Robot cluster management method, system, equipment and medium

Abstract

The invention provides a robot cluster management method, system and device and a medium. According to the method, working data of each robot in a robot cluster is acquired to form a working data set, then a target position constraint feature quantity of a target robot is determined according to a current position set, and a target constraint level of the target robot is determined according to the target position constraint feature quantity and a preset constraint level range. Determining a target operation safety coefficient of the target robot according to the target constraint level and a target task priority corresponding to the target current task, and determining a target safety range of the target robot at the target current position according to the target operation safety coefficient; the target moving path in the current task of the target is indicated to indicate other robots located in the target safety range in the robot cluster to avoid the target moving path in the current task of the target, so that collision and interference between the robots during working of the robot cluster are effectively avoided, and the safety and smoothness of the robot cluster during cooperative work are ensured.

Description

Technical Field

[0001] The present application relates to data processing technology, and in particular to a robot cluster management method, system, device and medium. Background Art

[0002] With the rapid development of science and technology, robots are increasingly used in many fields such as industrial production, service industry, and military. Robot swarms, that is, collaborative working systems composed of multiple robots, have become one of the hot topics in current robotics research because they can significantly improve work efficiency and flexibility.

[0003] In a robot swarm, each robot has an independent perception, computing and control system, and can complete simple tasks autonomously. However, when multiple robots perform complex tasks together, how to reasonably schedule and coordinate the work of each robot becomes a huge challenge due to the constant changes in task requirements, robot status and environmental information. Especially in a dense working environment, collisions and interferences between robots will not only affect the efficiency of task execution, but may also cause damage to the robot or even safety accidents. It can be seen that in the collaborative work process of robot swarms, how to ensure safe collaboration between robots and avoid collisions and interference has become an urgent problem to be solved. Summary of the invention

[0004] The present application provides a robot cluster management method, system, device and medium to avoid collision and interference between robots in a robot cluster when working, and ensure the safety and smoothness of the robot cluster when working collaboratively.

[0005] In a first aspect, the present application provides a robot cluster management method, comprising: Acquire work data of each robot in the robot cluster to form a work data set, wherein the work data set includes a current position set and a current task set; Determining a target position constraint feature quantity of a target robot in the robot cluster according to the current position set, wherein the target position constraint feature quantity is used to characterize the degree to which the target robot is constrained by other robots in the robot cluster in a spatial dimension; Determining a target constraint level of the target robot according to the target position constraint feature quantity and a preset constraint level range, and determining a target operation safety factor of the target robot according to the target constraint level and a target task priority corresponding to a target current task in the current task set; The target safety range of the target robot at the target current position is determined according to the target operation safety factor to instruct other robots in the robot cluster located within the target safety range to avoid the target moving path in the target current task, and the target safety range is negatively correlated with the target operation safety factor.

[0006] In the above scheme, the working data of each robot in the robot cluster is first obtained to form a working data set including a current position set and a current task set. Then, by obtaining the position and task information of the robot in real time, the foundation is laid for the efficient collaborative work of the robot cluster. Based on the current position set of the robot cluster, the target position constraint feature quantity of the target robot is further determined. This feature quantity is used to characterize the degree to which the target robot is constrained by other robots in the spatial dimension. By calculating the target position constraint feature quantity, the spatial relationship in the robot cluster can be comprehensively evaluated, providing a basis for the subsequent constraint level determination and safety range delineation. The implementation of this step depends on the understanding and calculation of the spatial layout of the robot cluster, ensuring the rationality and reliability of the decision. Then, according to the target position constraint feature quantity and the preset constraint level range, the target constraint level of the target robot is determined. Then, combined with the target task priority corresponding to the target current task in the current task set, the target operation safety factor of the target robot is determined. The determination of the target operation safety factor not only takes into account the spatial constraints between robots, but also fully considers the influence of task priority, so that the decision is more in line with actual needs. Then, based on the target operation safety factor, the target safety range of the target robot at the target current position is determined. The safety range is negatively correlated with the target operation safety factor, that is, the higher the operation safety factor, the smaller the safety range; conversely, the larger the safety range. By reasonably defining the target safety range, other robots in the robot cluster within the range can be instructed to avoid the target moving path in the current task, thereby effectively avoiding collisions and interference between robots and ensuring the safety and smoothness of the robot cluster when working together.

[0007] Optionally, determining the target position constraint feature quantity of the target robot in the robot cluster according to the current position set includes: According to the target current position of the target robot and the target end point position of the target moving path determines the target path influence characteristic quantity; Determine a target motion influence feature value according to the target current position of the target robot and the current position set; The target position constraint feature quantity is determined according to the target path influence feature quantity and the target motion influence feature quantity.

[0008] In the above scheme, firstly, the target path influence feature quantity is determined according to the target current position of the target robot and the terminal position of the target moving path, thereby reflecting the path influence that the target robot may have on other robots during the movement. By determining the target path influence feature quantity, the path conflict that the target robot may have with other robots during the movement can be identified in advance, providing an important basis for subsequent obstacle avoidance and path planning. Based on the path influence feature quantity, the resources in the cluster can be allocated more reasonably, such as adjusting the moving paths or task priorities of other robots to minimize path conflicts and improve the overall operation efficiency. Secondly, the target motion influence feature quantity is determined in combination with the target current position of the target robot and the current position set (that is, the current position of all robots in the cluster), and the relative position and motion state between the target robot and other robots are fully considered. By determining the target motion influence feature quantity, the obstacles (that is, other robots) that the target robot may encounter during the movement can be dynamically evaluated, and its moving path can be adjusted accordingly to achieve dynamic obstacle avoidance. By considering the motion state of other robots, the system can plan the moving path of the target robot more accurately, reduce unnecessary waiting and pauses, and thus improve the collaborative operation efficiency of the entire cluster. Finally, the target position constraint feature is determined by combining the target path influence feature and the target motion influence feature. This process combines the factors of path conflict and motion interference, providing a scientific basis for comprehensively evaluating the position constraint of the target robot in the cluster.

[0009] It can be seen that by calculating the target position constraint feature, the system can accurately evaluate the position constraint degree of the target robot in the cluster, providing strong support for subsequent task allocation and path planning. Based on the target position constraint feature, the system can more reasonably set the safety range of the target robot to ensure its safety during the execution of the task. At the same time, by instructing other robots in the cluster to avoid the target moving path, the risk of collision is further reduced. By comprehensively considering path conflicts and motion interference factors, the system can optimize the operation process of the entire cluster, reduce unnecessary waiting and conflicts, and thus improve overall operation efficiency.

[0010] Optionally, instructing other robots in the robot cluster that are within the safety range of the target to avoid a target moving path of the target in the current task includes: If the task priority of a robot in the robot cluster that is located within the target safety range is lower than the target task priority, the corresponding robot is instructed to move outside the target safety range.

