Robot task conflict processing method and device, robot and storage medium

Abstract

The invention relates to a robot control technology, and discloses a robot task conflict processing method and device, a robot and a storage medium, and the method comprises the steps: classifying related tasks when the robot receives a plurality of task instructions, and giving initial priorities according to task types and emergency degrees; for each related task, an RRT path planner is called to calculate the motion trail of the mechanical arm; performing path overlapping degree evaluation on the motion trails among different tasks; wherein if the path distance between the evaluated motion tracks is smaller than a set threshold value, it is judged that space-time conflicts exist between the related tasks; if space-time conflicts exist between the related tasks, task priorities are adjusted; performing task arbitration according to a priority adjustment result, and selecting a corresponding arbitration strategy; and controlling the robot to execute a corresponding task according to the arbitration strategy. According to the method, when the robot receives a plurality of task instructions at the same time, task conflicts are avoided while efficient processing of tasks is guaranteed.

Description

Technical Field

[0001] The present application relates to the technical field of robot control, and particularly relates to a method for handling robot task conflicts, a control device, a robot, and a computer-readable storage medium. Background Art

[0002] In application scenarios of various robots such as domestic service robots, industrial robots, and entertainment robots, robots usually need to process multiple tasks simultaneously, such as functional tasks (such as lighting adjustment, object handling) and emotional expression tasks (such as dancing, expression display).

[0003] When a robot needs to process multiple tasks simultaneously, the action paths of different tasks may overlap in space, resulting in action conflicts. Especially for non-humanoid robots with worse action flexibility than humanoid robots, task action conflicts are more likely to occur. For example, when the robot tries to dance while adjusting the lighting, the movement trajectories of the robotic arms may interfere with each other, even leading to task failure or abnormal robot actions.

[0004] The above content is only used to assist in understanding the technical solution of the present application, and does not represent an admission that the above content is prior art. Summary of the Invention

[0005] The main purpose of the present application is to provide a method for handling robot task conflicts, a control device, a robot, and a computer-readable storage medium, aiming to ensure the efficient processing of tasks while avoiding task conflicts when the robot receives multiple task instructions simultaneously.

[0006] To achieve the above purpose, the present application provides a method for handling robot task conflicts, including the following steps:

[0007] When the robot receives multiple task instructions, classify the relevant tasks and assign initial priorities according to the task type and urgency; wherein, the task type includes functional tasks and emotional expression tasks;

[0008] For each relevant task, call an RRT (Rapidly-exploring Random Trees) path planner to calculate the movement trajectory of the robotic arm;

[0009] Evaluate the path overlap degree of the movement trajectories between different tasks; wherein, if the path distance between the evaluated movement trajectories is less than a set threshold, it is determined that there is a spatio-temporal conflict between the relevant tasks;

[0010] If there are spatio-temporal conflicts between related tasks, the task priorities are adjusted; among them, for urgent functional tasks, they are adjusted to the highest priority; for non-urgent functional tasks, the priorities are dynamically adjusted according to the task execution progress and task importance.

[0011] Task arbitration is performed according to the priority adjustment result, and the corresponding arbitration strategy is selected; among them, if the conflicting tasks involve urgent functional tasks, the emergency interruption strategy is adopted to give priority to executing the urgent functional tasks; if the conflicting tasks do not involve urgent functional tasks, the smooth transition strategy is adopted, and each task is executed in turn according to the priority, and a smooth transition frame is inserted during task switching.

[0012] Control the robot to execute the corresponding tasks according to the arbitration strategy.

[0013] Optionally, during the process of the RRT path planner calculating the motion trajectory, first set the task start point and end point, and add the start point as the initial node to the path tree.

[0014] Randomly generate sampling points in the task space.

[0015] Find the node closest to the sampling point in the generated path tree.

[0016] Expand the path from the nearest node towards the sampling point to generate a new node.

[0017] Optimize the path through local optimization methods.

[0018] Optionally, the adjustment formula adopted by the algorithm for dynamically adjusting the priority is:

[0019] Priority new =Priority old +α×Progress―β×Importance;

[0020] Among them, Priority old is the original priority; α and β are adjustment coefficients dynamically set according to the task type and scenario; Progress is the task execution progress, and the value range is [0,1]; Importance is the task importance, and the value range is [0,1].

[0021] Optionally, the method for handling robot task conflicts further includes:

[0022] If the conflicting tasks involve non-urgent functional tasks and emotional expression tasks, and the emotional expression task is a social task, the action fusion technology is adopted to organically combine the emotional expression task with the functional task.

[0023] Optionally, after the step of controlling the robot to execute corresponding tasks according to the arbitration strategy, the method further includes:

[0024] After the task is completed, generate feedback data according to the task execution situation;

[0025] Optimize the algorithm for dynamically adjusting priorities and / or the RRT path planner according to the feedback data.

[0026] Optionally, the method for handling robot task conflicts further includes:

[0027] During the task execution process, continuously monitor the path overlap degree between different tasks to monitor whether there are new spatio-temporal conflicts between different tasks;

[0028] If so, return to execute the step of adjusting the task priority if there are spatio-temporal conflicts between related tasks.

[0029] Optionally, after the step of evaluating the path overlap degree of the motion trajectories between different tasks, the method further includes:

[0030] If there are no spatio-temporal conflicts between related tasks, control the robot to execute the related tasks simultaneously.

[0031] To achieve the above object, the present application further provides a control device, including:

[0032] A task initialization module, configured to classify related tasks when the robot receives multiple task instructions, and assign initial priorities according to the task type and urgency; wherein, the task type includes functional tasks and emotional expression tasks;

[0033] An RRT path planner module, configured to, for each related task, call the RRT path planner to calculate the motion trajectory of the robotic arm;

[0034] A spatio-temporal conflict detection module, configured to evaluate the path overlap degree of the motion trajectories between different tasks; wherein, if the path distance between the evaluated motion trajectories is less than a set threshold, it is determined that there are spatio-temporal conflicts between related tasks;

[0035] A dynamic priority algorithm module, configured to adjust the task priority if there are spatio-temporal conflicts between related tasks; wherein, for urgent functional tasks, adjust them to the highest priority; for non-urgent functional tasks, dynamically adjust the priority according to the task execution progress and task importance;

[0036] A task arbitration module, which is used to perform task arbitration according to the priority adjustment result and select the corresponding arbitration strategy. Among them, if the conflicting tasks involve urgent functional tasks, an emergency interruption strategy is adopted to give priority to executing the urgent functional tasks. If the conflicting tasks do not involve urgent functional tasks, a smooth transition strategy is adopted to execute each task in sequence according to the priority, and smooth transition frames are inserted during task switching.

