Robot Cluster Management Method, System, Device and Medium

Abstract

The present application provides a method, system, device and medium for robot cluster management. The method forms a working data set by acquiring the working data of each robot in the robot cluster. Then, it determines the target position constraint feature quantity of the target robot according to the current position set, and then determines 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. Furthermore, it determines 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 within the target safety range to avoid the target movement path in the target current task, thereby effectively avoiding collisions and interferences between robots when the robot cluster is working, and ensuring the safety and smoothness of the robot cluster during collaborative work.

Description

Technical Field

[0001] This application relates to data processing technologies, and in particular to a method, system, device, and medium for robot cluster management. Background Art

[0002] With the rapid development of technology, robots are increasingly widely used in multiple fields such as industrial production, the service industry, and the military. A robot cluster, that is, a collaborative working system composed of multiple robots, has become one of the hotspots in current robot technology research because it can significantly improve work efficiency and flexibility.

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

[0004] This application provides a method, system, device, and medium for robot cluster management to avoid collisions and interferences between robots during the operation of the robot cluster and ensure the safety and smoothness of the robot cluster during collaborative work.

[0005] In a first aspect, this application provides a method for robot cluster management, including:

[0006] Obtain the working data of each robot in the robot cluster to form a working data set, where the working data set includes a current position set and a current task set;

[0007] Determine the target position constraint feature quantity of a target robot in the robot cluster according to the current position set, where the target position constraint feature quantity is used to characterize the degree of constraint of the target robot by other robots in the robot cluster in the spatial dimension;

[0008] Determine the 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 the target operation safety coefficient 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;

[0009] Determine a target safety range of the target robot at the target current position according to the target running safety factor, so as to instruct other robots in the robot cluster located within the target safety range to avoid the target movement path in the target current task, and the target safety range has a negative correlation with the target running safety factor.

[0010] In the above solution, first, obtain the working data of each robot in the robot cluster 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, it lays a foundation 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 of constraint of the target robot 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 subsequent determination of the constraint level and delimitation of the safety range. The realization 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-making. Next, according to the target position constraint feature quantity and the preset constraint level range, the target constraint level of the target robot is determined. Furthermore, in combination with the target task priority corresponding to the target current task in the current task set, the target running safety factor of the target robot is determined. The determination of the target running safety factor not only considers the spatial constraint between robots but also fully considers the influence of the task priority, making the decision more in line with the actual needs. Then, based on the target running safety factor, the target safety range of the target robot at the target current position is determined. This safety range has a negative correlation with the target running safety factor, that is, the higher the running safety factor, the smaller the safety range; conversely, the larger the safety range. By reasonably delimiting the target safety range, it can instruct other robots in the robot cluster located within this range to avoid the target movement path in the target current task, thus effectively avoiding collisions and interferences between robots and ensuring the safety and smoothness of the robot cluster during collaborative work.

[0011] Optionally, the determining the target position constraint feature quantity of the target robot in the robot cluster according to the current position set includes:

[0012] According to the target current position of the target robot and the target end position of the target movement path to determine a target path influence feature quantity;

[0013] According to the target current position of the target robot and the current position set to determine a target movement influence feature quantity;

[0014] Determine the target position constraint feature quantity according to the target path influence feature quantity and the target motion influence feature quantity.

[0015] In the above solution, first, according to the target current position of the target robot and the end position of the target movement path, determine the target path influence feature quantity, thereby reflecting the possible path influence of the target robot on other robots during the movement process. By determining the target path influence feature quantity, it is possible to identify in advance the possible path conflicts that the target robot may have with other robots during the movement process, providing an important basis for subsequent obstacle avoidance and path planning. Based on the path influence feature quantity, resources within the cluster can be more reasonably allocated, such as adjusting the movement paths or task priorities of other robots, to minimize path conflicts and improve the overall operation efficiency. Secondly, in combination with the target current position of the target robot and the set of current positions (i.e., the current positions of all robots within the cluster), determine the target motion influence feature quantity, thereby comprehensively considering the relative positions and motion states between the target robot and other robots. By determining the target motion influence feature quantity, it is possible to dynamically evaluate the obstacles (i.e., other robots) that the target robot may encounter during the movement process and adjust its movement path accordingly to achieve dynamic obstacle avoidance. By considering the motion states of other robots, the system can more accurately plan the movement path of the target robot, reduce unnecessary waiting and pauses, and thus improve the collaborative operation efficiency of the entire cluster. Finally, in combination with the target path influence feature quantity and the target motion influence feature quantity, determine the target position constraint feature quantity. This process synthesizes the factors of path conflict and motion interference, providing a scientific basis for comprehensively evaluating the position constraints of the target robot within the cluster.

[0016] It can be seen that by calculating the target position constraint feature quantity, the system can accurately evaluate the degree of position constraint of the target robot within the cluster, providing strong support for subsequent task allocation and path planning. Based on the target position constraint feature quantity, the system can more reasonably set the safety range of the target robot to ensure its safety during the task execution process. At the same time, by instructing other robots within the cluster to avoid the target movement path, the collision risk is further reduced. By comprehensively considering the factors of path conflict and motion interference, the system can optimize the operation process of the entire cluster, reduce unnecessary waiting and conflicts, and thus improve the overall operation efficiency.

[0017] Optionally, the instructing other robots within the target safety range in the robot cluster to avoid the target movement path in the target current task includes:

[0018] If the task priority of the robot within the target safety range in the robot cluster is lower than the target task priority, then instruct the corresponding robot to move outside the target safety range.

[0019] In the above solution, after determining the target safety range of the target robot at its target current position, the task priorities of other robots within this range are first compared with the target task priority. If the task priorities of other robots are 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 perform resource scheduling based on the urgency and importance of the tasks. High-priority tasks can obtain the execution opportunity first, thus ensuring the timely completion of critical tasks. By instructing the robots with low-priority tasks to avoid, the system can reduce the path conflicts and waiting time between robots and improve the overall efficiency of the cluster operation. When the system decides to instruct a certain robot or some robots to move outside the target safety range, this decision is not static but dynamically adjusted according to the real-time positions and states of the robots within the cluster. The dynamic avoidance mechanism allows the system to make immediate responses and adjustments according to the real-time positions and states of the robots within 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 changeable task environments and emergencies.