[0011] In the above scheme, after determining the target safety range of the target robot at its target current position, the task priority of other robots in the range is first compared with the target task priority. If the task priority of other robots is lower than the target task priority, the system will instruct these robots to move outside the target safety range. By comparing the task priorities, the system can schedule resources based on the urgency and importance of the tasks. High-priority tasks can be given priority execution opportunities, thereby ensuring the timely completion of critical tasks. By instructing robots with low-priority tasks to avoid, the system can reduce path conflicts and waiting times between robots and improve the overall efficiency of cluster operations. When the system decides to instruct one or some robots to move outside the target safety range, this decision is not static, but is dynamically adjusted according to the real-time position and status of the robots in the cluster. The dynamic avoidance mechanism allows the system to respond and adjust immediately according to the real-time position and status of the robots in the cluster, ensuring the accuracy and effectiveness of the avoidance decision. Through dynamic avoidance, the system can enhance the flexibility and adaptability of the robot cluster, enabling it to better cope with complex and changing task environments and emergencies.

[0012] It can be seen that by instructing robots with low-priority tasks to avoid robots with high-priority tasks, the system can optimize the cluster's work process, reduce unnecessary waiting and conflicts, and improve overall work efficiency. By ensuring that the target robot has a sufficient safety range when performing tasks, the system can significantly reduce the risk of collision and conflict and enhance the safety of the robot cluster. Through reasonable task priority comparison and avoidance decisions, the system can more efficiently utilize the resources within the cluster and avoid waste and idleness of resources.

[0013] Optionally, determining the target constraint level of the target robot according to the target position constraint feature quantity and a preset constraint level range, and determining the target operation safety factor of the target robot according to the target constraint level and the target task priority corresponding to the target current task in the current task set, includes: Determining the target constraint level according to the target position constraint feature quantity and the preset constraint level range; The target operation safety factor of the target robot is determined according to the target constraint level and the target task priority corresponding to the target current task in the current task set.

[0014] In the above scheme, after determining the target constraint level, the system further combines the target task priority corresponding to the target current task in the current task set and determines the target operation safety factor of the target robot. This process comprehensively considers the importance and urgency of the task, as well as the actual constraints of the target robot in the cluster. By combining the task priority with the constraint level, the system can more comprehensively evaluate the safety of the target robot in the process of executing the task, ensuring that high-priority tasks can be executed in a relatively safe environment. As the task priority and cluster status change, the target operation safety factor can be dynamically adjusted to meet the safety requirements in different scenarios. In addition, combined with the determination process of the target constraint level and the target operation safety factor, this method plays an important role in improving the efficiency of robot cluster management and ensuring the safety of task execution.

[0015] It can be seen that by evaluating the operational safety factor of the target robot, the system can allocate tasks more reasonably to ensure that high-priority and relatively safe tasks are executed first. By quantifying the degree of constraints and calculating the operational safety factor in combination with task priority, the system can identify potential safety risks in advance and take corresponding avoidance or protection measures to enhance the safety of cluster operations. The above scheme provides a scientific decision-making basis for the cluster management system, enabling the system to make reasonable scheduling and avoidance decisions more quickly and improve overall decision-making efficiency.

[0016] Optionally, determining a target safety range of the target robot at a target current position according to the target operation safety factor includes: Determining a target safety radius of the target robot at a target current position according to the target operation safety factor; The target safety range is determined according to the target safety radius and the current position of the target.

[0017] In the above scheme, first, according to the target operation safety factor of the target robot, the system determines the target safety radius. As an important indicator to measure the safety of the target robot in the process of executing the task, the target operation safety factor directly affects the size of the safety radius. By calculating the target safety radius, the system can quantify the safety requirements of the target robot at the current position, providing a scientific basis for the subsequent determination of the safety range. The size of the target safety radius is dynamically adjusted with the change of the target operation safety factor, which can adapt to the safety requirements in different task scenarios. After determining the target safety radius, the system further determines the target safety range in combination with the current position of the target robot. This range clarifies the area that other robots need to avoid to avoid collision or interference with the target robot. By determining the target safety range, the system can clearly indicate the area that other robots need to avoid, reducing the possibility of collision and conflict. Reasonable target safety range setting can optimize the cluster operation space, improve space utilization, and ensure operation safety. Combined with the determination process of the target safety radius and the target safety range, the above scheme plays an important role in improving the efficiency of robot cluster management and ensuring the safety of task execution.

[0018] It can be seen that by accurately determining the target safety range, the system can significantly reduce the risk of collision between robots and improve the safety of cluster operations. Reasonable safety range settings can reduce the waiting and avoidance time between robots and improve task execution efficiency. In addition, it also provides clear avoidance rules and safety boundaries for robot clusters, enhancing the coordination and consistency between robots in the cluster.

[0019] Optionally, after determining the target safety range of the target robot at the target current position according to the target operation safety factor, the method further includes: Determining an overall operation safety factor corresponding to the robot cluster according to the operation safety factors of each robot in the robot cluster; If it is determined that the overall operation safety factor is less than a preset first overall operation safety factor threshold, a warning message is sent, where the warning message is used to instruct scheduling adjustments to be made to the robot cluster.

[0020] In the above scheme, first, the overall operation safety factor corresponding to the robot cluster is determined according to the operation safety factor of each robot in the robot cluster. This process comprehensively considers the safety status of all robots in the cluster and provides a quantitative indicator for evaluating the overall safety of the cluster. By calculating the overall operation safety factor, the system can comprehensively evaluate the overall safety status of the robot cluster and identify possible safety risk points. The weight coefficients of different robots can be considered, making the calculation of the overall operation safety factor more scientific and reasonable, and can accurately reflect the importance of each robot in the cluster and its impact on the overall safety. When the system determines that the overall operation safety factor is less than the preset first overall operation safety factor threshold, it will automatically send an early warning message. This early warning message is used to indicate that the robot cluster should be scheduled and adjusted to prevent potential safety accidents. By sending early warning messages in a timely manner, the system can notify managers in advance or automatically trigger emergency response mechanisms before safety risks occur, thereby effectively avoiding the occurrence of safety accidents. In addition, the early warning message not only indicates the existence of safety risks, but also clearly points out the need to schedule and adjust the robot cluster, providing managers with clear operational guidance. Combined with the determination of the overall operation safety factor and the sending of early warning messages, the above scheme plays an important role in improving the management efficiency of the robot cluster and ensuring the overall safety of the cluster.

[0021] It can be seen that by real-time monitoring and evaluating the overall safety status of the cluster, the system can promptly detect and respond to potential safety risks, thereby significantly enhancing the safety of the robot cluster. The sending of early warning information prompts managers to adjust the scheduling of the robot cluster, optimize resource allocation, and improve the operating efficiency of the cluster. It also provides scientific decision-making support for managers, enabling them to make more reasonable and accurate decisions based on quantitative indicators and data.

[0022] It is worth noting that the calculation of the overall operation safety factor and the sending of warning information is a dynamic monitoring process. As the cluster status and task requirements change, the system will continuously update the overall operation safety factor and send warning information as needed. This dynamic monitoring mechanism helps ensure that the robot cluster is always in a safe and efficient operation state and provides strong support for its continuous improvement.