[0037] An execution task module, which is used to control the robot to execute the corresponding task according to the arbitration strategy.

[0038] A feedback and optimization module, which is used to generate feedback data according to the task execution situation after the task is completed; and optimize the algorithm for dynamically adjusting the priority and / or the RRT path planner according to the feedback data.

[0039] To achieve the above object, the present application also provides a robot, which includes: a memory, a processor, and a computer program stored on the memory and executable on the processor. When the computer program is executed by the processor, the steps of the method for handling robot task conflicts as described above are implemented.

[0040] To achieve the above object, the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method for handling robot task conflicts as described above are implemented.

[0041] The method for handling robot task conflicts, control device, robot, and computer-readable storage medium provided by the present application calculate the manipulator motion trajectory through the RRT path planner, evaluate the path overlap degree, can detect the spatio-temporal conflicts between tasks in real time, and then adjust the task priorities to ensure the efficient and orderly processing of tasks, effectively solve the problem of task conflicts, and avoid the occurrence of action jams, task interruptions, and mechanical failures caused by overlapping task paths of the robot. At the same time, it can respond quickly in case of emergencies. Moreover, different arbitration strategies are adopted during task execution, especially the smooth transition strategy, which can insert smooth transition frames during task switching, enabling the robot to more naturally integrate emotional expression actions when performing functional tasks, greatly enhancing the social interaction experience with users. Description of the Drawings

[0042] Figure 1 It is a schematic diagram of the steps of the method for handling robot task conflicts in an embodiment of the present application.

[0043] Figure 2 It is a schematic diagram of the dynamic priority adjustment process in the method for handling robot task conflicts in an embodiment of the present application.

[0044] Figure 3Schematic diagram of the task arbitration process in the method for handling robot task conflicts in an embodiment of the present application;

[0045] Figure 4 Schematic diagram of a control device in an embodiment of the present application;

[0046] Figure 5 Schematic diagram of the system architecture inside a robot in an embodiment of the present application.

[0047] The realization of the purpose of the present application, functional features and advantages will be further described with reference to the embodiments and the accompanying drawings. Specific embodiments

[0048] The embodiments of the present application will be described in detail below. The examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements with the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to explain the present application, and should not be construed as limiting the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts belong to the scope of protection of the present application.

[0049] In addition, if the description in the present application involves "first", "second", etc., it is only for descriptive purposes (such as for distinguishing the same or similar features), and should not be construed as indicating or implying its relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of such features. In addition, the technical solutions between the various embodiments may be combined with each other, but it must be based on the fact that those of ordinary skill in the art can implement it. When the combination of technical solutions results in contradictions or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by the present application.

[0050] Refer to Figure 1 , in an embodiment, the method for handling robot task conflicts includes:

[0051] Step S10: When the robot receives multiple task instructions, classify the relevant tasks and assign initial priorities according to the task type and urgency; wherein, the task type includes functional tasks and emotional expression tasks;

[0052] Step S20: For each relevant task, call the RRT path planner to calculate the motion trajectory of the robotic arm;

[0053] Step S30: Evaluate the path overlap degree of the motion trajectories between different tasks; wherein, if the path distance between the evaluated motion trajectories is less than the set threshold, it is determined that there is a spatio-temporal conflict between the relevant tasks;

[0054] Step S40: If there are spatio-temporal conflicts between related tasks, adjust the task priorities. Among them, for urgent functional tasks, adjust them to the highest priority; for non-urgent functional tasks, dynamically adjust the priorities according to the task execution progress and task importance.

[0055] Step S50: Conduct task arbitration according to the priority adjustment result and select the corresponding arbitration strategy. Among them, if the conflicting tasks involve urgent functional tasks, adopt the emergency interruption strategy and give priority to executing the urgent functional tasks; if the conflicting tasks do not involve urgent functional tasks, adopt the smooth transition strategy, execute each task in sequence according to the priority, and insert smooth transition frames during task switching.

[0056] Step S60: Control the robot to execute the corresponding tasks according to the arbitration strategy.

[0057] In this embodiment, the execution terminal of the embodiment can be a robot, or other devices or apparatuses (such as a control device) that control the robot.

[0058] As described in step S10, when there are multiple task requirements in the system environment where the robot is located, these tasks will be sent to the robot in the form of instructions. For example, in a smart home scenario, the user may simultaneously issue task instructions such as "adjust the brightness of the living room lights" (functional task), "play cheerful music and show dancing movements" (emotional expression task), etc. After receiving these instructions, the robot enters the subsequent processing flow.

[0059] According to the nature of the tasks, the received related tasks are classified into two types: functional tasks and emotional expression tasks:

[0060] (1) Functional tasks: Such tasks are usually related to the actual functional operations of the robot and aim to complete specific work or achieve a certain actual effect. For example, on an industrial production line, operations such as a robotic arm grasping parts, transporting materials, and performing assembly; in a home environment, a floor-sweeping robot cleaning the floor, a smart air conditioner adjusting the indoor temperature, etc. all belong to functional tasks.

[0061] (2) Emotional expression tasks: Mainly focus on emotional interaction with the user and convey emotions or create an atmosphere through specific actions, expressions, sounds, etc. For example, the robot makes dancing movements, shows different facial expressions (such as smiling, surprised), plays music, etc. to meet the user's needs in terms of emotional experience.

[0062] When the robot receives multiple task instructions, it first classifies the tasks. The tasks are divided into functional tasks (such as lighting adjustment, object handling) and emotional expression tasks (such as dancing, expression display). Each task is assigned an initial priority according to its type and urgency.

