A robot collaborative control optimization system based on wireless communication

Abstract

The present invention discloses a robot collaborative control optimization system based on wireless communication, which relates to the field of wireless communication technology and includes a monitoring center, wherein the monitoring center is communicatively connected with a data acquisition module, a data processing module, a data storage module, an expected behavior module and a collaborative optimization module; the motion behavior data of different robots are collected and the motion behavior data of different robots are subjected to biased formal processing to obtain the biased motion behavior data of different robots; the biased motion behavior data of different robots are stored in a historical collection cycle to obtain the historical biased motion behavior data of different robots; then, according to the historical biased motion behavior data of different robots, a corresponding standard expected motion behavior model is constructed to obtain the corresponding expected value of the motion behavior; finally, according to the expected value of the motion behavior, a corresponding collaborative optimization instruction is generated; the robustness, practicality and efficiency of multi-robot collaborative control are greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless communication, and in particular to a robot collaborative control optimization system based on wireless communication. Background Art

[0002] With the development of network technology, mobile ad hoc networks, wireless sensor networks, wireless communications and other technologies have provided solutions for the flexible and collaborative control of multiple mobile robots. By establishing an optimized intelligent system architecture and modeling and analyzing the collaborative process of multiple mobile robots, and on this basis studying how to efficiently integrate wireless communication networking methods, the collaborative capabilities of the components of the entire multi-mobile robot system can be effectively improved.

[0003] Communication technology is a basic research of multi-robot cooperative control system. Through the experiment of monitoring the robots to maintain the formation, the effectiveness and stability of the system structure are verified. Multi-robot cooperative control method has become an important topic in the field of multi-robots. Under the premise of combining wireless communication with self-healing function, the multi-robot cooperative control method based on psychological state and reinforcement learning method with "blackboard structure" is analyzed. The psychological state can establish a model and perfectly describe the relationship between multi-robots, the working environment and the work tasks. The reinforcement learning method with "blackboard area" enhances the robot's ability to learn and understand the surrounding environment that changes at any time. In order to establish the robustness, practicality and efficiency of multi-robot cooperative control, a robot cooperative control optimization system based on wireless communication is provided. Summary of the invention

[0004] In order to solve the above technical problems, the purpose of the present invention is to provide a robot collaborative control optimization system based on wireless communication.

[0005] In order to achieve the above-mentioned object, the present invention provides the following technical solutions: a robot collaborative control optimization system based on wireless communication, comprising a monitoring center, wherein the monitoring center is communicatively connected with a data acquisition module, a data processing module, a data storage module, an expected behavior module and a collaborative optimization module;

[0006] The data acquisition module is used to collect motion behavior data of different robots;

[0007] The data processing module is used to perform partial-form processing on the motion behavior data of different robots to obtain partial-form processing of motion behavior data of different robots;

[0008] The data storage module is used to perform historical collection period storage on the biased movement behavior data of different robots to obtain the historical biased movement behavior data of different robots;

[0009] The expected behavior module is used to construct a corresponding standard expected motion behavior model according to the historical biased motion behavior data of different robots; and obtain the corresponding expected value of the motion behavior according to the standard expected motion behavior model;

[0010] The collaborative optimization module is used to generate a corresponding collaborative optimization solution according to the expected value of the motion behavior.

[0011] Furthermore, the process of the data acquisition module collecting the motion behavior data of different robots includes:

[0012] The data acquisition module is provided with a plurality of data acquisition units, which are arranged at different mechanical joint positions of the robot, and are used to collect motion behavior data corresponding to different mechanical joints of different robots, and set the acquisition cycle and the acquisition time;

[0013] Label different robots as is a natural number; different mechanical joints of the same robot are labeled as is a natural number;

[0014] The motion behavior data includes mechanical joint angles, mechanical joint angular velocities, mechanical joint motion velocities, mechanical joint displacements, and mechanical joint positions.