[0020] It can be seen that by instructing the robots with low-priority tasks to avoid the robots with high-priority tasks, the system can optimize the operation process of the cluster, reduce unnecessary waiting and conflicts, and improve the overall operation efficiency. By ensuring that the target robot has sufficient safety range when performing tasks, the system can significantly reduce the risk of collisions and conflicts and enhance the safety of the robot cluster. Through reasonable comparison of task priorities and avoidance decisions, the system can utilize the resources within the cluster more efficiently and avoid waste and idleness of resources.

[0021] Optionally, determining the target constraint level of the target robot according to the target position constraint feature quantity and the preset constraint level range, and determining the target running 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:

[0022] Determining the target constraint level according to the target position constraint feature quantity and the preset constraint level range;

[0023] Determining the target running 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.

[0024] In the above solution, 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 constraint situation 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 during task execution, ensuring that high-priority tasks can be executed in a relatively safe environment. As the task priority and the cluster state change, the target operation safety factor can be dynamically adjusted to adapt to the safety requirements in different scenarios. In addition, in combination with the determination process of the target constraint level and the target operation safety factor, this method plays an important role in improving the management efficiency of the robot cluster and ensuring the safety of task execution.

[0025] It can be seen that by evaluating the operation safety factor of the target robot, the system can allocate tasks more reasonably, ensuring that high-priority and relatively safe tasks are executed first. By quantifying the constraint degree and calculating the operation safety factor in combination with the 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 solution provides a scientific decision-making basis for the cluster management system, enabling the system to make more reasonable scheduling and avoidance decisions more quickly and improving the overall decision-making efficiency.

[0026] Optionally, determining the target safety range of the target robot at the target current position according to the target operation safety factor includes:

[0027] Determining the target safety radius of the target robot at the target current position according to the target operation safety factor;

[0028] Determining the target safety range according to the target safety radius and the target current position.

[0029] In the above solution, first, according to the target operating safety factor of the target robot, the system determines the target safety radius. As an important indicator for measuring the safety of the target robot during task execution, the target operating 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 determining the subsequent safety range. The size of the target safety radius is dynamically adjusted with the change of the target operating 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 defines the area that other robots need to avoid to prevent 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 collisions and conflicts. A reasonable setting of the target safety range can optimize the cluster operation space, improve space utilization, and ensure operation safety. Combining the determination process of the target safety radius and the target safety range, the above solution plays an important role in improving the management efficiency of the robot cluster and ensuring the safety of task execution.

[0030] It can be seen that by accurately determining the target safety range, the system can significantly reduce the collision risk between robots and improve the safety of cluster operations. A reasonable safety range setting can reduce the waiting and avoidance time between robots and improve the task execution efficiency. In addition, it also provides clear avoidance rules and safety boundaries for the robot cluster, enhancing the coordination and consistency among the robots in the cluster.

[0031] Optionally, after determining the target safety range of the target robot at the target current position according to the target operating safety factor, the following steps are further included:

[0032] Determine the overall operating safety factor corresponding to the robot cluster according to the operating safety factors of each robot in the robot cluster;

[0033] If it is determined that the overall operating safety factor is less than the preset first overall operating safety factor threshold, send a warning message, and the warning message is used to indicate scheduling adjustment of the robot cluster.

[0034] In the above solution, first, based on the operation safety coefficients of each robot in the robot cluster, the overall operation safety coefficient corresponding to the robot cluster is determined. This process comprehensively considers the safety status of all robots in the cluster and provides a quantitative index for evaluating the overall safety of the cluster. By calculating the overall operation safety coefficient, the system can comprehensively evaluate the overall safety status of the robot cluster and identify potential safety risk points. The weight coefficients of different robots can be considered, making the calculation of the overall operation safety coefficient more scientific and reasonable, and accurately reflecting the importance of each robot in the cluster and its impact on the overall safety. When the system determines that the overall operation safety coefficient is less than the preset first overall operation safety coefficient threshold, a warning message will be automatically sent. This warning message is used to indicate scheduling adjustments to the robot cluster to prevent potential safety accidents. By sending the warning message in a timely manner, the system can notify the management personnel or automatically trigger the emergency response mechanism before the safety risk occurs, thus effectively avoiding the occurrence of safety accidents. In addition, the warning message not only indicates the existence of the safety risk, but also clearly points out that scheduling adjustments need to be made to the robot cluster, providing clear operation guidance for the management personnel. Combining the determination of the overall operation safety coefficient and the sending of the warning message, the above solution plays an important role in improving the management efficiency of the robot cluster and ensuring the overall safety of the cluster.

[0035] It can be seen that by real-time monitoring and evaluating the overall safety status of the cluster, the system can timely discover and respond to potential safety risks, thus significantly enhancing the safety of the robot cluster. The sending of the warning message prompts the management personnel to make scheduling adjustments to the robot cluster, optimize resource allocation, and improve the operation efficiency of the cluster. It also provides scientific decision-making support for the management personnel, enabling them to make more reasonable and accurate decisions based on quantitative indicators and data.

[0036] It should be noted that the calculation of the overall operation safety coefficient and the sending of the warning message are a dynamic monitoring process. As the cluster status and task requirements change, the system will continuously update the overall operation safety coefficient and send warning messages as needed. This dynamic monitoring mechanism helps to ensure that the robot cluster is always in a safe and efficient operation state and provides strong support for its continuous improvement.

[0037] Optionally, after determining that the overall operation safety coefficient is less than the preset first overall operation safety coefficient threshold, it further includes:

[0038] If it is determined that the overall operation safety factor is less than a preset second overall operation safety factor threshold, a pause operation instruction is sent to the robots in the robot cluster whose task priorities are lower than a preset priority level threshold. The pause operation instruction is used to instruct the robots 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.