[0063] Optionally, set the initial priority of the functional task to be higher than that of the emotional expression task; on this basis, among tasks of the same type, the higher the urgency of the task, the higher the initial priority is assigned.

[0064] For example, an urgent functional task (such as obstacle avoidance) is assigned a high priority (e.g., 10), a non-urgent functional task is assigned a medium priority (e.g., 5), and an emotional expression task is assigned a low priority (e.g., 1).

[0065] The task information and priorities are stored in the system memory for subsequent dynamic adjustment. The task information includes key parameters such as task type, description, starting point, and target point.

[0066] As described in step S20, for each relevant task, call the improved RRT path planner to calculate the motion trajectory of the robotic arm in real time. The improved RRT generates a path from the starting point to the ending point quickly through random sampling and tree-like structure expansion, and optimizes the length and safety of the path.

[0067] It should be noted that the core idea of the RRT algorithm is to randomly sample in the configuration space of the robot, gradually construct a random tree to explore the entire space, so as to find a feasible path from the starting point to the target point. This algorithm does not require a complete modeling of the environment, but quickly searches for paths in complex environments by continuously randomly sampling and expanding the tree structure.

[0068] As described in step S30, before evaluating the path overlap degree, it is necessary to obtain the robotic arm motion trajectory data corresponding to each task. These data are calculated by calling the RRT path planner in step S20. The motion trajectory data can be represented as a sequence of coordinate points, and each coordinate point represents the position of the robotic arm at different times.

[0069] To evaluate the overlap degree between the motion trajectories of different tasks, the closest point distance or the average point distance can be used to calculate the path distance between them.

[0070] Pre-set a suitable path distance threshold (i.e., set the threshold) according to the working environment of the robot, the size of the robotic arm, and the requirements of the task. The determination of this threshold needs to comprehensively consider various factors such as the size of the robotic arm, the working environment, and the task requirements:

[0071] If the robotic arm itself is large, in order to avoid collisions, the threshold should be set relatively large; on the contrary, if the robotic arm is small, the threshold can be appropriately reduced;

[0072] In an environment with a narrow space and many obstacles, in order to ensure the safe operation of the robot, the threshold needs to be set more strictly; while in an open environment, the threshold can be relatively loose;

[0073] For some tasks with high requirements for precision and safety, such as fine assembly tasks, the threshold should be set smaller; for general handling tasks, the threshold can be appropriately increased.

[0074] For example, for a small non-humanoid robot (such as a household companion robot), the set threshold can be 5 cm.

[0075] Compare the path distance between different task motion trajectories obtained by calculation with the set threshold:

[0076] If the path distance is less than the set threshold, it is determined that there is a spatio-temporal conflict between the relevant tasks, which means that during the process of the robot executing these tasks, the motion trajectories of the robotic arms may interfere with each other and there is a risk of collision; if the path distance is greater than or equal to the set threshold, it is considered that there is no spatio-temporal conflict between the relevant tasks, and the robot can execute the tasks according to the action trajectories of each task respectively.

[0077] As described in step S40, when it is determined that there is a spatio-temporal conflict between the relevant tasks, the conflict detection result is sent to the dynamic priority algorithm module.

[0078] The dynamic priority algorithm module dynamically adjusts the task priorities according to the spatio-temporal conflict detection results. Refer to Figure 2 , the specific dynamic priority algorithm logic is as follows:

[0079] If a conflict is detected and the task is an urgent functional task (such as obstacle avoidance), the priority of this task is raised to the highest level and other tasks are forcibly interrupted. For example, in the scenario of an autonomous mobile robot, when the robot suddenly detects an obstacle in front during driving, the obstacle avoidance task is triggered and a spatio-temporal conflict is determined. At this time, the priority of the obstacle avoidance task will be raised to the highest level, and the robot will immediately stop other tasks currently being executed (such as cargo handling) and instead execute the obstacle avoidance operation to avoid a collision accident.

[0080] If the task is a non-urgent functional task, the priority is dynamically adjusted according to the task execution progress and task importance.

[0081] Optionally, the adjustment formula used by the algorithm for dynamically adjusting the priority is:

[0082] Priority new =Priority old +α×Progress―β×Importance;

[0083] Among them, Priority old is the original priority; α and β are adjustment coefficients dynamically set according to the task type and scenario respectively; Progress is the task execution progress, and its value range is [0, 1]; Importance is the task importance, and its value range is [0, 1]. The adjusted task priority is sent to the task arbitration module.

[0084] It should be noted that the task execution progress reflects the degree to which the task has been completed. For example, if a task has been completed 80%, then its execution progress Progress = 0.8; generally, tasks with a higher execution progress should be completed first because continuing to execute these tasks may only require less time and resources to complete. The task importance indicates the importance of the task to the entire system or goal. For example, for tasks on a production line, the importance of some key processes may be relatively high, while the importance of some auxiliary tasks is relatively low.

[0085] The values of α and β are adjustment coefficients dynamically set according to the degree of emphasis on the task execution progress and task importance based on the task type and scenario. For example, in some scenarios with high requirements for task execution speed, the value of α will be set relatively large to encourage the priority completion of tasks with a higher execution progress; while in some scenarios that pay more attention to task importance, the value of β may be set relatively large to ensure that important tasks can be processed first.

[0086] Optionally, a real-time monitoring mechanism can be established to dynamically adjust α and β according to the real-time execution progress and the changing trend of the importance of the task. For example, in the logistics distribution during traffic congestion, if the execution progress of a certain task lags severely due to congestion and its importance is relatively high, at this time, α can be appropriately increased while keeping β at a certain level to balance the impact of the execution progress and importance.

[0087] Optionally, collect a large amount of task execution data, including task type, scenario information, execution progress, importance, and the final task completion situation, etc. Use machine learning algorithms (such as decision trees, neural networks, etc.) to train this data to enable the algorithm to automatically learn the optimal values of α and β under different task types and scenarios.

[0088] Optionally, analyze the task execution situations in the past similar tasks and scenarios, and summarize the combination of values of α and β that can make the overall task completion effect the best. For example, review the execution data of the past 100 production tasks, and count the indicators such as task completion time and quality under different values of α and β, and find the optimal values as a reference.