[0015] Furthermore, the process of the data processing module performing partial formal processing on the motion behavior data of different robots includes:

[0016] The first The different collection moments in the same collection cycle of a robot are marked as is a natural number;

[0017] Get the The mechanical joint angle, mechanical joint angular velocity, mechanical joint movement speed, mechanical joint displacement and mechanical joint position of each robot at different acquisition moments within the same acquisition cycle;

[0018] Set the lower limit of the mechanical joint angle error threshold, the lower limit of the mechanical joint angular velocity error threshold, the lower limit of the mechanical joint motion velocity error threshold, the lower limit of the mechanical joint displacement error threshold, and the lower limit of the mechanical joint position error threshold;

[0019] Compare the mechanical joint angle error threshold lower limit, the mechanical joint angular velocity error threshold lower limit, the mechanical joint motion speed error threshold lower limit, the mechanical joint displacement error threshold lower limit and the mechanical joint position error threshold lower limit with the corresponding mechanical joint angle, mechanical joint angular velocity, mechanical joint motion speed, mechanical joint displacement and mechanical joint position;

[0020] The mechanical joint angle, mechanical joint angular velocity, mechanical joint movement speed, mechanical joint displacement and mechanical joint position that meet the comparison requirements are obtained.

[0021] Furthermore, the process of the data processing module obtaining the positive movement behavior data includes:

[0022] According to the mechanical joint angles, mechanical joint angular velocities, mechanical joint movement speeds, mechanical joint displacements and mechanical joint positions that meet the comparison requirements, the correct mechanical joint angles, correct mechanical joint angular velocities, correct mechanical joint movement speeds, correct mechanical joint displacements and correct mechanical joint positions are obtained.

[0023] Furthermore, the process of the data storage module storing the historical collection period of the biased motion behavior data of different robots includes:

[0024] The data storage module is provided with a real-time database and a historical database to obtain the first The robot's biased movement behavior data is collected and sent to the real-time database for storage;

[0025] When the real-time database receives the When collecting the biased motion behavior data of a robot, the first The biased motion behavior data of each robot is sent to a historical database for storage; The positive motion behavior data of the robot is marked as The historical biased motion behavior data of a robot.

[0026] Furthermore, the process of constructing the corresponding standard expected motion behavior model by the expected behavior module includes:

[0027] The historical biased motion behavior data of several groups of different robots in the historical collection period are used as training sets and test sets, and the training sets and test sets are input into the standard expected motion behavior model, the standard expected motion behavior model is trained, and the standard expected motion behavior model after training is obtained.

[0028] Furthermore, the process of the collaborative optimization module generating the corresponding collaborative optimization instruction includes:

[0029] Acquire expected values ​​of motion behaviors of different robots, and generate corresponding collaborative optimization instructions according to the expected values ​​of motion behaviors; the collaborative optimization instructions include termination motion instructions and cyclic execution motion instructions;

[0030] Preset target movement behavior data and movement behavior error;

[0031] If |Motion behavior expected value - target motion behavior data| is greater than the motion behavior error, a termination motion instruction is generated to stop the running robot and remind the maintenance personnel to check;

[0032] If |Movement behavior expected value - target movement behavior data| is less than the movement behavior error, a cyclic execution movement instruction is generated to perform another partial normalization process on the robot's movement behavior data until |Movement behavior expected value - target movement behavior data| is equal to the movement behavior error;

[0033] If |Motion behavior expected value - target motion behavior data| is equal to the motion behavior error, the robot moves normally.

[0034] Furthermore, the process of the collaborative optimization module executing the cyclic execution motion instruction includes:

[0035] Obtaining a cyclic execution motion instruction of the corresponding robot, parsing the cyclic execution motion instruction according to a recursive solver, and obtaining a real-time action update rate of the corresponding robot;

[0036] Obtaining a real-time action update rate according to an expected value of the robot's motion behavior corresponding to the generated real-time action update rate and target motion behavior data;

[0037] According to the real-time action update rate, the next motion behavior of the corresponding robot is updated in real time.

[0038] Compared with the prior art, the beneficial effects of the present invention are: by collecting motion behavior data of different robots and performing biased formal processing on the motion behavior data of different robots, the biased motion behavior data of different robots are obtained; according to the biased motion behavior data of different robots, historical collection periodic storage is performed to obtain the historical biased motion behavior data of different robots; then, according to the historical biased motion behavior data of different robots, a corresponding standard expected motion behavior model is constructed, and the corresponding expected motion behavior value is obtained; finally, according to the expected motion behavior value, the corresponding collaborative optimization instruction is generated; the robustness, practicality and efficiency of multi-robot collaborative control are greatly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0040] Figure 1 It is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0041] To make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described in detail below. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other implementation methods obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.