[0039] In the above solution, when the overall operation safety factor drops below the preset threshold, it is crucial to take appropriate measures to quickly restore the safety state 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 robots with lower task priorities to achieve a rapid and safe adjustment of the cluster. When the overall operation safety factor is lower than the preset second threshold, it indicates that the robot cluster faces relatively serious safety risks. At this time, by pausing the operation of the robots whose task priorities are lower than the preset priority level threshold, the system can quickly reduce the dynamic elements in the cluster, thereby reducing safety risks such as collisions and interferences. Pausing 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 handling high-risk tasks or robots, the system can more effectively manage and control the overall safety of the cluster. Pausing low-priority tasks is not only to immediately reduce risks but also to provide an opportunity for subsequent task rescheduling and optimization. After pausing 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 priorities and safety conditions, the system can reallocate cluster resources to improve the overall operation efficiency.

[0040] In addition, while sending the pause operation instruction, the system may also instruct some robots to move to a predetermined position. This measure further enhances the flexibility and safety of cluster management. By instructing the robots to move to a predetermined position, the system can achieve an orderly evacuation and reorganization of the robots, avoiding chaos and collisions. The robots move to the designated position along the predetermined path, maintaining the orderliness of the cluster and reducing the safety risks caused by disorderly movement. By reasonably arranging the positions of the robots, the system can optimize the operation space of the cluster and improve the space utilization rate. Moving the robots to a predetermined position can also prepare for emergency response to ensure that rapid actions can be taken in case of emergencies. When the robots are in the predetermined positions, they can respond more quickly to emergency instructions or execute emergency tasks. The predetermined layout of the robot positions provides greater flexibility for the cluster to adapt to different task requirements and environmental changes.

[0041] In a second aspect, the present application provides a robot cluster management system, including:

[0042] An acquisition module, configured to acquire the working data of each robot in the robot cluster to form a working data set, where the working data set includes a current position set and a current task set;

[0043] A processing module, configured to determine a target position constraint feature quantity of a target robot in the robot cluster according to the current position set, where the target position constraint feature quantity is used to characterize the degree of constraint of the target robot by other robots in the robot cluster in the spatial dimension;

[0044] The processing module 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 running 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;

[0045] The processing module is further configured to determine a target safety range of the target robot at a target current position according to the target running safety factor, so as to instruct other robots located within the target safety range in the robot cluster to avoid a target movement path in the target current task, and the target safety range has a negative correlation with the target running safety factor.

[0046] Optionally, the processing module is specifically configured to:

[0047] Determine a target path influence feature quantity according to the target current position of the target robot and a target end position of the target movement path;

[0048] Determine a target movement influence feature quantity according to the target current position of the target robot and the current position set;

[0049] Determine the target position constraint feature quantity according to the target path influence feature quantity and the target movement influence feature quantity.

[0050] Optionally, the processing module is specifically configured to:

[0051] If the task priority of a robot located within the target safety range in the robot cluster is less than the target task priority, instruct the corresponding robot to move outside the target safety range.

[0052] Optionally, the processing module is specifically configured to:

[0053] Determine the target constraint level according to the target position constraint feature quantity and the preset constraint level range;

[0054] Determine the target operating 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.

[0055] Optionally, the processing module is specifically configured to:

[0056] Determine the target safety radius of the target robot at the target current position according to the target operating safety factor;

[0057] Determine the target safety range according to the target safety radius and the target current position.

[0058] Optionally, the processing module is specifically configured to:

[0059] Determine the overall operating safety factor corresponding to the robot cluster according to the operating safety factors of the robots in the robot cluster;

[0060] If it is determined that the overall operating safety factor is less than a preset first overall operating safety factor threshold, send a warning message, where the warning message is used to indicate scheduling adjustment of the robot cluster.

[0061] Optionally, the processing module is specifically configured to:

[0062] If it is determined that the overall operating safety factor is less than a preset second overall operating safety factor threshold, send a pause operation instruction to the robots in the robot cluster whose task priorities are lower than a preset priority level threshold, where the pause operation instruction is used to indicate that the robot pauses operation or moves to a predetermined position, and the preset second overall operating safety factor threshold is less than the preset first overall operating safety factor threshold.

[0063] In a third aspect, the present application provides an electronic device, including:

[0064] A processor; and,

[0065] A memory for storing executable instructions of the processor;

[0066] Wherein, the processor is configured to execute any possible method described in the first aspect by executing the executable instructions.

[0067] In a fourth aspect, the present application provides a computer-readable storage medium, where computer-executable instructions are stored in the computer-readable storage medium, and when the computer-executable instructions are executed by a processor, they are used to implement any possible method described in the first aspect.

[0068] The robot cluster management method, system, device, and medium provided by this application form a working data set by obtaining the working data of each robot in the robot cluster. 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. Next, 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 running 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. Furthermore, the target safety range of the target robot at the target current position is determined according to the target running safety factor, so as to instruct other robots within the target safety range in the robot cluster to avoid the target movement path in the target current task, thus effectively avoiding collisions and interferences between robots during the operation of the robot cluster and ensuring the safety and smoothness of the robot cluster during collaborative work. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] The accompanying drawings herein are incorporated into and constitute a part of this specification, showing embodiments consistent with this application, and are used together with the specification to explain the principles of this application.

[0070] Figure 1 is a schematic flowchart of a robot cluster management method shown according to an exemplary embodiment of this application;

[0071] Figure 2 is a schematic flowchart of a robot cluster management method shown according to another exemplary embodiment of this application;

[0072] Figure 3 is a schematic structural diagram of a robot cluster management system shown according to an exemplary embodiment of this application;

[0073] Figure 4 is a schematic structural diagram of an electronic device shown according to an exemplary embodiment of this application.

[0074] Through the above accompanying drawings, specific embodiments of this application have been shown, and there will be more detailed descriptions hereinafter. These drawings and written descriptions are not intended to limit the scope of the concept of this application in any way, but to illustrate the concept of this application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0075] Exemplary embodiments will be described in detail here, and examples are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. On the contrary, they are merely examples of devices and methods consistent with some aspects of this application as detailed in the appended claims.

[0076] To solve the above problems, the embodiments provided in this application form a complete set of working data by comprehensively obtaining the working data of each robot in the robot cluster, including key information such as the current position and task priority. This set of data provides a solid foundation for subsequent analysis and decision-making.

[0077] Based on the set of working data, the concept of the target position constraint feature quantity is further introduced. By calculating the target position constraint feature quantity of the target robot, the degree of constraint of the target robot 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 and provides a scientific basis for subsequent task scheduling and path planning.