[0023] Optionally, after determining that the overall operation safety factor is less than a preset first overall operation safety factor threshold, the method further includes: If it is determined that the overall operation safety factor is less than the preset second overall operation safety factor threshold, a pause operation instruction is sent to the robots in the robot cluster whose task priority is lower than the preset priority level threshold, and the pause operation instruction is used to instruct the robot to pause operation or move to a predetermined position, and the preset second overall operation safety factor threshold is less than the preset first overall operation safety factor threshold.

[0024] In the above scheme, when the overall operation safety factor drops below the preset threshold, it is crucial to take appropriate measures to quickly restore the safety status of the cluster. When the overall operation safety factor is not only lower than the preset first threshold, but also further lower than the preset second threshold (and the second threshold is lower), the system will send a pause operation instruction to the robot with a lower task priority to achieve rapid safety adjustment of the cluster. When the overall operation safety factor is lower than the preset second threshold, it indicates that the robot cluster faces a more serious safety risk. At this time, the system can quickly reduce the dynamic elements in the cluster by suspending the operation of robots with task priorities lower than the preset priority threshold, thereby reducing safety risks such as collision and interference. Suspending the operation of low-priority robots can immediately reduce the number of active robots in the cluster and effectively alleviate the current safety risks. By concentrating resources on high-risk tasks or robots, the system can more effectively manage and control the overall safety of the cluster. Suspending low-priority tasks is not only to reduce risks immediately, but also to provide opportunities for rescheduling and optimization of subsequent tasks. After suspending low-priority tasks, the system can re-evaluate and adjust task priorities to ensure that critical tasks are given priority. According to the new task priority and safety status, the system can reallocate cluster resources to improve overall operation efficiency.

[0025] In addition, while sending the pause command, the system may also instruct some robots to move to a predetermined position, which further enhances the flexibility and safety of cluster management. By instructing the robots to move to the predetermined position, the system can achieve orderly evacuation and reorganization of the robots to avoid confusion and collision. The robots move to the designated position according to the predetermined path, maintaining the orderliness of the cluster and reducing the safety risks caused by disorderly movement. By arranging the positions of the robots reasonably, the system can optimize the working space of the cluster and improve space utilization. Moving the robots to the predetermined position can also prepare for emergency response and ensure that quick action can be taken in an emergency. When the robots are in the predetermined position, they can respond to emergency commands or perform emergency tasks more quickly. The predetermined robot position layout provides the cluster with greater flexibility to adapt to different task requirements and environmental changes.

[0026] In a second aspect, the present application provides a robot cluster management system, comprising: An acquisition module, used for acquiring working data of each robot in the robot cluster to form a working data set, wherein the working data set includes a current position set and a current task set; A processing module, used to determine a target position constraint feature quantity of a target robot in the robot cluster according to the current position set, wherein the target position constraint feature quantity is used to characterize the degree to which the target robot is constrained by other robots in the robot cluster in a spatial dimension; The processing module is further used to determine the target constraint level of the target robot according to the target position constraint feature quantity and the preset constraint level range, so as to determine the target operation safety factor of the target robot according to the target constraint level and the target task priority corresponding to the target current task in the current task set; The processing module is also used to determine the target safety range of the target robot at the target current position based on the target operation safety factor, so as to instruct other robots in the robot cluster that are located within the target safety range to avoid the target moving path in the target current task, and the target safety range is negatively correlated with the target operation safety factor.

[0027] Optionally, the processing module is specifically used to: According to the target current position of the target robot and the target end point position of the target moving path determines the target path influence characteristic quantity; Determine a target motion influence feature value according to the target current position of the target robot and the current position set; The target position constraint feature quantity is determined according to the target path influence feature quantity and the target motion influence feature quantity.

[0028] Optionally, the processing module is specifically used to: If the task priority of a robot in the robot cluster that is located within the target safety range is lower than the target task priority, the corresponding robot is instructed to move outside the target safety range.

[0029] Optionally, the processing module is specifically used to: Determining the target constraint level according to the target position constraint feature quantity and the preset constraint level range; The target operation safety factor of the target robot is determined according to the target constraint level and the target task priority corresponding to the target current task in the current task set.

[0030] Optionally, the processing module is specifically used to: Determining a target safety radius of the target robot at a target current position according to the target operation safety factor; The target safety range is determined according to the target safety radius and the current position of the target.

[0031] Optionally, the processing module is specifically used to: Determining an overall operation safety factor corresponding to the robot cluster according to the operation safety factors of each robot in the robot cluster; If it is determined that the overall operation safety factor is less than a preset first overall operation safety factor threshold, a warning message is sent, where the warning message is used to instruct scheduling adjustments to be made to the robot cluster.

[0032] Optionally, the processing module is specifically used to: If it is determined that the overall operation safety factor is less than the preset second overall operation safety factor threshold, a pause operation instruction is sent to the robots in the robot cluster whose task priority is lower than the preset priority level threshold, and the pause operation instruction is used to instruct the robot to pause operation or move to a predetermined position, and the preset second overall operation safety factor threshold is less than the preset first overall operation safety factor threshold.

[0033] In a third aspect, the present application provides an electronic device, including: processor; and, A memory, configured to store executable instructions of the processor; The processor is configured to perform any possible method described in the first aspect by executing the executable instructions.

[0034] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement any possible method described in the first aspect.

[0035] The robot cluster management method, system, device and medium provided in the present application obtain the working data of each robot in the robot cluster to form a working data set, and then determine the target position constraint feature quantity of the target robot in the robot cluster according to the current position set in the working data set, and then determine the target constraint level of the target robot according to the target position constraint feature quantity and the preset constraint level range, so as to determine the target operation safety factor of the target robot according to the target constraint level and the target task priority corresponding to the target current task in the current task set, and then determine the target safety range of the target robot at the target current position according to the target operation safety factor, so as to instruct other robots in the robot cluster that are within the target safety range to avoid the target moving path in the target current task, thereby effectively avoiding collisions and interferences between robots in the robot cluster when working, and ensuring the safety and smoothness of the robot cluster when working collaboratively. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0037] Figure 1 This is a flow chart of a robot cluster management method according to an example embodiment of the present application; Figure 2 is a flowchart of a robot cluster management method according to another exemplary embodiment of the present application; Figure 3 is a schematic diagram of the structure of a robot cluster management system according to an exemplary embodiment of the present application; Figure 4 It is a schematic diagram of the structure of an electronic device according to an exemplary embodiment of the present application.

[0038] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0039] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0040] In order to solve the above problems, the embodiment provided by the present application forms a complete work data set by comprehensively acquiring the work data of each robot in the robot cluster, including key information such as current position and task priority, etc. This data set provides a solid foundation for subsequent analysis and decision-making.

[0041] Based on the work data set, the concept of target position constraint feature quantity is further introduced. By calculating the target position constraint feature quantity of the target robot, the degree to which the target robot is constrained by other robots in the spatial dimension can be accurately characterized. The introduction of this feature quantity enables the robot cluster management system to more accurately understand the spatial relationship between robots, providing a scientific basis for subsequent task scheduling and path planning.