[0042] like Figure 1 As shown, a robot collaborative control optimization system based on wireless communication includes a monitoring center, and the monitoring center is communicatively connected with a data acquisition module, a data processing module, a data storage module, an expected behavior module and a collaborative optimization module;

[0043] The data acquisition module is used to collect motion behavior data of different robots;

[0044] The data processing module is used to perform partial-form processing on the motion behavior data of different robots to obtain partial-form processing of motion behavior data of different robots;

[0045] The data storage module is used to perform historical collection period storage on the biased movement behavior data of different robots to obtain the historical biased movement behavior data of different robots;

[0046] The expected behavior module is used to construct a corresponding standard expected motion behavior model according to the historical biased motion behavior data of different robots; and obtain the corresponding expected value of the motion behavior according to the standard expected motion behavior model;

[0047] The collaborative optimization module is used to generate a corresponding collaborative optimization solution according to the expected value of the motion behavior.

[0048] It should be further explained that, in the specific implementation process, the specific process of the data acquisition module collecting the motion behavior data of different robots includes:

[0049] The data acquisition module is provided with a plurality of data acquisition units, which are arranged at different mechanical joint positions of the robot, and are used to collect motion behavior data corresponding to different mechanical joints of different robots, and set the acquisition cycle and the acquisition time;

[0050] Label different robots as is a natural number; different mechanical joints of the same robot are labeled as is a natural number;

[0051] It should be further explained that the movement behavior data includes mechanical joint angle, mechanical joint angular velocity, mechanical joint movement velocity, mechanical joint displacement and mechanical joint position;

[0052] The data acquisition module uploads the sports behavior data to the data processing module.

[0053] It should be further explained that, in the specific implementation process, the specific process of the data processing module performing partial formal processing on the motion behavior data of different robots includes:

[0054] Get the motion behavior data of a robot, and obtaining biased motion behavior data according to the motion behavior data;

[0055] It should be further explained that the above-mentioned corrected motion behavior data includes corrected mechanical joint angles. , angular velocity of mechanical joints , the movement speed of the mechanical joint , partial mechanical joint displacement And correct the position of mechanical joints ;

[0056] The mechanical joint angle, mechanical joint angular velocity, mechanical joint movement velocity, mechanical joint displacement and mechanical joint position in the motion behavior data are marked as , , , as well as ;

[0057] The first The different collection moments in the same collection cycle of a robot are marked as is a natural number;

[0058] Get the The mechanical joint angles of the robots at different acquisition times in the same acquisition cycle , Mechanical joint angular velocity , Mechanical joint movement speed , Mechanical joint displacement and mechanical joint positions ;

[0059] Set the lower limit of the mechanical joint angle error threshold , Mechanical joint angular velocity error lower threshold , Mechanical joint motion speed error lower threshold , Mechanical joint displacement error threshold lower limit And the lower limit of the mechanical joint position error threshold ;

[0060] If the mechanical joint angle Greater than the lower limit of the mechanical joint angle error threshold , then the mechanical joint angle at the current acquisition moment is eliminated , get the value less than or equal to the lower limit of the mechanical joint angle error threshold Mechanical joint angle , for the error threshold less than or equal to the mechanical joint angle Mechanical joint angle Perform the offset calculation to obtain the offset mechanical joint angle The calculation formula is

[0061] ;

[0062] in, is the mechanical joint angle Greater than the lower limit of the mechanical joint angle error threshold The number of

[0063] If the mechanical joint angular velocity Greater than the lower limit of the mechanical joint angular velocity error threshold , then the mechanical joint angular velocity at the current acquisition moment is eliminated , get the value less than or equal to the lower limit of the mechanical joint angular velocity error threshold Angular velocity of mechanical joints , for the error less than or equal to the lower limit of the mechanical joint angular velocity error threshold Angular velocity of mechanical joints Perform the offset calculation to obtain the offset mechanical joint angular velocity The calculation formula is