[0078] After determining the target position constraint feature quantity, according to the preset constraint level range, the target constraint level of the target robot is determined. This step quantifies the spatial constraint relationship between robots into specific constraint levels and provides a quantitative indicator for subsequent decision-making. Then, in combination with the target task priority corresponding to the target current task in the current task set, the target running safety factor of the target robot is determined. This target running safety factor comprehensively considers the importance and urgency of the task, as well as the actual constraint situation of the target robot in the cluster, providing a strong guarantee for the safe operation of the robot.

[0079] Finally, according to the target running safety factor, the target safety range of the target robot at the target current position is determined. This safety range has a negative correlation with the target running safety factor, that is, the higher the running safety factor, the smaller the safety range; conversely, the larger the safety range. By reasonably delimiting the target safety range, it can indicate other robots in the robot cluster within this range to avoid the target movement path in the target current task, thus effectively avoiding collisions and interferences between robots and ensuring the safety and smoothness of the robot cluster during collaborative work.

[0080] Figure 1 is a schematic flowchart of a robot cluster management method shown according to an exemplary embodiment of this application. As Figure 1 shown, the robot cluster management method provided in this embodiment includes:

[0081] S101. Obtain the working data of each robot in the robot cluster to form a set of working data.

[0082] In this step, obtain the working data of each robot in the robot cluster to form a set of working data, and the set of working data includes a set of current positions and a set of current tasks.

[0083] Specifically, precise position information of each robot is obtained in real time through positioning sensors (such as GPS, lidar, vision sensors, etc.) integrated on the robot. This position information is usually represented in the form of three-dimensional coordinates and can accurately reflect the specific position of the robot in the working space.

[0084] Each robot will receive and execute specific tasks, such as handling, detection, assembly, etc. The current task set records information such as the type of task currently being executed by each robot, the task progress, and the task objectives. This information is crucial for subsequent task allocation and scheduling.

[0085] To more precisely calculate the relative motion between robots and the potential collision risk, the current velocity vector information of each robot can also be obtained. This information can be directly obtained through the motion sensors or controllers of the robot.

[0086] By integrating the above information, a working data set containing the current position set, the current task set (and optionally the current velocity vector set) is formed, providing basic data support for subsequent analysis and decision-making.

[0087] S102. Determine the target position constraint feature quantity of the target robot in the robot cluster according to the current position set.

[0088] 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, where the target position constraint feature quantity is used to characterize the degree of constraint of the target robot by other robots in the robot cluster in the spatial dimension.

[0089] Specifically, the target path influence feature quantity can be calculated according to the target current position of the target robot and the target end position of the target movement path. This feature quantity reflects the potential influence of the target robot's movement path on other robots. Then, according to 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 influence of the target robot's movement 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 of constraint of the target robot by other robots in the spatial dimension.

[0090] S103. 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.

[0091] 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, the maximum value, and the minimum value). Among them, a 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.

[0092] S104. Determine the target safety range of the target robot at the target current position according to the target operation safety factor.

[0093] 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 within the target safety range in the robot cluster to avoid the target movement path in the target current task. The target safety range and the target operation safety factor have a negative correlation.

[0094] Specifically, according to the target operation safety factor, the target safety radius corresponding to the target safety range of the target robot at the target current position is calculated. According to the calculated target safety range, other robots within this range in the robot cluster 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.

[0095] In a possible implementation, if the task priority of the robots within the target safety range in the robot cluster is lower than the target task priority, the corresponding robots are instructed to move outside the target safety range. Specifically, after each robot receives the broadcast message, it first confirms whether it is within the target safety range. It obtains its current position information through its own positioning sensors (such as GPS, lidar, etc.) and compares it with the boundary coordinates of the target safety range. Each robot simultaneously obtains its own task priority information. It 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 a robot confirms that it is within the target safety range and its task priority is lower than the target task priority, it generates an avoidance instruction. The avoidance instruction should include key information such as the identifier of the target robot, the avoidance direction, and the 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, the robot should continuously monitor the distance from the target safety range to ensure that it does not enter the range again. During the process of the robot moving and avoiding, it may involve the path planning and coordination of multiple robots. The system should monitor the movement status of the robots in real time to avoid collisions and interferences between the robots. If there are path conflicts or difficulties in avoidance, the system should adjust the avoidance instruction in a timely manner or re-plan the avoidance path. The system should continuously monitor the avoidance effect to ensure that the target robot can execute 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.

[0096] In this embodiment, by obtaining the working data of each robot in the robot cluster to form a working data set, then, determining 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 determining 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 coefficient 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 further determining the target safety range of the target robot at the target current position according to the target operation safety coefficient, to instruct other robots within the target safety range in the robot cluster to avoid the target movement path in the target current task, thus effectively avoiding collisions and interferences between robots during the work of the robot cluster, and ensuring the safety and smoothness of the robot cluster during collaborative work.

[0097] Figure 2 is a schematic flowchart of a robot cluster management method according to another exemplary embodiment of the present application. As Figure 2 shown, the robot cluster management method provided in this embodiment includes:

[0098] S201. Obtain the working data of each robot in the robot cluster to form a working data set.

[0099] In this step, obtain the working data of each robot in the robot cluster to form a working data set, where the working data set includes a current position set and a current task set.

[0100] Specifically, the precise position information of each robot is obtained in real time through positioning sensors (such as GPS, lidar, vision sensors, etc.) integrated on the robot. These position information is usually represented in the form of three-dimensional coordinates, which can accurately reflect the specific position of the robot in the working space.

[0101] Each robot will receive and execute specific tasks, such as handling, detection, assembly, etc. The current task set records information such as the type of task currently being executed by each robot, the task progress, and the task goal. This information is crucial for subsequent task allocation and scheduling.

[0102] To more precisely calculate the relative motion between robots and the potential collision risk, the current velocity vector information of each robot can also be obtained. This information can be directly obtained through the motion sensors or controllers of the robots.

[0103] By integrating the above information, a working data set containing the current position set, the current task set (and optionally the current velocity vector set) is formed, providing basic data support for subsequent analysis and decision-making.

[0104] S202. Determine the target position constraint feature quantity of the target robot in the robot cluster according to the current position set.