[0042] After determining the target position constraint feature quantity, the target constraint level of the target robot is determined according to the preset constraint level range. This step quantifies the spatial constraint relationship between robots into a specific constraint level, providing a quantitative indicator for subsequent decision-making. Then, combined with the target task priority corresponding to the target current task in the current task set, the target operation safety factor of the target robot is determined. This target operation safety factor comprehensively considers the importance and urgency of the task, as well as the actual constraints of the target robot in the cluster, providing a strong guarantee for the safe operation of the robot.

[0043] Finally, the target safety range of the target robot at the target current position is determined according to the target operation safety factor. The safety range is negatively correlated with the target operation safety factor, that is, the higher the operation safety factor, the smaller the safety range; conversely, the larger the safety range. By reasonably defining the target safety range, other robots in the robot cluster within the range can be instructed to avoid the target moving path in the target current task, thereby effectively avoiding collisions and interference between robots and ensuring the safety and smoothness of the robot cluster when working together.

[0044] Figure 1 FIG. 1 is a flow chart of a robot cluster management method according to an exemplary embodiment of the present application. Figure 1 As shown, the robot cluster management method provided in this embodiment includes: S101. Obtain working data of each robot in a robot cluster to form a working data set.

[0045] In this step, the working data of each robot in the robot cluster is obtained to form a working data set, which includes a current position set and a current task set.

[0046] Specifically, the precise location information of each robot is obtained in real time through the positioning sensors integrated on the robot (such as GPS, laser radar, visual sensors, etc.). This location information is usually expressed in the form of three-dimensional coordinates, which can accurately reflect the specific position of the robot in the workspace.

[0047] Each robot receives and performs specific tasks, such as handling, inspection, assembly, etc. The current task set records the type of task, task progress, task goal, etc. that each robot is currently performing. This information is crucial for subsequent task allocation and scheduling.

[0048] In order to more accurately calculate the relative motion and potential collision risk between robots, the current velocity vector information of each robot can also be obtained. This information can be directly obtained through the robot's motion sensor or controller.

[0049] By integrating the above information, a working data set including the current position set, the current task set (and the optional current velocity vector set) is formed, providing basic data support for subsequent analysis and decision-making.

[0050] S102. Determine a target position constraint feature quantity of a target robot in the robot cluster according to the current position set.

[0051] In this step, the target position constraint feature quantity of the target robot in the robot cluster is determined according to the current position set, wherein the target position constraint feature quantity is used to characterize the degree to which the target robot is constrained by other robots in the robot cluster in the spatial dimension.

[0052] Specifically, the target path influence feature quantity can be calculated based on the target current position of the target robot and the target terminal position of the target moving path. This feature quantity reflects the potential impact of the target robot's moving path on other robots. Then, based on the target current position of the target robot and the current position set (i.e., the position information of other robots), the target motion influence feature quantity is calculated. This feature quantity reflects the potential impact of the target robot's motion on other robots. Combining the target path influence feature quantity and the target motion influence feature quantity, the target position constraint feature quantity is calculated. This feature quantity comprehensively reflects the degree to which the target robot is constrained by other robots in the spatial dimension.

[0053] S103, determining a target constraint level of the target robot according to the target position constraint feature quantity and a preset constraint level range, and determining a target operation safety factor of the target robot according to the target constraint level and a target task priority corresponding to the target current task in the current task set.

[0054] Specifically, the target constraint level can be calculated based on the target position constraint feature quantity and the preset constraint level range (including the maximum increment, maximum value and minimum value). Among them, the constraint condition quantization function can be set to map the target position constraint feature quantity to the corresponding constraint level. Then, the target operation safety factor is calculated based on the target constraint level and the target task priority corresponding to the target current task in the current task set.

[0055] S104. Determine a target safety range of the target robot at the target current position according to the target operation safety factor.

[0056] In this step, the target safety range of the target robot at the target current position is determined according to the target operation safety factor to instruct other robots in the robot cluster within the target safety range to avoid the target moving path in the target current task. The target safety range is negatively correlated with the target operation safety factor.

[0057] Specifically, according to the target operation safety factor, the target safety radius corresponding to the target safety range of the target robot at the current target position is calculated. According to the calculated target safety range, other robots in the robot cluster within the range are instructed to avoid the target movement path of the target robot. This measure ensures the safety and smoothness of the target robot when performing tasks.

[0058] In a possible implementation, if the task priority of a robot in the robot cluster that is within the target safety range is lower than the target task priority, the corresponding robot is instructed to move outside the target safety range. Specifically, after receiving the broadcast information, each robot first confirms whether it is within the target safety range. The robot obtains its current position information through its own positioning sensor (such as GPS, laser radar, etc.) and compares it with the boundary coordinates of the target safety range. Each robot also obtains its own task priority information. The robot compares its own task priority with the target task priority to determine whether its own task priority is lower than the target task priority. If the robot confirms that it is within the target safety range and the task priority is lower than the target task priority, an avoidance instruction is generated. The avoidance instruction should include key information such as the target robot's identification, avoidance direction, and avoidance distance. The generated avoidance instruction is sent to the corresponding robot. The robot that receives the avoidance instruction adjusts its position according to the information in the instruction and moves outside the target safety range. During the movement process, the robot should continuously monitor the distance from the target safety range to ensure that it will not enter the range again. In the process of robot movement and avoidance, path planning and coordination of multiple robots may be involved. The system should monitor the movement status of the robot in real time to avoid collision and interference between robots. If there is a path conflict or avoidance difficulty, the system should adjust the avoidance command or re-plan the avoidance path in a timely manner. The system should continuously monitor the avoidance effect to ensure that the target robot can perform the task smoothly. If the avoidance effect is not good or the target robot still faces safety risks, the system should re-evaluate the target safety range and adjust the avoidance strategy.

[0059] In this embodiment, the working data of each robot in the robot cluster is obtained to form a working data set, and then the target position constraint feature quantity of the target robot in the robot cluster is determined according to the current position set in the working data set, and then the target constraint level of the target robot is determined according to the target position constraint feature quantity and the preset constraint level range, so as to determine the target operation safety factor of the target robot according to the target constraint level and the target task priority corresponding to the target current task in the current task set, and then determine the target safety range of the target robot at the target current position according to the target operation safety factor, so as to instruct other robots in the robot cluster that are within the target safety range to avoid the target moving path in the target current task, thereby effectively avoiding collisions and interferences between robots in the robot cluster when working, and ensuring the safety and smoothness of the robot cluster when working collaboratively.

[0060] Figure 2 FIG. 1 is a flow chart of a robot cluster management method according to another exemplary embodiment of the present application. Figure 2 As shown, the robot cluster management method provided in this embodiment includes: S201. Obtain working data of each robot in the robot cluster to form a working data set.

[0061] In this step, the working data of each robot in the robot cluster is obtained to form a working data set, which includes a current position set and a current task set.