[0089] As described in step S50, refer to Figure 3, the task arbitration module executes the corresponding arbitration strategy according to the decision of the dynamic priority algorithm module.

[0090] When the conflicting tasks include urgent functional tasks, such as obstacle avoidance tasks, emergency rescue tasks, etc., in order to ensure the safety of the robot system and the achievement of key goals, an emergency interruption strategy needs to be adopted.

[0091] Emergency interruption strategy: If the task is an urgent functional task, the emotional expression task is forcibly interrupted to ensure the priority execution of the urgent task. During the interruption, the current state of the emotional expression task is saved for subsequent recovery.

[0092] When all the conflicting tasks are non-urgent functional tasks, in order to reduce the impact of task switching on the robot system and ensure the stability and smoothness of task execution, a smooth transition strategy is adopted.

[0093] Smooth transition strategy: If the task is a non-urgent functional task, smooth transition frames are inserted during task switching. The smooth transition frames are calculated by interpolation formulas to ensure the smooth transition of the robot's actions from one task to another.

[0094] Optionally, the smooth transition frame is 0.5 seconds and is calculated using the following interpolation formula:

[0095]

[0096] where q old (t) and q new (t) are the positions of the old task and the new task at time t, respectively.

[0097] As described in step S60, the robot executes the corresponding task according to the decision of the task arbitration module.

[0098] When the emergency interruption strategy is adopted, it means that there are urgent functional tasks that need to be processed first. The system will quickly allocate various resources of the robot to ensure the smooth execution of the urgent tasks.

[0099] For example, when an industrial robot is performing a material handling task and suddenly detects that a person has entered a dangerous area in front, triggering the urgent functional task of obstacle avoidance, the robot will immediately stop the material handling action. Release the resources occupied by the execution of non-urgent tasks (such as the motion control of the robotic arm, sensor data processing, etc.) to provide sufficient resource support for the execution of the urgent functional task. Then give priority to executing the urgent functional task until the task is completed. In the above obstacle avoidance task, the robot will quickly start the obstacle avoidance program, adjust its own position and posture, and avoid the obstacle. When the urgent functional task is completed, the system will re-arrange the execution order of the uncompleted non-urgent tasks according to the adjusted priorities and resume the execution of these tasks.

[0100] Optionally, when executing the smooth transition strategy, the results will be adjusted according to the priority, and the conflicting non-urgent tasks will be sorted to determine the execution order (tasks with higher priority will be executed first). When switching tasks, the system will insert smooth transition frames. The role of these transition frames is to smoothly transition the motion state of the robot from the state of the current task to the starting state of the next task. After completing the smooth transition, the system starts to execute the next task with the highest priority. This cycle continues until all tasks are completed.

[0101] In one embodiment, the motion trajectory of the robotic arm is calculated by the RRT path planner, and the path overlap degree is evaluated, which can detect the spatio-temporal conflicts between tasks in real time, and then adjust the task priorities to ensure the efficient and orderly processing of tasks, effectively solving the problem of task conflicts and avoiding situations such as motion jamming, task interruption, and mechanical failures caused by overlapping task paths for the robot; at the same time, it can respond quickly in case of emergencies; moreover, different arbitration strategies are adopted during task execution, especially the smooth transition strategy, which can insert smooth transition frames during task switching, enabling the robot to more naturally integrate emotional expression actions when performing functional tasks, greatly enhancing the social interaction experience with users.

[0102] In one embodiment, based on the above embodiment, during the process of the RRT path planner calculating the motion trajectory, first set the task start point and end point, and add the start point as the initial node to the path tree;

[0103] Randomly generate sampling points in the task space;

[0104] Find the node in the generated path tree that is closest to the sampling point;

[0105] Expand the path from the nearest node towards the sampling point to generate a new node;

[0106] Optimize the path through local optimization methods.

[0107] In this embodiment, for each task, an improved RRT path planner is called to calculate the motion trajectory of the robotic arm in real time. The improved RRT quickly generates a path from the start point to the end point through random sampling and tree-like structure expansion, and optimizes the length and safety of the path. The working process of the RRT path planner is as follows:

[0108] (1) Initialization: Set the task start point and end point, and add the start point as the initial node to the path tree. The determination of this start point and end point is based on the specific requirements of the task. For example, in a warehouse handling scenario, the start point may be the storage location of the goods, and the end point is the target storage point of the goods. Subsequently, add the start point as the initial node to the path tree. This path tree is like the prototype of a planned map, providing a basis for subsequent path exploration.

[0109] (2) Random sampling: Randomly generate sampling points in the task space. The generation range of the sampling points is determined according to the boundaries of the task space. This task space can be the physical space where the robot operates, such as a factory workshop, a home room, etc. The generation range of the sampling points is strictly determined according to the boundaries of the task space to ensure that all sampling points are within the reasonable range where the robot can move. Through random sampling, the task space can be comprehensively explored to avoid falling into local optimal solutions.

[0110] (3) Nearest node selection: Find the node in the generated path tree that is closest to the sampling point. This step is like finding the nearest known location on a map to the newly explored point. By comparing the distances between the sampling point and each node in the path tree, the nearest node is determined, providing a direction for subsequent path expansion.

[0111] (4) Path expansion: Expand the path from the nearest node towards the sampling point to generate new nodes. The expansion step size is set according to the dynamic characteristics of the task and the spatial resolution. In some tasks with high precision requirements, the expansion step size will be relatively small to ensure the accuracy of the path; while in some tasks with high speed requirements, the expansion step size can be appropriately increased. Such dynamic adjustment can make the path planning more flexible and adapt to different task requirements.

[0112] (5) Path optimization: Optimize the path through local optimization methods (such as interpolation and collision detection) to ensure the smoothness and safety of the path. During the optimization process, the position of each node on the path is calculated through an interpolation formula to ensure the continuity and collision-free of the path. For example, in an environment with obstacles, collision detection can be used to timely detect whether the path will collide with obstacles, and the node positions can be adjusted through interpolation to avoid obstacles, ensuring the safety and smoothness of the path.