[0105] In this step, determine the target position constraint feature quantity of the target robot in the robot cluster according to the current position set, where the target position constraint feature quantity is used to characterize the degree of constraint of the target robot by other robots in the robot cluster in the spatial dimension.

[0106] In a possible implementation, use Formula 1 and according to the target current position of the target robot and the target end position of the target movement path to determine the target path influence feature quantity , where Formula 1 is:

[0107]

[0108] Among them, is the path influence gain coefficient;

[0109] Use Formula 2 and according to the target current position of the target robot and the current position set Determine the target motion influence feature quantity , where Formula 2 is:[[]]

[0110]

[0111] Among them, is the motion influence gain coefficient, is the current position set The current position of any robot other than the target robot in is the motion influence range between the target robot and other robots;

[0112] Using Formula 3 and based on the target path influence feature quantity and the target motion influence feature quantity Determine the target position constraint feature quantity , where Formula 3 is:[[]]

[0113]

[0114] Among them, is the gradient operator, is the number of robots in the robot cluster, is the th robot's current position among the robots in the robot cluster other than the target robot.

[0115] Formula 1 obtains the target path influence feature quantity by calculating the square of the Euclidean distance between the current position of the target robot and the target end position and multiplying it by the path influence gain coefficient. This feature quantity reflects the potential influence of the target robot's moving path on other robots and provides an important basis for calculating the target position constraint feature quantity later. By introducing the path influence gain coefficient, the size of the path influence can be adjusted according to the actual situation, making the calculation result more in line with the requirements of the actual scenario.

[0116] Formula 2 takes different values according to 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 based on the comparison result between this distance and the maximum motion influence range, the target motion influence feature quantity is obtained. This feature quantity reflects the potential influence of the target robot's motion on other robots. Especially when the target robot approaches other robots, its motion influence will increase significantly. By introducing the maximum motion influence range and the motion influence gain coefficient, the influence of the target robot's motion on other robots can be quantified more precisely, providing more accurate data support for calculating the target position constraint feature quantity later.

[0117] Formula 3 obtains the target position constraint feature quantity by calculating the gradient of the target path influence feature quantity and the negative value of the sum of the gradients of all target motion influence feature quantities. This feature quantity comprehensively reflects the degree of constraint of the target robot by other robots in the spatial dimension, providing key data for 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 constraint of the target robot by other robots in the spatial dimension can be described more precisely. At the same time, by accumulating the gradients of all target motion influence feature quantities, the influence of all other robots in the cluster on the target robot can be comprehensively considered to ensure the accuracy and reliability of the calculation results.

[0118] Further, before determining the target path influence feature quantity according to the current target position of the target robot and the target end position of the target movement path it is also possible to use Formula 4 to determine the target path dynamic influence factor according to the current position set , and Formula 4 is:

[0119]

[0120] where is the preset safety distance corresponding to the target task priority, is the safety distance attenuation coefficient corresponding to the target task priority, is the distance between the th robot other than the target robot in the robot cluster and the target robot, is the distance attenuation coefficient corresponding to the larger task priority between the task priority of the th robot other than the target robot in the robot cluster and the target task priority, is the first preset coefficient, is the second preset coefficient;

[0121] Using Formula 5, and according to the target path dynamic influence factor and the preset basic path influence gain coefficient determine the path influence gain coefficient , and Formula 5 is:

[0122]

[0123] where is the third preset coefficient.

[0124] The above formula 4 comprehensively considers multiple factors such as the target task priority, safety distance, the distance between other robots and the target robot, and the task priorities of other robots, and calculates the dynamic influence factor of the target path. This factor reflects the dynamic degree to which the movement path of the target robot is affected by other robots under the current task priority and robot distribution scenario. By introducing a safety distance attenuation coefficient and a preset coefficient, it can flexibly adapt to the requirements under different task priorities and robot distribution scenarios, making the calculated dynamic influence factor of the target path more accurate and reliable.

[0125] The above formula 5 dynamically adjusts the preset basic path influence gain coefficient according to the calculated dynamic influence factor of the target path to obtain the path influence gain coefficient. This coefficient reflects the intensity of the influence of the movement path of the target robot 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 change more reasonable and controllable under different dynamic influence factors of the target path. This dynamic adjustment mechanism helps to more accurately quantify the influence of the movement path of the target robot on other robots, providing more accurate data support for the subsequent calculation of the target path influence characteristic quantity.

[0126] It can be seen that by introducing the dynamic adjustment mechanism of the dynamic influence factor of the target path and the path influence gain coefficient, the target path influence 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 requirements under different task priorities and robot distribution scenarios, making the robot cluster management method more general and practical. Based on the more accurate target path influence characteristic quantity, the robot cluster management system can make more reasonable task allocation and scheduling decisions, improving the overall work efficiency and safety of the cluster.

[0127] Furthermore, the working data set includes the current speed set. Correspondingly, before determining the target motion influence characteristic quantity based on the target current position of the target robot and the current position set, it is also possible to use formula 6 and determine the motion influence gain coefficient according to the current speed set and the preset basic motion influence gain coefficient The formula 6 is as follows: where

[0128]

[0129] is the th robot in the robot cluster other than the target robot determined based on the current speed set The relative speed between a robot and the target robot, is the preset maximum speed threshold, is the relative speed direction angle between the th robot in the robot cluster except the target robot and the target robot, is the preset speed sensitivity coefficient, is the preset direction sensitivity coefficient.

[0130] In the above formula 6, the relative speed magnitude between the target robot and other robots, as well as the preset speed sensitivity coefficient and direction sensitivity coefficient, are comprehensively considered to calculate the motion influence gain coefficient. This coefficient reflects the intensity of the influence of the target robot's motion on other robots under the current speed distribution and relative motion state. By introducing two factors, the relative speed magnitude and the direction angle, and combining the speed sensitivity coefficient and the direction sensitivity coefficient for weighted summation, formula 6 can more comprehensively evaluate the potential influence of the target robot's motion on other robots. At the same time, the preset basic motion influence gain coefficient provides a benchmark value, making the calculation results more stable and reliable.