[0062] Specifically, the precise location information of each robot is obtained in real time through the positioning sensors integrated on the robot (such as GPS, laser radar, visual sensors, etc.). This location information is usually expressed in the form of three-dimensional coordinates, which can accurately reflect the specific position of the robot in the workspace.

[0063] Each robot receives and performs specific tasks, such as handling, inspection, assembly, etc. The current task set records the type of task, task progress, task goal, etc. that each robot is currently performing. This information is crucial for subsequent task allocation and scheduling.

[0064] In order to more accurately calculate the relative motion and potential collision risk between robots, the current velocity vector information of each robot can also be obtained. This information can be directly obtained through the robot's motion sensor or controller.

[0065] By integrating the above information, a working data set including the current position set, the current task set (and the optional current velocity vector set) is formed, providing basic data support for subsequent analysis and decision-making.

[0066] S202. Determine a target position constraint feature quantity of a target robot in the robot cluster according to the current position set.

[0067] In this step, the target position constraint feature quantity of the target robot in the robot cluster is determined according to the current position set, wherein the target position constraint feature quantity is used to characterize the degree to which the target robot is constrained by other robots in the robot cluster in the spatial dimension.

[0068] In one possible implementation, using Formula 1, and according to the target current position of the target robot and the target end position of the target movement path Determine the target path impact characteristic , where Formula 1 is:

[0069] in, is the path influence gain coefficient; Using formula 2, and according to the target robot's current target position and the current location collection Determine the target motion impact feature , where Formula 2 is:

[0070] in, is the motion influence gain coefficient, The current location collection The current position of any robot except the target robot, is the motion influence range between the target robot and other robots; Using formula 3, and according to the target path to affect the feature quantity And the target motion affects the characteristic quantity Determine the target position constraint feature quantity , where Formula 3 is:

[0071] in, is the gradient operator, is the number of robots in the robot cluster, is the first robot in the robot cluster except the target robot The current position of the robot.

[0072] Formula 1 calculates the square of the Euclidean distance between the current position of the target robot and the target end position and multiplies it by the path influence gain coefficient to obtain the target path influence feature quantity. This feature quantity reflects the potential impact of the target robot's moving path on other robots and provides an important basis for the subsequent calculation of the target position constraint feature quantity. By introducing the path influence gain coefficient, the size of the path influence can be adjusted according to the actual situation, so that the calculation results are more in line with the needs of the actual scene.

[0073] Formula 2 takes different values ​​depending on whether the distance between the target robot and other robots is less than the maximum motion influence range. Thus, by calculating the distance between the target robot and other robots and comparing the distance with the maximum motion influence range, the target motion influence characteristic quantity is obtained. This characteristic quantity reflects the potential impact of the target robot's motion on other robots, especially when the target robot approaches other robots, its motion impact will increase significantly. By introducing the maximum motion influence range and motion influence gain coefficient, the impact of the target robot's motion on other robots can be more accurately quantified, providing more accurate data support for the subsequent calculation of the target position constraint characteristic quantity.

[0074] Formula 3 obtains the target position constraint feature by calculating the negative value of the sum of the gradient of the target path influence feature and the gradient of all target motion influence features. This feature comprehensively reflects the degree to which the target robot is constrained by other robots in the spatial dimension, and provides key data for the subsequent determination of the target constraint level and target operation safety factor of the target robot. By introducing the gradient operator, the direction and intensity of the target robot being constrained by other robots in the spatial dimension can be more accurately described. At the same time, by accumulating the gradients of all target motion influence features, the influence of all other robots in the cluster on the target robot can be fully considered to ensure the accuracy and reliability of the calculation results.

[0075] Further, according to the current position of the target robot and the target end position of the target movement path Determine the target path impact characteristic Previously, we could also use Formula 4 to determine the target path dynamic impact factor based on the current position set. , Formula 4 is:

[0076] in, The preset safety distance corresponding to the target task priority, is the safety distance attenuation coefficient corresponding to the target task priority, is the first robot in the robot cluster except the target robot The distance between the robot and the target robot, is the first robot in the robot cluster except the target robot The distance attenuation coefficient corresponding to the larger task priority of the robot and the target task priority, is the first preset coefficient, is the second preset coefficient; Using formula 5, and dynamically influencing factors based on the target path And preset basic path influence gain coefficient Determine the path impact gain coefficient , Formula 5 is:

[0077] in, is the third preset coefficient.

[0078] The above formula 4 takes into account multiple factors such as the target task priority, safety distance, the distance between other robots and the target robot, and the task priority of other robots, and calculates the target path dynamic impact factor. This factor reflects the dynamic degree to which the target robot's moving path is affected by other robots under the current task priority and robot distribution scenario. By introducing the safety distance attenuation coefficient and the preset coefficient, it can flexibly adapt to the needs of different task priorities and robot distribution scenarios, making the calculated target path dynamic impact factor more accurate and reliable.

[0079] The above formula 5 dynamically adjusts the preset basic path influence gain coefficient according to the calculated target path dynamic influence factor to obtain the path influence gain coefficient. This coefficient reflects the intensity of the impact of the target robot's moving path on other robots under the current task priority and robot distribution scenario. By introducing the hyperbolic tangent function and the third preset coefficient, formula 5 can smoothly adjust the path influence gain coefficient, making its changes under different target path dynamic influence factors more reasonable and controllable. This dynamic adjustment mechanism helps to more accurately quantify the impact of the target robot's moving path on other robots, and provides more accurate data support for the subsequent calculation of the target path impact characteristic quantity.

[0080] It can be seen that by introducing the dynamic adjustment mechanism of the target path dynamic impact factor and the path impact gain coefficient, the target path impact characteristic quantity can be calculated more accurately, so as to more accurately evaluate the degree to which the target robot is constrained by other robots in the spatial dimension. This step can flexibly adapt to the needs of different task priorities and robot distribution scenarios, making the robot cluster management method more universal and practical. Based on more accurate target path impact characteristic quantities, the robot cluster management system can make more reasonable task allocation and scheduling decisions, and improve the overall work efficiency and safety of the cluster.

[0081] Furthermore, the working data set includes a current speed set. Correspondingly, according to the target current position of the target robot and the current location collection Determine the target motion impact feature Previously, you could also use formula 6 and calculate the gain coefficient based on the current speed set and the preset basic motion effect Determine the motion effect gain factor , Formula 6 is:

[0082] in, is the robot in the robot cluster determined based on the current speed set, excluding the target robot. The relative speed between the robot and the target robot, To preset the maximum speed threshold, is the first robot in the robot cluster except the target robot The relative velocity direction angle between the robot and the target robot, is the preset speed sensitivity coefficient, is the preset directional sensitivity coefficient.

[0083] The above formula 6 comprehensively considers the relative speed between the target robot and other robots, as well as the preset speed sensitivity coefficient and direction sensitivity coefficient, and calculates the motion impact gain coefficient. This coefficient reflects the intensity of the impact of the target robot's motion on other robots under the current speed distribution and relative motion state. By introducing the two factors of relative speed and direction angle, and combining the speed sensitivity coefficient and direction sensitivity coefficient for weighted summation, formula 6 can more comprehensively evaluate the potential impact of the target robot's motion on other robots. At the same time, the preset basic motion impact gain coefficient provides a benchmark value, making the calculation result more stable and reliable.