[0113] In one embodiment, the improved RRT path planner can quickly generate a path from the starting point to the ending point through random sampling and tree-like structure expansion, without the need to comprehensively search the entire task space, greatly shortening the planning time and improving the response speed of the robot; and the expansion step size is set according to the dynamic characteristics of the task and the spatial resolution, capable of adapting to different types of tasks and environments. Whether in a complex industrial scenario or a simple home environment, it can plan a suitable path, with strong versatility; the random sampling method can comprehensively explore the task space to avoid falling into local optimal solutions, thereby finding a better path plan, which enables the robot to find the best motion trajectory in a complex environment and improves the success rate of task execution; the optimized path can not only reduce the motion loss of the robot but also avoid collisions with obstacles, improving the operation efficiency and reliability of the robot.

[0114] In one embodiment, based on the above embodiment, the method for handling robot task conflicts further includes:

[0115] If the conflicting tasks involve non - urgent functional tasks and emotional expression tasks, and the emotional expression task is a social task, then the action fusion technology is adopted to organically combine the emotional expression task into the functional task.

[0116] In this embodiment, referring to Figure 3 , in a scenario where the robot receives multiple task instructions, when encountering task conflicts, in addition to the conventional processing methods described above, for conflict situations involving non - urgent functional tasks and emotional expression tasks (and the emotional expression task is a social task), the action fusion technology will be used for processing.

[0117] First of all, the system needs to identify that among the currently conflicting tasks, there are non - urgent functional tasks and emotional expression tasks, and the emotional expression task belongs to the social task. For example, the robot is performing a non - urgent room cleaning (functional task), and at the same time receives an instruction to greet a guest (emotional expression - type social task), which triggers such a special task conflict scenario.

[0118] The core goal of the action fusion technology is to organically combine the emotional expression task into the functional task, so that the robot can perform the emotional expression task while completing the functional task, avoiding the unnatural feeling brought by task interruption or separate execution, and making the robot's behavior more fluent and user - friendly.

[0119] Analyze the action postures required for non - urgent functional tasks and emotional expression social tasks. For example, when cleaning the room and greeting a guest, the robot can turn its head or upper body while moving the cleaning tool to face the guest and make a friendly gesture, such as nodding slightly. In this way, the cleaning action and the greeting gesture are fused together, and the coherence of cleaning will not be interrupted because of stopping specifically to greet.

[0120] Reasonably arrange the time sequence of the two task actions. For example, during the execution of the non - urgent functional task, select an appropriate time point to insert the action of the emotional expression task. If the robot is cleaning the living room with a vacuum cleaner, when it moves near the guest, it can pause the movement operation of the vacuum cleaner for a moment, while sending a friendly greeting and making corresponding gestures, and then continue cleaning.

[0121] Adjust the intensity and speed of the actions to make the actions of the two tasks coordinated. Taking the example of a robot carrying a tray (a non-emergency functional task) and smiling and talking to guests (an emotional expression social task), when smiling and talking, the hand movement of carrying the tray can be appropriately slowed down and the intensity can be made more stable to show friendliness and concentration, avoiding tipping over the tray due to excessive movements or giving an impolite feeling.

[0122] During the process of executing tasks using action fusion technology, the system will continuously evaluate the effect of the fusion. By collecting information about the surrounding environment and human feedback through sensors, it judges whether the fused actions are natural and reasonable. If it is found that the guests show signs of confusion or dissatisfaction with the performance of the robot, the system will promptly adjust the way of action fusion, such as changing the action posture, adjusting the timing or intensity, etc., to achieve a better fusion effect, enabling the robot to efficiently complete both non-emergency functional tasks and emotional expression social tasks simultaneously.

[0123] Through this action fusion technology, the robot can better balance functional and emotional social needs when dealing with task conflicts, improving the quality and experience of human-robot interaction.

[0124] Optionally, the action fusion technology can adopt the following fusion formula:

[0125] q fused (t) = γ × q functional (t) + (1 - γ) × q emotional (t);

[0126] where γ is the fusion coefficient, which is dynamically adjusted according to the social requirements of the task; q functional (t) and q emotional (t) are the positions of the functional task and the emotional expression task at time t respectively. For example, when performing the lighting adjustment task, rhythmic flashing is synchronized to enhance the social interactivity of the robot.

[0127] Optionally, the action fusion technology is preferably based on performing the functional task and, as much as possible, fusing the social tasks that still need to be executed currently. Therefore, it is recommended to set the value range of the fusion coefficient to (0.5, 1).

[0128] Optionally, to avoid conflicts in action fusion, based on the relevant data of the previously evaluated path overlap between tasks (these data record the movement trajectory information of the functional task and the social task respectively, including the position of the robotic arm in space, the movement path, etc.; by analyzing these data, the overlap situation of the actions of the two tasks in space and time can be clearly understood, providing a basis for screening the appropriate action timing of the social task later), from the action timings of the social task, the action timings that do not have path overlap with the functional task are screened for fusion.

[0129] Among them, traverse all the action time sequences of the social task, and judge whether the action path at each time sequence overlaps with the path of the functional task according to the path overlap degree data. For the action time sequences with path overlap, exclude them; only retain the action time sequences that do not overlap with the functional task path. For example, if the robotic arm of the robot needs to perform a cleaning operation within a certain specific area in the functional task, then the action time sequences related to this area in the social task will be filtered out.

[0130] Suppose the robot is performing a functional task of wiping the table, and at the same time receives a social task instruction to wave hello to the guest. Through the path overlap degree evaluation data, it is found that during some time periods of wiping the table, the robotic arm will occupy most of the table area. Then, from the action time sequences of waving hello, the action time sequences where the robotic arm waves outside the table area will be screened out and fused with the action of wiping the table, so that both social interaction is completed and action conflicts are avoided.

[0131] In this way, by screening and fusing the action time sequences without path overlap based on the path overlap degree data, the conflict problem in the action fusion process can be effectively solved, and the efficiency and quality of the robot performing multiple tasks can be improved.

[0132] In one embodiment, on the basis of the above embodiment, after the step of controlling the robot to execute the corresponding task according to the arbitration strategy, it further includes:

[0133] After the task is executed, generate feedback data according to the task execution situation;

[0134] Optimize the algorithm for dynamically adjusting priorities and / or the RRT path planner according to the feedback data.