[0064] ;

[0065] in, is the mechanical joint angular velocity Greater than the lower limit of the mechanical joint angular velocity error threshold The number of

[0066] If the mechanical joint movement speed Greater than the lower limit of the mechanical joint motion speed error threshold , then the mechanical joint movement speed at the current acquisition moment is eliminated , get the lower limit of the mechanical joint motion speed error threshold Mechanical joint movement speed , for the error threshold value less than or equal to the mechanical joint motion speed Mechanical joint movement speed Perform the offset calculation to obtain the offset mechanical joint movement speed The calculation formula is

[0067] ;

[0068] in, is the mechanical joint movement speed Greater than the lower limit of the mechanical joint motion speed error threshold The number of

[0069] If the mechanical joint is displaced Greater than the lower limit of the mechanical joint displacement error threshold , then the mechanical joint displacement at the current acquisition moment is eliminated , get the value less than or equal to the lower limit of the mechanical joint displacement error threshold Mechanical joint displacement , for the error less than or equal to the lower limit of the mechanical joint displacement error threshold Mechanical joint displacement Perform the offset calculation to obtain the offset mechanical joint displacement The calculation formula is

[0070] ;

[0071] in, Mechanical joint displacement Greater than the lower limit of the mechanical joint displacement error threshold The number of

[0072] If the mechanical joint position Greater than the lower limit of the mechanical joint position error threshold , then the mechanical joint position at the current acquisition time is eliminated , get the value less than or equal to the lower limit of the mechanical joint position error threshold Mechanical joint position , for the position error less than or equal to the lower limit of the mechanical joint position error threshold Mechanical joint position Perform the offset calculation to obtain the offset mechanical joint position The calculation formula is

[0073] ;

[0074] in, is the mechanical joint position Greater than the lower limit of the mechanical joint position error threshold The number of

[0075] The data processing module uploads the deviation movement behavior data to the data storage module.

[0076] It should be further explained that, in the specific implementation process, the specific process of the data storage module storing the historical collection period of the biased motion behavior data of different robots includes:

[0077] The data storage module is provided with a real-time database and a historical database to obtain the first The robot's biased movement behavior data is collected and sent to the real-time database for storage;

[0078] When the real-time database receives the When collecting the biased motion behavior data of a robot, the first The biased movement behavior data of each robot is sent to the historical database for storage;

[0079] The historical database The positive motion behavior data of the robot is marked as Historical biased motion behavior data of each robot;

[0080] It should be further explained that the historical lateral movement behavior data includes the historical lateral mechanical joint angle 、Historical bias mechanical joint angular velocity , Historical bias mechanical joint movement speed , Historical partial mechanical joint displacement and historically correct mechanical joint positions ;

[0081] The data storage module uploads the historical biased movement behavior data to the expected behavior module.

[0082] It should be further explained that, in the specific implementation process, the specific process of the expected behavior module constructing the corresponding standard expected motion behavior model includes:

[0083] Using historical biased motion behavior data of several groups of different robots in a historical collection period as training sets and test sets, and inputting the training sets and test sets into a standard expected motion behavior model, training the standard expected motion behavior model, and obtaining a standard expected motion behavior model after training;

[0084] According to the standard expected movement behavior model after training, the corresponding expected value of movement behavior is obtained The calculation formula is

[0085] ;

[0086] The expected behavior module converts the expected value of the movement behavior into Upload to the collaborative optimization module.

[0087] It should be further explained that, in the specific implementation process, the specific process of the collaborative optimization module generating the corresponding collaborative optimization instruction includes:

[0088] Get the expected values ​​of motion behaviors of different robots , according to the expected value of the movement behavior Generate corresponding collaborative optimization instructions;

[0089] It should be further explained that the collaborative optimization instructions include termination motion instructions and loop execution motion instructions;

[0090] Preset target movement behavior data and motor behavior errors ;

[0091] If | Expected value of sports behavior - Target movement behavior data |Greater than the motion behavior error When the robot is stopped, a termination instruction is generated to stop the robot and remind the maintenance personnel to check.