[0131] By dynamically calculating the motion influence gain coefficient, the influence of the target robot's motion on other robots can be more accurately quantified. This helps to more precisely reflect the spatial relationship and dynamic interaction between the target robot and other robots when calculating the target motion influence characteristic quantity. Since the motion influence gain coefficient is dynamically calculated based on the current speed set, it can adapt to scenarios under different speed distributions and relative motion states. This enables the robot cluster management method to maintain high calculation accuracy and robustness in different environments.

[0132] Based on the more accurate target motion influence characteristic quantity, the robot cluster management system can more reasonably allocate tasks to each robot, avoiding task conflicts and potential collision risks. By precisely evaluating the influence of the target robot's motion on other robots, the robot cluster management system can optimize the motion paths and speeds of the robots, reducing unnecessary waiting and stagnation times, thereby improving the operating efficiency of the entire cluster. Dynamically calculating the motion influence gain coefficient and applying it to the calculation of the target motion influence characteristic quantity helps to identify and prevent potential safety risks in advance, ensuring the safe operation of the robot cluster in complex environments.

[0133] S203. Determine the target constraint level of the target robot according to the target position constraint characteristic quantity and the preset constraint level range, so as to determine the target operation safety coefficient 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.

[0134] Specifically, formula 7 can be used and according to the target position constraint characteristic quantity and determine the target constraint level within the preset constraint level range , Formula 7 is as follows:

[0135]

[0136] where is the quantification function of the th preset constraint condition, is the number of quantification functions of the preset constraint conditions, is the preset weight of the th constraint condition, 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;

[0137] Using Formula 8, and based on the target constraint level and the target task priority corresponding to the target current task in the current task set determine the target operating safety factor of the target robot , Formula 8 is as follows:

[0138]

[0139] where is the average value of all preset constraint levels, is the maximum value of the task priority, is the first adjustment parameter, used to adjust the sensitivity of the target operating safety factor to the constraint level, is the second adjustment parameter, used to adjust the sensitivity of the target operating safety factor to the task priority.

[0140] Formula 7 comprehensively considers multiple constraint condition quantification functions and their weights. By means of weighted average and logarithmic transformation, it maps the target position constraint feature quantity to the preset constraint level range, and obtains the target constraint level. This process makes the determination of the target constraint level more scientific and reasonable, and can more accurately reflect the constrained degree of the target robot in the cluster. By introducing the weight coefficient, Formula 7 can perform differential processing according to the importance and influence degree of different constraint conditions, improving the accuracy and flexibility of the 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.

[0141] Formula 8 calculates the target operating safety factor in the form of a logistic function based on the target constraint level and the current task priority. The value range of the target operating safety factor is (0, 1), which can intuitively reflect the operating safety status of the target robot under the current task and environment. When the target constraint level is high or the target task priority is high, the value of the target operating safety factor will decrease accordingly, indicating an increase in the operating safety risk of the target robot; conversely, it indicates a decrease in the operating safety risk. In addition, by introducing a tuning parameter, Formula 8 can flexibly adjust the sensitivity of the target operating safety factor to the constraint level and task priority according to the requirements of different application scenarios. This enables the robot cluster management system to more accurately evaluate the operating safety status of the target robot under different tasks and environments, providing strong support for task allocation and scheduling decisions.

[0142] It can be seen that by comprehensively considering multiple constraint conditions and their weights, and introducing the logistic function to calculate the target operating safety factor, the present invention can more accurately evaluate the operating safety status of the target robot in the cluster. By introducing a tuning parameter and a flexible constraint level calculation method, it can adapt to the requirements under different tasks and environments, improving the generality and practicality of the robot cluster management method. Moreover, based on the more accurate operating safety assessment results, the robot cluster management system can make more reasonable task allocation and scheduling decisions, improving the overall working efficiency and safety of the cluster.

[0143] S204. Determine the target safety range of the target robot at the target current position according to the target operating safety factor.

[0144] In this step, the target safety range of the target robot at the target current position is determined according to the target operating safety factor, so as to instruct other robots in the robot cluster within the target safety range to avoid the target movement path in the target current task. The target safety range has a negative correlation with the target operating safety factor.

[0145] Specifically, it can be to use Formula 9 and determine the target safety radius corresponding to the target safety range of the target robot at the target current position according to the target operating safety factor The formula 9 is: where,

[0146]

[0147] is 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 is the current speed of the target robot, is the maximum speed of the target robot, is the speed adjustment factor, which is used to adjust the influence degree of the robot speed on the safety range.

[0148] Formula 9 comprehensively considers the target operation safety factor, the average expected distance of the 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 safety operation requirements of the target robot in the current task and environment. By introducing the speed adjustment factor, Formula 9 can perform differential processing according to the safety risks at different speeds, making the calculation result of the target safety radius 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 safety operation requirements of the target robot in the cluster.

[0149] Moreover, by dynamically calculating the target safety radius, a more accurate safety range can be provided for the target robot, thereby effectively avoiding collisions and interferences 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 cooperate according to the target safety range, improving 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 requirements in different tasks and environments. This makes the robot cluster management method maintain high safety and adaptability in different scenarios.

[0150] In addition, by comprehensively considering multiple factors such as the target operation safety factor, average expected distance, and speed, the safety 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 operation situations and task requirements, improving the flexibility and robustness of the system. Based on the more accurate target safety range, each robot in the robot cluster can better cooperate, improving the overall efficiency and safety of the cluster.

[0151] S205. Determine the overall operation safety factor corresponding to the robot cluster according to the operation safety factors of each robot in the robot cluster.

[0152] Specifically, use Formula 10 and determine the overall operation safety factor corresponding to the robot cluster according to the operation safety factors of each robot in the robot cluster Formula 10 is:

[0153]

[0154] Among them, is the running safety factor of the th robot in the robot cluster, is the weight factor of the th robot in the robot cluster, is a preset adjustment factor used to adjust the influence degree of task priority on the overall running safety factor, is the task priority of the th robot in the robot cluster, is the actual distance between the th robot and the th robot in the robot cluster, is the expected safety distance between the th robot and the th robot in the robot cluster.

[0155] S206. Send a warning message or a suspension operation instruction.