[0084] By dynamically calculating the motion influence gain coefficient, the impact of the target robot's motion on other robots can be more accurately quantified. This helps to more accurately reflect the spatial relationship and dynamic interaction between the target robot and other robots when calculating the target motion influence feature. Since the motion influence gain coefficient is dynamically calculated based on the current velocity set, it can adapt to scenarios with different velocity distributions and relative motion states. This allows the robot cluster management method to maintain high calculation accuracy and robustness in different environments.

[0085] Based on more accurate target motion impact characteristic quantities, the robot cluster management system can more reasonably assign tasks to each robot to avoid task conflicts and potential collision risks. By accurately evaluating the impact of the target robot's motion on other robots, the robot cluster management system can optimize the robot's motion path and speed, reduce unnecessary waiting and stagnation time, and thus improve the operating efficiency of the entire cluster. Dynamically calculating the motion impact gain coefficient and applying it to the calculation of the target motion impact characteristic quantity can help identify and prevent potential safety risks in advance and ensure the safe operation of the robot cluster in complex environments.

[0086] S203, determining a target constraint level of the target robot according to the target position constraint feature quantity and a preset constraint level range, and determining a target operation safety factor of the target robot according to the target constraint level and a target task priority corresponding to the target current task in the current task set.

[0087] Specifically, we can use Formula 7 and constrain the feature quantity according to the target position And the preset constraint level range determines the target constraint level , Formula 7 is:

[0088] in, For preset A constraint quantization function, Quantize the number of functions for the given constraints, For the The preset weights of the constraints, is the maximum increment of the preset constraint level range, is the maximum value of the preset constraint level range, is the minimum value of the preset constraint level range; Using formula 8, and according to the target constraint level And the target task priority corresponding to the target current task in the current task set Determine the target operation safety factor of the target robot , Formula 8 is:

[0089] in, is the average value of all preset constraint levels, is the maximum value of the task priority, is the first adjustment parameter, which is used to adjust the sensitivity of the target operation safety factor to the constraint level. It is the second adjustment parameter, which is used to adjust the sensitivity of the target operation safety factor to the task priority.

[0090] Formula 7 comprehensively considers multiple constraint quantization functions and their weights, and maps the target position constraint feature quantity to the preset constraint level range through weighted average and logarithmic transformation to obtain the target constraint level. This process makes the determination of the target constraint level more scientific and reasonable, and can more accurately reflect the degree of constraint of the target robot in the cluster. By introducing the weight coefficient, Formula 7 can perform differentiated processing according to the importance and influence of different constraints, improving the accuracy and flexibility of constraint level calculation. At the same time, the logarithmic transformation method makes the calculation result of the constraint level smoother, avoiding the influence of extreme values ​​on the overall result.

[0091] Formula 8 calculates the target operation safety factor in the form of a logistic function according to the target constraint level and the current task priority. The value range of the target operation safety factor is (0,1), which can intuitively reflect the operation safety status of the target robot in the current task and environment. When the target constraint level is higher or the target task priority is higher, the value of the target operation safety factor will decrease accordingly, indicating that the operation safety risk of the target robot increases; otherwise, it indicates that the operation safety risk decreases. In addition, by introducing adjustment parameters, Formula 8 can flexibly adjust the sensitivity of the target operation safety factor to the constraint level and task priority according to the needs of different application scenarios. This enables the robot cluster management system to more accurately evaluate the operation safety status of the target robot in different tasks and environments, and provide strong support for task allocation and scheduling decisions.

[0092] It can be seen that by comprehensively considering multiple constraints and their weights, and introducing the logistic function to calculate the target operation safety factor, the present invention can more accurately evaluate the operation safety status of the target robot in the cluster. By introducing adjustment parameters and flexible constraint level calculation methods, it can adapt to the needs of different tasks and environments, and improve the versatility and practicality of the robot cluster management method. In addition, based on more accurate operation safety assessment results, the robot cluster management system can make more reasonable task allocation and scheduling decisions, and improve the overall work efficiency and safety of the cluster.

[0093] S204. Determine a target safety range of the target robot at the target current position according to the target operation safety factor.

[0094] In this step, the target safety range of the target robot at the target current position is determined according to the target operation safety factor to instruct other robots in the robot cluster within the target safety range to avoid the target moving path in the target current task. The target safety range is negatively correlated with the target operation safety factor.

[0095] Specifically, formula 9 can be used to calculate the safety factor according to the target operation. Determine the target safety radius corresponding to the target safety range of the target robot at the target current position , Formula 9 is:

[0096] in, The basic safety radius corresponding to the basic safety range, is the minimum value of the operating safety factor, is the maximum value of the operating safety factor, is the current average expected distance of all robots in the robot cluster, is the current speed of the target robot, is the maximum speed of the target robot, It is the speed adjustment factor, which is used to adjust the impact of the robot speed on the safety range.

[0097] Formula 9 comprehensively considers the target operation safety factor, the average expected distance of robots in the robot cluster, and the current speed of the target robot, and dynamically calculates the target safety radius corresponding to the target safety range. This process makes the determination of the target safety range more scientific and reasonable, and can more accurately reflect the safe operation requirements of the target robot in the current task and environment. By introducing the speed adjustment factor, Formula 9 can perform differentiated processing according to the safety risks at different speeds, so that the calculation results of the target safety radius are more in line with the actual operation situation. At the same time, combined with the target operation safety factor and the average expected distance, Formula 9 can more comprehensively evaluate the safe operation requirements of the target robot in the cluster.

[0098] Moreover, by dynamically calculating the target safety radius, a more accurate safety range can be provided for the target robot, thereby effectively avoiding collision and interference with other robots and improving the overall safety of the robot cluster. After determining the target safety range, the robot cluster management system can more reasonably plan the movement path and speed of the target robot to ensure the efficient execution of the task. At the same time, other robots can also avoid and work together according to the target safety range to improve the overall operation efficiency of the cluster. Since the target safety radius is dynamically calculated based on the current operation safety factor, average expected distance and speed, it can adapt to the needs of different tasks and environments. This enables the robot cluster management method to maintain high safety and adaptability in different scenarios.

[0099] In addition, by comprehensively considering multiple factors such as the target operation safety factor, average expected distance and speed, the safe operation requirements of the target robot in the current task and environment can be more accurately evaluated, providing strong support for determining the target safety range. By dynamically calculating the target safety radius, the robot cluster management system can be flexibly adjusted according to different operating conditions and task requirements, improving the flexibility and robustness of the system. Based on a more accurate target safety range, the individual robots in the robot cluster can work together better, improving the overall efficiency and safety of the cluster.

[0100] S205. Determine the overall operation safety factor corresponding to the robot cluster according to the operation safety factor of each robot in the robot cluster.