[0135] In this embodiment, after the task is executed, the system gives feedback on the task execution situation and records key indicators such as the task conflict rate and task execution time. According to the feedback data, the algorithm for dynamically adjusting priorities and / or the RRT path planner can be optimized to further improve the performance and stability of the system.

[0136] During the optimization process, the algorithm parameters can be adjusted through error backpropagation, such as adjusting coefficients α and β, and fusion coefficient γ, to minimize the error and reduce the task conflict rate. An example of the optimization formula is as follows:

[0137] Error=∑ i (ConflictRate i ―TargetRate) 2 ;

[0138] Among them, ConflictRate iLet \(ConflictRate_i\) be the conflict rate of the \(i\)-th task, and \(TargetRate\) be the target conflict rate. By optimizing the algorithm parameters, the system can better adapt to different task scenarios and improve the overall performance.

[0139] In one embodiment, based on the above embodiment, the method for handling robot task conflicts further includes:

[0140] During the task execution process, continuously monitor the path overlap degree between different tasks to detect whether there are new spatio-temporal conflicts between different tasks;

[0141] If so, return to execute the step of adjusting the task priority if there are spatio-temporal conflicts between related tasks.

[0142] In this embodiment, during the dynamic process of the robot executing tasks, the environment is constantly changing, and the execution situation of each task is not static. For example, when the robot executes a functional task, it may encounter obstacles, resulting in a change in its motion trajectory; or when executing an emotional expression task, due to the change in the position of surrounding people, the action path of this task will also change. These factors may cause new spatio-temporal conflicts between tasks that originally had no path overlap. Therefore, it is very necessary to continuously monitor the path overlap degree between different tasks, which can timely detect potential conflicts and ensure the safety and efficiency of robot task execution.

[0143] That is, during the process of the robot executing related tasks, continue to monitor the spatial overlap degree of the task paths in real time to ensure the smooth progress of the tasks and avoid the occurrence of new conflicts. If a new conflict is detected during the execution process, the system will re-trigger the spatio-temporal conflict detection and dynamic priority adjustment process to ensure the real-time performance and safety of the tasks.

[0144] In one embodiment, based on the above embodiment, after the step of evaluating the path overlap degree of the motion trajectories between different tasks, it further includes:

[0145] If there are no spatio-temporal conflicts between related tasks, control the robot to execute the related tasks simultaneously.

[0146] In this embodiment, when the robot processes multiple tasks, evaluating the path overlap degree of the motion trajectories between different tasks is a crucial pre-step. Through this evaluation, the mutual relationship of each task in the spatio-temporal dimension can be clearly understood, and it can be judged whether task conflicts will occur. Its core purpose is to ensure the safety and efficiency of the robot during the execution of multiple tasks, and avoid equipment damage, task execution failure or dangerous situations caused by interference between tasks.

[0147] When it is determined through path overlap evaluation that there are no spatio-temporal conflicts between related tasks, it means that these tasks will not interfere with each other in terms of time and space and can be carried out in parallel. At this time, the system will issue an instruction to control the robot to execute related tasks simultaneously.

[0148] For example, in a smart home scenario, the robot may need to execute two tasks, sweeping the floor and voice interaction, simultaneously. Through path overlap evaluation, it is confirmed that the movement trajectory of the floor-sweeping task and the position during voice interaction will not conflict. Then the robot can communicate with family members by voice, answer questions or execute voice commands while sweeping the floor, providing a more convenient and intelligent service experience for users.

[0149] In one embodiment, when there are no spatio-temporal conflicts between related tasks, controlling the robot to execute related tasks simultaneously can effectively improve the working efficiency and resource utilization rate of the robot, bringing a better service experience for users.

[0150] In addition, referring to Figure 4 , this application embodiment also provides a control device Z10, including:

[0151] A task initialization module Z11, which is used to classify related tasks when the robot receives multiple task instructions and assign initial priorities according to the task type and urgency; among them, the task type includes functional tasks and emotional expression tasks;

[0152] An RRT path planner module Z12, which is used to call the RRT path planner to calculate the movement trajectory of the robotic arm for each related task;

[0153] A spatio-temporal conflict detection module Z13, which is used to evaluate the path overlap of the movement trajectories between different tasks; among them, if the path distance between the evaluated movement trajectories is less than the set threshold, it is determined that there are spatio-temporal conflicts between related tasks;

[0154] A dynamic priority algorithm module Z14, which is used to adjust the task priorities if there are spatio-temporal conflicts between related tasks; among them, for urgent functional tasks, they are adjusted to the highest priority; for non-urgent functional tasks, the priorities are dynamically adjusted according to the task execution progress and task importance;

[0155] A task arbitration module Z15, which is used to perform task arbitration according to the priority adjustment result and select the corresponding arbitration strategy; among them, if the conflicting tasks involve urgent functional tasks, the emergency interruption strategy is adopted to give priority to executing the urgent functional tasks; if the conflicting tasks do not involve urgent functional tasks, the smooth transition strategy is adopted to execute each task in turn according to the priorities, and smooth transition frames are inserted during task switching;

[0156] The task execution module Z16 is used to control the robot to execute corresponding tasks according to the arbitration strategy;

[0157] The feedback and optimization module Z17 is used to generate feedback data according to the task execution situation after the task is completed; optimize the algorithm for dynamically adjusting priorities and / or the RRT path planner according to the feedback data.

[0158] Optionally, the control device Z10 can be a virtual control device (such as a virtual machine) or a physical device (such as a physical device other than the robot that can execute the corresponding method).

[0159] In this embodiment, the spatio-temporal conflict detection module monitors the path overlap situation between the functional task and the emotional expression task in real time through the improved RRT path planner, ensuring that the robot can timely detect and handle action conflicts during the multi-task execution process, so as to accurately calculate the spatial overlap degree of the path and trigger the subsequent dynamic priority adjustment process.

[0160] The dynamic priority adjustment algorithm dynamically adjusts the task priorities according to the spatio-temporal conflict detection results, and can flexibly adjust the task execution order according to the urgency of the tasks and the real-time scenario. This algorithm enables the robot to optimize the task execution strategy in real time when facing complex and changeable task scenarios, ensuring that urgent tasks are given priority and improving the overall task execution efficiency.

