

[0037] S5: The task manager sets the assigned tasks as running in the task pool, updates the waiting time of the unassigned tasks to be run, continues to dynamically calculate the assignment priority in the task pool, and assigns tasks according to the above steps S2, S3, S4 and related sub-steps until there are no tasks or no robots that can execute tasks.

[0038] S6: Adjust the execution priority of the robot tasks, and the specific steps are as follows: After a robot with existing tasks obtains a new task, combine the initial task priority and the compensation coefficient to calculate the execution priority of the task: , Formula Seven; Among them, P ex : The execution priority of the task, which is used to determine the execution order of tasks in the robot task queue, P t0 : The initial task priority of the task, which reflects the importance and urgency of the task itself, γ: The compensation coefficient, which is used to adjust the compensation cost weight for the delay in executing the original task when a robot with existing tasks obtains a new task. The larger the compensation coefficient, the greater the weight of running the original tasks of the robot first, T w : The waiting time of the task, which is the time the task waits for assignment in the task pool, T wmax : The longest waiting time of the task, which is the longest time the task can wait for assignment.

[0039] (2) Reorder according to the execution priority to ensure that tasks can be executed in a reasonable order.

[0040] S7: The robot executes tasks according to the reordered task queue.

[0041] The present invention can effectively improve the deficiencies of the existing technology and has great promotion value.

[0042] The above are only the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A method for dynamic task management of a robot, characterized in that Manage the task allocation among multiple robots through a scheduling management system. After obtaining a task, the robot executes it autonomously. The steps are as follows: S1: The task manager of the scheduling management system receives tasks and places them in the task pool waiting for allocation; S2: The task manager dynamically calculates the allocation priority of tasks by combining at least the longest waiting time, the elapsed waiting time, the initial task priority, and the subsidy coefficient of each task; S3: Screen candidate robots for executable tasks. Calculate the time cost based on at least the current position, the maximum moving speed, and the task destination point of the candidate robots. Combine the start-up cost, the movement coefficient, and the time cost to calculate the movement cost for the candidate robot to execute the task with the highest allocation priority; S4: Allocate the task with the highest allocation priority to the robot with the lowest movement cost; S5: The task manager sets the allocated tasks as running in the task pool, updates the elapsed waiting time for the unallocated tasks waiting to run, and continues to dynamically calculate the allocation priority in the task pool. Allocate tasks according to the above steps S2, S3, and S4 until there are no tasks or no robots capable of executing tasks; S6: After a robot with existing tasks obtains a new task, calculate the execution priority of the tasks by combining the initial task priority and the compensation coefficient, and reorder according to the execution priority; S7: The robot executes tasks according to the reordered task queue; The subsidy coefficient is the subsidy cost coefficient for the elapsed waiting time of the tasks waiting to run. The start-up cost is the cost for an idle robot to start executing a task from the idle state. The movement coefficient is the time cost coefficient for the robot to execute a task. The compensation coefficient is the compensation cost coefficient for the delay in executing the original tasks when a robot with existing tasks obtains a new task.

2. The method for dynamically managing tasks of a robot according to claim 1, wherein Before generating tasks, preset task parameters and robot parameters. The task parameters at least include the initial task priority, the longest waiting time, and the subsidy coefficient of each task. The robot parameters include the maximum load capacity, the maximum moving speed, the start-up cost, the compensation coefficient, and the movement coefficient, which are set to be adjustable.

3. The method for dynamically managing tasks of a robot according to claim 1, wherein Before the scheduling management system allocates tasks, collect information of all robots, at least including the status, the current position, the remaining battery power, the maximum load capacity, the remaining load capacity, the running status of existing tasks, the running map, and the running path of the robots.

4. A method for dynamic task management of a robot according to claim 1, characterized in that, In step S2: The task manager combines the longest waiting time, the elapsed waiting time, the initial task priority, and the subsidy coefficient of each task to dynamically calculate the allocation priority of tasks. Further, in S2a: The task manager can be set to merge similar tasks, specifically including: clustering the tasks waiting to run in the task pool. For example, cluster the subtasks within the start point clustering radius range and the end point clustering radius range, and generate a batch task group in combination with the current maximum remaining load capacity of the robot. Calculate the allocation priority of the task group based on the minimum value of the longest waiting time, the maximum value of the elapsed waiting time, and the highest priority of the initial task priority within the subtasks of the task group, combined with the subsidy coefficient, and allocate the task group with the highest allocation priority to the robot with the lowest movement cost.

5. A method for robot dynamic task management according to claim 4, characterized in that, Further including, S2b: dynamically calculate the urgency of the subtasks in the task group to be run, where the urgency = waiting time / maximum waiting time, set the urgency threshold of the stripping mechanism, and when the urgency is greater than or equal to the threshold, trigger the stripping mechanism, the task manager strips the subtask from the task group, and forcibly assigns it to the robot with the lowest movement cost for priority execution.

6. A method for dynamically managing tasks of a robot according to claim 1, characterized in that, When S3 calculates the time cost, further, S3a: for the task allocation of transportation between different floors, at least the current floor of the robot, the floor where the task destination is located, the elevator interaction time, the elevator speed, the current position of the robot, the maximum moving speed, and the task destination are used to calculate the time cost of taking the elevator, and the starting cost, the moving coefficient, and the time cost are combined to calculate the elevator movement cost of the candidate robot to perform the task with the highest assigned priority.

7. A method for robot dynamic task management according to claim 1, characterized in that, When S3 calculates the time cost, further, S3b: the scheduling management system marks the congested nodes according to the traffic conditions in the operating area, calculates the traffic time cost based on at least the current position of the robot, the maximum moving speed, the task destination, and the number of congested nodes, and combines the starting cost, the moving coefficient, and the time cost to calculate the traffic movement cost of the candidate robot to perform the task with the highest assigned priority.

8. A method for dynamic task management of a robot according to claim 1, characterized in that The S4: assigning the task group with the highest priority to the robot with the highest comprehensive score further includes, S4a: when there are two or more candidate robots with the same comprehensive score, assigning tasks in combination with other robot parameters such as remaining power and the cumulative number of completed tasks.

9. A method for robot dynamic task management according to claim 1, characterized in that The S4: assigns the task with the highest priority to the robot with the lowest moving cost. Furthermore, S4b: the task manager can be set to assign a task along the way to the robot after the robot obtains the task with the highest priority. Specifically, it includes: judging whether the current robot is fully loaded. If it is fully loaded, the task along the way is not calculated. If it is not fully loaded, the path for the robot to execute the task with the highest priority is calculated, the distance difference between the destination point of the task to be run and the path of the current task is calculated, and whether the along-the-way condition is met. If there is a task along the way, the task along the way is assigned to the robot. After the robot obtains the task along the way, it is bound to the aforementioned task with the highest priority for execution.

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