[0101] Specifically, using formula 10, and based on the operation safety factor of each robot in the robot cluster, the overall operation safety factor of the robot cluster is determined: , Formula 10 is:

[0102] in, For the robot cluster The operational safety factor of a robot, For the robot cluster The weight coefficient of each robot, It is a preset adjustment coefficient used to adjust the impact of task priority on the overall operation safety factor. For the robot cluster The task priority of each robot, For the robot cluster The robot and The actual distance between the robots, For the robot cluster The robot and The desired safe distance between the robots.

[0103] S206: Send a warning message or a command to suspend operation.

[0104] In one possible scenario, if the overall operational safety factor is determined If it is less than the preset first overall operation safety factor threshold, an early warning message is sent, and the early warning message is used to instruct the scheduling adjustment of the robot cluster.

[0105] In the above scheme, Formula 10 comprehensively considers the operation safety factor, weight coefficient, task priority, actual distance and expected safety distance between robots of each robot in the robot cluster, and calculates the overall operation safety factor of the robot cluster by weighted average and exponential transformation. This process can fully reflect the overall operation safety status of the robot cluster under the current task and environment. By introducing weight coefficients and task priorities, Formula 10 can perform differentiated processing according to the importance and task urgency of different robots in the cluster, thereby improving the accuracy and rationality of the calculation of the overall operation safety factor. At the same time, combined with the actual distance and expected safety distance between robots, Formula 10 can more comprehensively evaluate the collaborative work effect and safety risks of the robot cluster.

[0106] If it is determined that the overall operation safety factor is less than the preset first overall operation safety factor threshold, a warning message is sent. By setting the warning conditions, when the overall operation safety status of the robot cluster is lower than the preset threshold, a warning message can be issued in time to prompt the robot cluster to make scheduling adjustments. This process can effectively avoid mission failures or safety accidents caused by excessive operation safety risks of the robot cluster. The introduction of the early warning decision-making mechanism enables the robot cluster management system to actively identify and respond to potential safety risks, improving the response speed and safety of the system. At the same time, by setting a reasonable early warning threshold, the accuracy and effectiveness of the early warning information can be ensured, and unnecessary interference and false alarms can be avoided.

[0107] It can be seen that by comprehensively evaluating the overall operational safety status of the robot cluster and setting early warning conditions for timely intervention, the safety of the robot cluster can be significantly improved and the probability of safety accidents can be reduced. Based on the calculation results of the overall operational safety factor, the robot cluster management system can more reasonably plan task allocation and scheduling strategies to improve the overall work efficiency and performance of the cluster. By introducing an early warning decision-making mechanism, the robot cluster management system can better cope with complex and changing environments and task requirements, and improve the robustness and adaptability of the system.

[0108] In another possible situation, if the overall operational safety factor is determined If it is less than the preset second overall operation safety factor threshold, a pause operation instruction is sent to the robots in the robot cluster whose task priority is lower than the preset priority threshold. The pause operation instruction is used to instruct the robot to pause operation or move to a predetermined position. The preset second overall operation safety factor threshold is less than the preset first overall operation safety factor threshold.

[0109] In the above scheme, when the overall operation safety factor drops below the preset threshold, it is crucial to take appropriate measures to quickly restore the safety status of the cluster. When the overall operation safety factor is not only lower than the preset first threshold, but also further lower than the preset second threshold (and the second threshold is lower), the system will send a pause operation instruction to the robot with a lower task priority to achieve rapid safety adjustment of the cluster. When the overall operation safety factor is lower than the preset second threshold, it indicates that the robot cluster faces a more serious safety risk. At this time, the system can quickly reduce the dynamic elements in the cluster by suspending the operation of robots with task priorities lower than the preset priority threshold, thereby reducing safety risks such as collision and interference. Suspending the operation of low-priority robots can immediately reduce the number of active robots in the cluster and effectively alleviate the current safety risks. By concentrating resources on high-risk tasks or robots, the system can more effectively manage and control the overall safety of the cluster. Suspending low-priority tasks is not only to reduce risks immediately, but also to provide opportunities for rescheduling and optimization of subsequent tasks. After suspending low-priority tasks, the system can re-evaluate and adjust task priorities to ensure that critical tasks are given priority. According to the new task priority and safety status, the system can reallocate cluster resources to improve overall operation efficiency.

[0110] In addition, while sending the pause command, the system may also instruct some robots to move to a predetermined position, which further enhances the flexibility and safety of cluster management. By instructing the robots to move to the predetermined position, the system can achieve orderly evacuation and reorganization of the robots to avoid confusion and collision. The robots move to the designated position according to the predetermined path, maintaining the orderliness of the cluster and reducing the safety risks caused by disorderly movement. By arranging the positions of the robots reasonably, the system can optimize the working space of the cluster and improve space utilization. Moving the robots to the predetermined position can also prepare for emergency response and ensure that quick action can be taken in an emergency. When the robots are in the predetermined position, they can respond to emergency commands or perform emergency tasks more quickly. The predetermined robot position layout provides the cluster with greater flexibility to adapt to different task requirements and environmental changes.

[0111] It can be seen that by pausing the operation of low-priority robots and instructing them to move to a predetermined position, the system can significantly enhance the safety and stability of the robot cluster and effectively prevent the occurrence of safety accidents. While reducing safety risks, this measure also optimizes the efficiency of task execution, ensuring that critical tasks are handled in a timely and effective manner by rescheduling and optimizing task priorities.

[0112] It is worth noting that this measure is not a one-time application, but is dynamically adjusted as the cluster status and task requirements change. The system will continuously monitor the overall operational safety factor and send a pause command or instruct the robot to move to a predetermined position as needed to ensure that the cluster is always in a safe and efficient operating state. This dynamic adjustment mechanism helps to continuously improve and optimize the robot cluster.

[0113] Figure 3 FIG. 1 is a schematic diagram of a robot cluster management system according to an exemplary embodiment of the present application. Figure 3 As shown, the robot cluster management system 300 provided in this embodiment includes: An acquisition module 310 is used to acquire working data of each robot in the robot cluster to form a working data set, wherein the working data set includes a current position set and a current task set; A processing module 320 is used to determine a target position constraint feature quantity of a target robot in the robot cluster according to the current position set, wherein the target position constraint feature quantity is used to characterize the degree to which the target robot is constrained by other robots in the robot cluster in a spatial dimension; The processing module 320 is further configured to determine a target constraint level of the target robot according to the target position constraint feature quantity and a preset constraint level range, so as to determine a target operation safety factor of the target robot according to the target constraint level and a target task priority corresponding to the target current task in the current task set; The processing module 320 is also used to determine the target safety range of the target robot at the target current position based on the target operation safety factor, so as to instruct other robots in the robot cluster that are located within the target safety range to avoid the target moving path in the target current task, and the target safety range is negatively correlated with the target operation safety factor.

[0114] Optionally, the processing module 320 is specifically configured to: According to the target current position of the target robot and the target end point position of the target moving path determines the target path influence characteristic quantity; Determine a target motion influence feature value according to the target current position of the target robot and the current position set; The target position constraint feature quantity is determined according to the target path influence feature quantity and the target motion influence feature quantity.