[0161] The improved RRT path planner module quickly generates a path from the starting point to the ending point through random sampling and tree structure expansion, and optimizes the length and safety of the path. In this way, it can calculate the mechanical arm movement trajectory in real time, ensure the smoothness and safety of the path, and provide accurate data support for spatio-temporal conflict detection.

[0162] The task arbitration module performs operations such as emergency interruption, smooth transition, or action fusion according to the decision of the dynamic priority algorithm module. In this way, it can flexibly execute the corresponding arbitration strategy according to the priorities of different tasks and the scenario requirements, ensuring the fluency and safety of the robot task execution.

[0163] In addition, an embodiment of the present application also provides a robot, and the system architecture inside the robot can be as Figure 5As shown in the figure, it includes a processor, a memory, a communication interface, and an input interface connected through a system bus. Among them, the processor is used to provide computing and control capabilities. The memory includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database is used to store data called by the computer program. The communication interface is used to communicate with an external terminal for data. The input interface is used to receive signals input by an external device. When the computer program is executed by the processor, it implements a method for handling robot task conflicts as described in the above embodiments.

[0164] Those skilled in the art can understand that Figure 5 the structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the robot to which the solution of the present application is applied. For example, in some alternative embodiments, the robot may further include an output interface (not shown in the figure), and the output interface is also connected to the system bus and is used to output corresponding signals to external devices.

[0165] In addition, the present application also proposes a computer-readable storage medium, which includes a computer program. When the computer program is executed by a processor, it implements the steps of the method for handling robot task conflicts as described in the above embodiments. It can be understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0166] In summary, for the method for handling robot task conflicts, the control device, the robot, and the computer-readable storage medium provided in the embodiments of the present application, by calculating the motion trajectory of the robotic arm through the RRT path planner and evaluating the path overlap degree, it can detect the spatio-temporal conflicts between tasks in real time, and then adjust the task priorities to ensure the efficient and orderly processing of tasks, effectively solving the problem of task conflicts, and avoiding situations such as action jamming, task interruption, and mechanical failures of the robot caused by overlapping task paths; at the same time, it can respond quickly when an emergency occurs; and different arbitration strategies are adopted during task execution, especially the smooth transition strategy, which can insert smooth transition frames during task switching, enabling the robot to more naturally integrate emotional expression actions when performing functional tasks, greatly enhancing the social interaction experience with users.

[0167] The example of the entire solution process is as follows:

[0168] For example, in a home environment, a non-humanoid robot receives two task instructions: one is a functional task of adjusting the brightness of the living room lights, and the other is an emotional expression task of interacting and dancing with family members. These two tasks need to be processed simultaneously by the robot, but their movement paths may conflict, especially during the movement of the robotic arm. To effectively resolve this conflict, the robot adopts the system and method of the present invention.

[0169] First, the robot initializes and classifies these two tasks. The light adjustment task is marked as a functional task and is assigned an initial priority of 5. The dancing task is marked as an emotional expression task and is assigned an initial priority of 1. The task information and priorities are stored in the system memory for subsequent dynamic adjustment. The task information includes key parameters such as task type, description, starting point, and target point. For example, the starting point of the light adjustment task is the current position of the robotic arm (0, 0, 0), and the target point is the position of the light adjustment device (1, 1, 0.5). The starting point of the dancing task is the current position of the robotic arm (0, 0, 0), and the target point is the starting position of the dancing movement (0.5, 0.5, 0.3).

[0170] After that, the robot calls an improved RRT path planner to plan the movement trajectory of the robotic arm from the initial position (0, 0, 0) to the target position (1, 1, 0.5) for the light adjustment task. The path planner quickly generates a path from the starting point to the end point through random sampling and tree structure expansion, and optimizes the length and safety of the path. The specific steps are as follows: First, the path planner randomly generates sampling points in the task space, and the generation range of the sampling points is determined according to the boundaries of the task space. Then, find the node closest to the sampling point in the generated path tree. Expand the path from the closest node towards the sampling point direction to generate a new node. The expansion step size is set according to the dynamic characteristics of the task and the spatial resolution. Optimize the path through local optimization methods (such as interpolation and collision detection) to ensure the smoothness and safety of the path. During the optimization process, the position of each node on the path is calculated through an interpolation formula to ensure the continuity and collision-free of the path.

[0171] At the same time, the robot also plans a path for the robotic arm to perform rhythmic swings in space for the dancing task. The path planning for the dancing task also uses an improved RRT algorithm to ensure the smoothness and safety of the path. During the path planning process, the robot calculates the spatial overlap degree of the two paths in real time. When it is detected that the spatial distance between the two paths at a certain moment is less than 5 centimeters, the dynamic priority adjustment algorithm is triggered. According to the urgency of the task and the current execution progress, the algorithm dynamically adjusts the priority of the light adjustment task to 6, while keeping the priority of the dancing task unchanged. The adjustment formula is:

[0172] Priority new =Priority old+α×Progress ― β×Importance;

[0173] where α = 0.5, β = 0.3, Progress is the task execution progress, and Importance is the task importance. For example, the execution progress of the lighting adjustment task is 0.4 and the importance is 0.6. Therefore, its priority is adjusted to: Priority new = 5 + 0.5×0.4 - 0.3×0.6 = 6.

[0174] The task arbitration module executes the corresponding arbitration strategy according to the decision of the dynamic priority algorithm module. Since the priority of the lighting adjustment task is higher than that of the dancing task, the task arbitration module decides to insert a 0.5-second smooth transition frame between the two tasks. Calculate the position of the transition frame through interpolation to smoothly transition the robotic arm from the lighting adjustment action to the dancing action. The interpolation formula is:

[0175]

[0176] For example, during the transition, the position of the robotic arm smoothly transitions from the last node (1, 1, 0.5) of the lighting adjustment task to the first node (0.5, 0.5, 0.3) of the dancing task.