[0092] If | Expected value of sports behavior - Target movement behavior data |Smaller than the motion behavior error When the motion instruction is generated and executed in a loop, the robot's motion behavior data is once again normalized until the expected value of the motion behavior is - Target movement behavior data |Equal to the motion behavior error ;

[0093] If | Expected value of sports behavior - Target movement behavior data |Equal to the motion behavior error , the robot moves normally.

[0094] It should be further explained that, in the specific implementation process, the specific process of the collaborative optimization module executing the cyclic execution motion instruction includes:

[0095] Get the The cyclic execution motion instructions of the robot are parsed according to the recursive solver to obtain the first Real-time action update rate of each robot ;

[0096] Generate real-time action update rate corresponding to the The expected value of the robot's motion behavior and target movement behavior data , get real-time action update rate The calculation formula is

[0097] ;

[0098] in, is the positive control constant;

[0099] According to the real-time action update rate , for The next motion behavior of each robot is updated.

[0100] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A robot collaborative control optimization system based on wireless communication, comprising a monitoring center, characterized in that: The monitoring center is communicatively connected to a data acquisition module, a data processing module, a data storage module, an expected behavior module and a collaborative optimization module; The data acquisition module is used to collect motion behavior data of different robots, and the process includes: The data acquisition module is provided with a plurality of data acquisition units, which are arranged at different mechanical joint positions of the robot, and are used to collect motion behavior data corresponding to different mechanical joints of different robots, and set the acquisition cycle and the acquisition time; Label different robots as is a natural number; different mechanical joints of the same robot are labeled as is a natural number; The movement behavior data includes mechanical joint angle, mechanical joint angular velocity, mechanical joint movement velocity, mechanical joint displacement and mechanical joint position; The data processing module is used to perform partial-form processing on the motion behavior data of different robots to obtain partial-form processing of motion behavior data of different robots; The process of partial formal processing includes: Get the motion behavior data of a robot, and obtaining biased motion behavior data according to the motion behavior data; It should be further explained that the above-mentioned corrected motion behavior data includes corrected mechanical joint angles. , angular velocity of mechanical joints , the movement speed of the mechanical joint , partial mechanical joint displacement And correct the position of mechanical joints ; The mechanical joint angle, mechanical joint angular velocity, mechanical joint movement velocity, mechanical joint displacement and mechanical joint position in the motion behavior data are marked as as well as ; The first The different collection moments in the same collection cycle of a robot are marked as is a natural number; Get the The mechanical joint angles of the robots at different acquisition times in the same acquisition cycle , Mechanical joint angular velocity , Mechanical joint movement speed , Mechanical joint displacement and mechanical joint positions ; Set the lower limit of the mechanical joint angle error threshold , Mechanical joint angular velocity error lower threshold , Mechanical joint motion speed error lower threshold , Mechanical joint displacement error threshold lower limit And the lower limit of the mechanical joint position error threshold ; If the mechanical joint angle Greater than the lower limit of the mechanical joint angle error threshold , then the mechanical joint angle at the current acquisition moment is eliminated , get the value less than or equal to the lower limit of the mechanical joint angle error threshold Mechanical joint angle , for the error threshold less than or equal to the mechanical joint angle Mechanical joint angle Perform the offset calculation to obtain the offset mechanical joint angle The calculation formula is ； in, is the mechanical joint angle Greater than the lower limit of the mechanical joint angle error threshold The number of If the mechanical joint angular velocity Greater than the lower limit of the mechanical joint angular velocity error threshold , then the mechanical joint angular velocity at the current acquisition moment is eliminated , get the value less than or equal to the lower limit of the mechanical joint angular velocity error threshold Angular velocity of mechanical joints , for the error less than or equal to the lower limit of the mechanical joint angular velocity error threshold Angular velocity of mechanical joints Perform the offset calculation to obtain the offset mechanical joint angular velocity The calculation formula is ； in, is the mechanical joint angular velocity Greater than the lower limit of the mechanical joint angular velocity error threshold The number of If the mechanical joint movement speed Greater than the lower limit of the mechanical joint motion speed error threshold , then the mechanical joint movement speed at the current acquisition moment is eliminated , get the lower limit of the mechanical joint motion speed error threshold Mechanical joint movement speed , for the error threshold value less than or equal to the mechanical joint motion speed Mechanical joint movement speed Perform the offset calculation to obtain the offset mechanical joint movement speed The calculation formula is ； in, is the mechanical joint movement speed Greater than the lower limit of the mechanical joint motion speed error threshold The number of If the mechanical joint is displaced Greater than the lower limit of the mechanical joint displacement error threshold , then the mechanical joint displacement at the current acquisition moment is eliminated , get the value less than or equal to the lower limit of the mechanical joint displacement error threshold Mechanical joint displacement , for the error less than or equal to the lower limit of the mechanical joint displacement error threshold Mechanical joint displacement Perform the offset calculation to obtain the offset mechanical joint displacement The calculation formula is ； in, Mechanical joint displacement Greater than the lower limit of the mechanical joint displacement error threshold The number of If the mechanical joint position Greater than the lower limit of the mechanical joint position error threshold , then the mechanical joint position at the current acquisition time is eliminated , get the value less than or equal to the lower limit of the mechanical joint position error threshold Mechanical joint position , for the position error less than or equal to the lower limit of the mechanical joint position error threshold Mechanical joint position Perform the offset calculation to obtain the offset mechanical joint position The calculation formula is ； in, is the mechanical joint position Greater than the lower limit of the mechanical joint position error threshold The number of The data storage module is used to perform historical collection period storage on the bias-corrected motion behavior data of different robots to obtain the historical bias-corrected motion behavior data of different robots; The expected behavior module is used to construct a corresponding standard expected motion behavior model according to the historical biased motion behavior data of different robots; and obtain the corresponding expected value of the motion behavior according to the standard expected motion behavior model; The collaborative optimization module is used to generate a corresponding collaborative optimization solution according to the expected value of the motion behavior.