[0156] In a possible situation, if it is determined that the overall running safety factor is less than the preset first overall running safety factor threshold, then send a warning message, and the warning message is used to indicate scheduling adjustment for the robot cluster.

[0157] In the above solution, Formula 10 comprehensively considers the running safety factor, weight factor, task priority of each robot in the robot cluster, as well as the actual distance and expected safety distance between robots. Through the methods of weighted average and exponential transformation, the overall running safety factor of the robot cluster is calculated. This process can comprehensively reflect the overall running safety state of the robot cluster under the current task and environment. By introducing the weight factor and task priority, Formula 10 can perform differential processing according to the importance and task urgency of different robots in the cluster, improving the accuracy and rationality of the calculation of the overall running 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 risk of the robot cluster.

[0158] If it is determined that the overall operating safety factor is less than the preset first overall operating safety factor threshold, a warning message is sent. By setting warning conditions, it is possible to send a warning message in a timely manner when the overall operating safety status of the robot cluster is lower than the preset threshold, prompting scheduling adjustments to the robot cluster. This process can effectively avoid task failures or safety accidents caused by excessive operating safety risks in the robot cluster. The introduction of the warning decision-making mechanism enables the robot cluster management system to actively identify and respond to potential safety risks, improving the system's response speed and safety. At the same time, by setting reasonable warning thresholds, the accuracy and effectiveness of warning messages can be ensured, avoiding unnecessary interference and false alarms.

[0159] It can be seen that by comprehensively evaluating the overall operating safety status of the robot cluster and setting 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 operating safety factor, the robot cluster management system can more reasonably plan task allocation and scheduling strategies, improving the overall work efficiency and performance of the cluster. By introducing the warning decision-making mechanism, the robot cluster management system can better respond to complex and changing environments and task requirements, improving the system's robustness and adaptability.

[0160] In another possible scenario, if it is determined that the overall operating safety factor is less than the preset second overall operating safety factor threshold, a suspension instruction is sent to the robots in the robot cluster whose task priorities are lower than the preset priority level threshold. The suspension instruction is used to instruct the robot to suspend operation or move to a predetermined position, and the preset second overall operating safety factor threshold is less than the preset first overall operating safety factor threshold.

[0161] In the above solution, when the overall operating safety factor drops below the preset threshold, it is crucial to take appropriate measures to quickly restore the safe state of the cluster. When the overall operating 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 suspension instruction to the robots with lower task priorities to achieve a rapid and safe adjustment of the cluster. When the overall operating safety factor is lower than the preset second threshold, it indicates that the robot cluster faces relatively serious safety risks. At this time, by suspending the operation of the robots with task priorities lower than the preset priority level threshold, the system can quickly reduce the dynamic elements in the cluster, thereby reducing safety risks such as collisions and interferences. 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 handling 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 immediately reduce risks but also to provide opportunities for subsequent task rescheduling and optimization. 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 priorities and safety conditions, the system can reallocate cluster resources to improve the overall operating efficiency.

[0162] In addition, while sending the suspension instruction, the system may also instruct some robots to move to predetermined positions, which further enhances the flexibility and safety of cluster management. By instructing the robots to move to predetermined positions, the system can achieve an orderly evacuation and reorganization of the robots, avoiding chaos and collisions. The robots move to the designated positions along the predetermined paths, maintaining the orderliness of the cluster and reducing the safety risks caused by disorderly movement. By reasonably arranging the positions of the robots, the system can optimize the operation space of the cluster and improve the space utilization rate. Moving the robots to predetermined positions can also prepare for emergency response to ensure that rapid actions can be taken in case of emergencies. When the robots are in predetermined positions, they can respond more quickly to emergency instructions or perform emergency tasks. The predetermined layout of the robot positions provides greater flexibility for the cluster to adapt to different task requirements and environmental changes.

[0163] It can be seen that by suspending the operation of low-priority robots and instructing them to move to predetermined positions, 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 task execution efficiency. By re-scheduling and optimizing task priorities, it ensures that critical tasks are processed in a timely and effective manner.

[0164] It should be noted that this measure is not applied once for all, but is dynamically adjusted according to the changes in the cluster state and task requirements. The system will continuously monitor the overall operation safety factor and send instructions to suspend operation or direct 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 the continuous improvement and optimization of the robot cluster.

[0165] Figure 3 It is a schematic structural diagram of a robot cluster management system shown according to an exemplary embodiment of the present application. As Figure 3 shown, the robot cluster management system 300 provided in this embodiment includes:

[0166] An acquisition module 310, configured to acquire the working data of each robot in the robot cluster to form a working data set, where the working data set includes a current position set and a current task set;

[0167] A processing module 320, configured to determine a target position constraint feature quantity of a target robot in the robot cluster according to the current position set, where the target position constraint feature quantity is used to characterize the degree of constraint of the target robot by other robots in the robot cluster in the spatial dimension;

[0168] 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, and determine a 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;

[0169] The processing module 320 is further configured to determine a target safety range of the target robot at the target current position according to the target operation safety factor, and instruct other robots in the robot cluster located within the target safety range to avoid the target movement path in the target current task, and the target safety range has a negative correlation with the target operation safety factor.

[0170] Optionally, the processing module 320 is specifically configured to:

[0171] According to the target current position of the target robot and the target end position of the target movement path, determine a target path influence feature quantity;

[0172] According to the target current position of the target robot and the current position set, determine a target movement influence feature quantity;

[0173] Determine the target position constraint feature quantity according to the target path influence feature quantity and the target movement influence feature quantity.

[0174] Optionally, the processing module 320 is specifically configured to:

[0175] If the task priority of the robots within the target safety range in the robot cluster is lower than the target task priority, instruct the corresponding robots to move outside the target safety range.

[0176] Optionally, the processing module 320 is specifically configured to:

[0177] Determine the target constraint level according to the target position constraint feature quantity and the preset constraint level range;

[0178] Determine the target running 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.

[0179] Optionally, the processing module 320 is specifically configured to:

[0180] Determine the target safety radius of the target robot at the target current position according to the target running safety factor;

[0181] Determine the target safety range according to the target safety radius and the target current position.