[0177] During the execution of the task, the robot continues to monitor the spatial overlap of the task path in real time to ensure the smooth progress of the task and no new conflicts occur. If a new conflict is detected during the execution, the system will re-trigger the space-time conflict detection and dynamic priority adjustment process to ensure the real-time performance and safety of the task. For example, if during the execution of the dancing task, the robot detects that the distance between the robotic arm and the furniture is less than the safety threshold, the system will immediately trigger dynamic priority adjustment, promote the obstacle avoidance task to the highest priority, and interrupt the current task to ensure the safety of the robot. After the task is completed, the system provides feedback on the task execution situation and records key metrics such as the task conflict rate and task execution time. For example, the conflict rate of this task is 0.03 and the task execution time is 2.3 seconds. Based on the feedback data, optimize the dynamic priority algorithm and the path planner to further improve the performance and stability of the system. During the optimization process, adjust the algorithm parameters through error backpropagation to minimize the error and reduce the task conflict rate.

[0178] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium provided in this application and used in the embodiments can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0179] It should be noted that in this article, the terms "including", "comprising", or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, apparatus, article, or method including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, apparatus, article, or method including that element.

[0180] The above are only the preferred embodiments of this application, and do not limit the patent scope of this application accordingly. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of this application, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of this application.

Claims

1. A method for handling robot task conflicts, characterized in that, Including: When the robot receives multiple task instructions, classify the relevant tasks and assign an initial priority according to the task type and urgency; among them, the task types include functional tasks and emotional expression tasks; For each relevant task, call the RRT path planner to calculate the motion trajectory of the robotic arm; Evaluate the path overlap degree of the motion trajectories between different tasks; among them, if the path distance between the evaluated motion trajectories is less than the set threshold, it is determined that there is a spatio-temporal conflict between the relevant tasks; If there is a spatio-temporal conflict between the relevant tasks, adjust the task priority; among them, for urgent functional tasks, adjust them to the highest priority; for non-urgent functional tasks, dynamically adjust the priority according to the task execution progress and task importance; Perform task arbitration according to the priority adjustment result and select the corresponding arbitration strategy; among them, if the conflicting tasks involve urgent functional tasks, adopt the emergency interruption strategy and give priority to executing the urgent functional tasks; if the conflicting tasks do not involve urgent functional tasks, adopt the smooth transition strategy, execute each task in turn according to the priority, and insert smooth transition frames when switching tasks; Control the robot to execute the corresponding tasks according to the arbitration strategy.

2. The method for handling robot task conflicts according to claim 1, wherein During the process of the RRT path planner calculating the motion trajectory, first set the task start point and end point, and add the start point as the initial node to the path tree; Randomly generate sampling points in the task space; Find the node closest to the sampling point in the generated path tree; Expand the path from the nearest node towards the sampling point direction to generate a new node; Optimize the path through local optimization methods.

3. The method for handling robot task conflicts according to claim 1, wherein, The adjustment formula adopted by the algorithm for dynamically adjusting the priority is: Priority new = Priority old + α × Progress ― β × Importance; Among them, Priority old is the original priority; α and β are adjustment coefficients dynamically set according to the task type and scenario respectively; Progress is the task execution progress, and its value range is [0, 1]; Importance is the task importance, and its value range is [0, 1].

4. The method for handling robot task conflicts according to claim 1, wherein The method for handling robot task conflicts further includes: If the conflicting tasks involve non-urgent functional tasks and emotional expression tasks, and the emotional expression task is a social task, adopt the action fusion technology to organically combine the emotional expression task into the functional task.

5. The method for handling robot task conflicts according to any one of claims 1-4, characterized in that After the step of controlling the robot to execute the corresponding tasks according to the arbitration strategy, it further includes: After the task is completed, generate feedback data according to the task execution situation; Optimize the algorithm for dynamically adjusting the priority and / or the RRT path planner according to the feedback data.

6. The method for handling robot task conflicts according to claim 1, wherein The method for handling robot task conflicts further includes: During the task execution process, continuously monitor the path overlap degree between different tasks to monitor whether there is a new spatio-temporal conflict between different tasks; If so, return to execute the step of if there is a spatio-temporal conflict between the relevant tasks, then adjust the task priority.

7. The method for handling robot task conflicts according to claim 1, wherein After the step of evaluating the path overlap degree of the motion trajectories between different tasks, it further includes: If there is no spatio-temporal conflict between the relevant tasks, control the robot to execute the relevant tasks simultaneously.

8. A control device, characterized in that, Including: A task initialization module, used for when the robot receives multiple task instructions, classify the relevant tasks and assign an initial priority according to the task type and urgency; among them, the task types include functional tasks and emotional expression tasks; An RRT path planner module, used for for each relevant task, call the RRT path planner to calculate the motion trajectory of the robotic arm; A spatio-temporal conflict detection module for evaluating the path overlap degree of the motion trajectories between different tasks; wherein, if the path distance between the evaluated motion trajectories is less than a set threshold, it is determined that there is a spatio-temporal conflict between the relevant tasks; A dynamic priority algorithm module for adjusting the task priorities if there is a spatio-temporal conflict between the relevant tasks; wherein, for urgent functional tasks, they are adjusted to the highest priority; for non-urgent functional tasks, the priorities are dynamically adjusted according to the task execution progress and task importance; A task arbitration module for performing task arbitration according to the priority adjustment result and selecting the corresponding arbitration strategy; wherein, if the conflicting tasks involve urgent functional tasks, an emergency interruption strategy is adopted to give priority to executing the urgent functional tasks; if the conflicting tasks do not involve urgent functional tasks, a smooth transition strategy is adopted to execute each task in sequence according to the priorities, and smooth transition frames are inserted during task switching; An execute task module for controlling the robot to execute the corresponding tasks according to the arbitration strategy; A feedback and optimization module for generating feedback data according to the task execution situation after the task execution is completed; optimizing the algorithm for dynamically adjusting priorities and / or the RRT path planner according to the feedback data.

9. A robot, characterized in that, The robot includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the computer program is executed by the processor, it implements the steps of the method for handling robot task conflicts as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, and when the computer program is executed by the processor, it implements the steps of the method for handling robot task conflicts as described in any one of claims 1 to 7.

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