2. A robot collaborative control optimization system based on wireless communication according to claim 1, characterized in that: The process of the data storage module storing the historical collection period of the biased motion behavior data of different robots includes: The data storage module is provided with a real-time database and a historical database to obtain the first The robot's biased movement behavior data is collected and sent to the real-time database for storage; When the real-time database receives the When collecting the biased motion behavior data of a robot, the first The biased motion behavior data of each robot is sent to a historical database for storage; The positive motion behavior data of the robot is marked as The historical biased motion behavior data of a robot.

3. A robot collaborative control optimization system based on wireless communication according to claim 2, characterized in that: The process of constructing the corresponding standard expected motion behavior model by the expected behavior module includes: The historical biased motion behavior data of several groups of different robots in the historical collection period are used as training sets and test sets, and the training sets and test sets are input into the standard expected motion behavior model, the standard expected motion behavior model is trained, and the standard expected motion behavior model after training is obtained.

4. The robot collaborative control optimization system based on wireless communication according to claim 3 is characterized in that: The process of the collaborative optimization module generating the corresponding collaborative optimization instruction includes: Acquire expected values ​​of motion behaviors of different robots, and generate corresponding collaborative optimization instructions according to the expected values ​​of motion behaviors; the collaborative optimization instructions include termination motion instructions and cyclic execution motion instructions; Preset target movement behavior data and movement behavior error; like When it is greater than the motion behavior error, a termination motion instruction is generated to stop the running robot and remind maintenance personnel to check; like When it is less than the motion behavior error, a cyclic execution motion instruction is generated to perform another normalization process on the robot's motion behavior data until Equal to the motor behavior error; like When it is equal to the motion behavior error, the robot moves normally.

5. The robot collaborative control optimization system based on wireless communication according to claim 4 is characterized in that: The process of the collaborative optimization module executing the cyclic execution motion instruction includes: Obtaining a cyclic execution motion instruction of the corresponding robot, parsing the cyclic execution motion instruction according to a recursive solver, and obtaining a real-time action update rate of the corresponding robot; Generate real-time action update rate corresponding to the robot as well as , get the real-time action update rate; According to the real-time action update rate, the next motion behavior of the corresponding robot is updated in real time.

Images