[0115] Optionally, the processing module 320 is specifically configured to: If the task priority of a robot in the robot cluster that is located within the target safety range is lower than the target task priority, the corresponding robot is instructed to move outside the target safety range.

[0116] Optionally, the processing module 320 is specifically configured to: Determining the target constraint level according to the target position constraint feature quantity and the preset constraint level range; The target operation safety factor of the target robot is determined according to the target constraint level and the target task priority corresponding to the target current task in the current task set.

[0117] Optionally, the processing module 320 is specifically configured to: Determining a target safety radius of the target robot at a target current position according to the target operation safety factor; The target safety range is determined according to the target safety radius and the current position of the target.

[0118] Optionally, the processing module 320 is specifically configured to: Determining an overall operation safety factor corresponding to the robot cluster according to the operation safety factors of each robot in the robot cluster; If it is determined that the overall operation safety factor is less than a preset first overall operation safety factor threshold, a warning message is sent, where the warning message is used to instruct scheduling adjustments to be made to the robot cluster.

[0119] Optionally, the processing module 320 is specifically configured to: If it is determined that the overall operation safety factor is less than the preset second overall operation safety factor threshold, a pause operation instruction is sent to the robots in the robot cluster whose task priority is lower than the preset priority level threshold, and the pause operation instruction is used to instruct the robot to pause operation or move to a predetermined position, and the preset second overall operation safety factor threshold is less than the preset first overall operation safety factor threshold.

[0120] Figure 4 is a schematic diagram of the structure of an electronic device according to an exemplary embodiment of the present application. Figure 4As shown, an electronic device 400 provided in this embodiment includes: a processor 401 and a memory 402; wherein: The memory 402 is used to store computer programs, and the memory may also be a flash memory.

[0121] The processor 401 is used to execute the execution instructions stored in the memory to implement each step in the above method. For details, please refer to the relevant description in the above method embodiment.

[0122] Optionally, the memory 402 may be independent or integrated with the processor 401 .

[0123] When the memory 402 is a device independent of the processor 401, the electronic device 400 may further include: The bus 403 is used to connect the memory 402 and the processor 401 .

[0124] This embodiment further provides a readable storage medium, in which a computer program is stored. When at least one processor of an electronic device executes the computer program, the electronic device executes the methods provided in the above-mentioned various implementation modes.

[0125] This embodiment also provides a program product, which includes a computer program stored in a readable storage medium. At least one processor of the electronic device can read the computer program from the readable storage medium, and at least one processor executes the computer program so that the electronic device implements the methods provided in the above various embodiments.

[0126] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the claims.

[0127] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A robot cluster management method, characterized in that: include: Acquire work data of each robot in the robot cluster to form a work data set, wherein the work data set includes a current position set and a current task set; Determining a target position constraint feature quantity of a target robot in the robot cluster according to the current position set, wherein the target position constraint feature quantity is used to characterize the degree to which the target robot is constrained by other robots in the robot cluster in a spatial dimension; Determining a target constraint level of the target robot according to the target position constraint feature quantity and a preset constraint level range, and determining a target operation safety factor of the target robot according to the target constraint level and a target task priority corresponding to a target current task in the current task set; The target safety range of the target robot at the target current position is determined according to the target operation safety factor to instruct other robots in the robot cluster located within the target safety range to avoid the target moving path in the target current task, and the target safety range is negatively correlated with the target operation safety factor.

2. The robot cluster management method according to claim 1, characterized in that: The step of determining the target position constraint feature quantity of the target robot in the robot cluster according to the current position set includes: According to the target current position of the target robot and the target end point position of the target moving path determines the target path influence characteristic quantity; Determine a target motion influence feature value according to the target current position of the target robot and the current position set; The target position constraint feature quantity is determined according to the target path influence feature quantity and the target motion influence feature quantity.

3. The robot cluster management method according to claim 2, characterized in that: The instructing other robots in the robot cluster that are within the target safety range to avoid the target moving path in the current task of the target includes: If the task priority of a robot in the robot cluster that is located within the target safety range is lower than the target task priority, the corresponding robot is instructed to move outside the target safety range.

4. The robot cluster management method according to any one of claims 1 to 3, characterized in that: The step of determining the target constraint level of the target robot according to the target position constraint feature quantity and a preset constraint level range, and determining the target operation safety factor of the target robot according to the target constraint level and the target task priority corresponding to the target current task in the current task set, includes: Determining the target constraint level according to the target position constraint feature quantity and the preset constraint level range; The target operation safety factor of the target robot is determined according to the target constraint level and the target task priority corresponding to the target current task in the current task set.

5. The robot cluster management method according to claim 4, characterized in that: Determining a target safety range of the target robot at a target current position according to the target operation safety factor includes: Determining a target safety radius of the target robot at a target current position according to the target operation safety factor; The target safety range is determined according to the target safety radius and the current position of the target.

6. The robot cluster management method according to claim 5, characterized in that: After determining the target safety range of the target robot at the target current position according to the target operation safety factor, the method further includes: Determining an overall operation safety factor corresponding to the robot cluster according to the operation safety factors of each robot in the robot cluster; If it is determined that the overall operation safety factor is less than a preset first overall operation safety factor threshold, a warning message is sent, where the warning message is used to instruct scheduling adjustments to be made to the robot cluster.

7. The robot cluster management method according to claim 6, characterized in that: After determining that the overall operation safety factor is less than a preset first overall operation safety factor threshold, the method further includes: If it is determined that the overall operation safety factor is less than the preset second overall operation safety factor threshold, a pause operation instruction is sent to the robots in the robot cluster whose task priority is lower than the preset priority level threshold, and the pause operation instruction is used to instruct the robot to pause operation or move to a predetermined position, and the preset second overall operation safety factor threshold is less than the preset first overall operation safety factor threshold.

8. A robot cluster management system, characterized in that: include: An acquisition module, used for acquiring working data of each robot in the robot cluster to form a working data set, wherein the working data set includes a current position set and a current task set; A processing module, used to determine a target position constraint feature quantity of a target robot in the robot cluster according to the current position set, wherein the target position constraint feature quantity is used to characterize the degree to which the target robot is constrained by other robots in the robot cluster in a spatial dimension; The processing module is further used to determine the target constraint level of the target robot according to the target position constraint feature quantity and the preset constraint level range, so as to determine the target operation safety factor of the target robot according to the target constraint level and the target task priority corresponding to the target current task in the current task set; The processing module is also used to determine the target safety range of the target robot at the target current position based on the target operation safety factor, so as to instruct other robots in the robot cluster that are located within the target safety range to avoid the target moving path in the target current task, and the target safety range is negatively correlated with the target operation safety factor.

9. An electronic device, characterized in that: include: processor; as well as, A memory, configured to store executable instructions of the processor; The processor is configured to perform the method of any one of claims 1 to 7 by executing the executable instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 7 when executed by a processor.

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