[0182] Optionally, the processing module 320 is specifically configured to:

[0183] Determine the overall running safety factor corresponding to the robot cluster according to the running safety factors of the robots in the robot cluster;

[0184] If it is determined that the overall running safety factor is less than a preset first overall running safety factor threshold, send a warning message, where the warning message is used to indicate scheduling adjustment of the robot cluster.

[0185] Optionally, the processing module 320 is specifically configured to:

[0186] If it is determined that the overall running safety factor is less than a preset second overall running safety factor threshold, send a pause running instruction to the robots in the robot cluster whose task priorities are lower than a preset priority level threshold, where the pause running instruction is used to instruct the robots to pause running or move to a predetermined position, and the preset second overall running safety factor threshold is less than the preset first overall running safety factor threshold.

[0187] Figure 4 It is a schematic structural diagram of an electronic device shown according to an exemplary embodiment of the present application. As Figure 4As shown in the figure, an electronic device 400 provided in this embodiment includes: a processor 401 and a memory 402; where:

[0188] The memory 402 is used to store computer programs, and this memory can also be a flash (flash memory).

[0189] The processor 401 is used to execute the execution instructions stored in the memory to implement each step in the above method. For specific details, please refer to the relevant descriptions in the previous method embodiments.

[0190] Optionally, the memory 402 can be either independent or integrated with the processor 401.

[0191] When the memory 402 is a device independent of the processor 401, the electronic device 400 may further include:

[0192] A bus 403 for connecting the memory 402 and the processor 401.

[0193] This embodiment also provides a readable storage medium, in which a computer program is stored. When at least one processor of the electronic device executes this computer program, the electronic device executes the methods provided by the above various embodiments.

[0194] 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 this computer program from the readable storage medium, and the execution of this computer program by at least one processor enables the electronic device to implement the methods provided by the above various embodiments.

[0195] After considering the specification and practicing the invention disclosed herein, those skilled in the art will readily think of other embodiments of the present application. The present application is intended to cover any variations, uses, or adaptations of the present application, which follow the general principles of the present application and include common general knowledge or conventional technical means in the technical field not disclosed in the present application. The specification and embodiments are only regarded as exemplary, and the true scope and spirit of the present application are pointed out by the claims.

[0196] It should be understood that the present application is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present application is only limited by the appended claims.

Claims

1. A method for managing a robot cluster, characterized in that, Including: Obtaining the working data of each robot in the robot cluster to form a working data set, where the working 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, where the target position constraint feature quantity is used to characterize the degree of constraint of the target robot by other robots in the robot cluster in the 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, 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 a target current task in the current task set; Determining a target safety range of the target robot at a target current position according to the target operation safety factor, so as to instruct other robots in the robot cluster located within the target safety range to avoid a target movement path in the target current task, and the target safety range has a negative correlation with the target operation safety factor; The determining the target safety range of the target robot at the target current position according to the target operation safety factor includes: Using formula 9 and based on the target operating safety factor S target Determine the target safety radius W corresponding to the target safety range of the target robot at the target current position safe , and the formula 9 is: Among them, W base is the basic safety radius corresponding to the basic safety range, S min is the minimum value of the operating safety factor, S max is the maximum value of the operating safety factor, D avg is the current average expected distance of all robots in the robot cluster, v target is the current speed of the target robot, v max is the maximum speed of the target robot, and γ is the speed adjustment factor used to adjust the influence degree of the robot speed on the safety range.

2. The robot cluster management method according to claim 1, wherein The determining the target position constraint feature quantity of the target robot in the robot cluster according to the current position set includes: Determining a target path influence feature quantity according to the target current position q of the target robot and a target end position of the target movement path; Determining a target movement influence feature quantity according to the target current position of the target robot and the current position set; Determining the target position constraint feature quantity according to the target path influence feature quantity and the target movement influence feature quantity.

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

4. The robot cluster management method according to any one of claims 1-3, characterized in that, The determining 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 includes: Determining the target constraint level according to the target position constraint feature quantity and the preset constraint level range; 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.

5. The robot cluster management method according to claim 1, wherein, After the determining the target safety range of the target robot at the target current position according to the target operation safety factor, it 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, and the warning message is used to indicate scheduling adjustment of the robot cluster.

6. The robot cluster management method according to claim 5, wherein, After it is determined that the overall operation safety factor is less than the preset first overall operation safety factor threshold, it further includes: If it is determined that the overall operation safety factor is less than a preset second overall operation safety factor threshold, a pause operation instruction is sent to the robots in the robot cluster whose task priorities are lower than a preset priority level threshold. The pause operation instruction is used to indicate that the robot pauses operation or moves to a predetermined position, and the preset second overall operation safety factor threshold is less than the preset first overall operation safety factor threshold.

7. A robot cluster management system, characterized in that, It includes: An acquisition module, configured to acquire the working data of each robot in the robot cluster to form a working data set, and the working data set includes a current position set and a current task set; A processing module, configured to determine a target position constraint feature quantity of a target robot in the robot cluster according to the current position set, where the target position constraint feature quantity is used to characterize the degree of constraint of the target robot by other robots in the robot cluster in the spatial dimension; The processing module 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 the target task priority corresponding to the target current task in the current task set; The processing module is further configured to determine a 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 located within the target safety range to avoid the target movement path in the target current task, and the target safety range has a negative correlation with the target operation safety factor; The processing module is specifically configured to: Using formula 9 and based on the target running safety factor S target Determine the target safety radius W corresponding to the target safety range of the target robot at the target current position safe , where formula 9 is: Among them, W base is the basic safety radius corresponding to the basic safety range, S min is the minimum value of the operating safety factor, S max is the maximum value of the operating safety factor, D avg is the current average expected distance of all robots in the robot cluster, v target is the current speed of the target robot, v max is the maximum speed of the target robot, and γ is the speed adjustment factor used to adjust the influence degree of the robot speed on the safety range.

8. An electronic device, characterized in that, It includes: A processor; And, A memory, configured to store executable instructions of the processor; Wherein, the processor is configured to execute the method according to any one of claims 1 to 6 by executing the executable instructions.

9. A computer-readable storage medium, characterized in that, Computer-executable instructions are stored in the computer-readable storage medium, and when the computer-executable instructions are executed by a processor, they are used to implement the method according to any one of claims 1 to 6.

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