An event-triggered multi-manipulator consensus control method under communication constraints

Abstract

The present invention discloses a method for consistency control of multiple robotic arms based on event triggering under limited communication. The method comprises: establishing a multi-robotic arm system model for the multi-robotic arm system based on algebraic graph theory; performing algorithmic control on each robotic arm of the multi-robotic arm system model through a distributed consistency control algorithm; when performing consistency control on each robotic arm, controlling the communication between each robotic arm through a preset event triggering communication protocol; when multiple robotic arms need to send status information, allocating communication channels to the multiple robotic arms through a preset channel scheduling strategy. The technical solution in the embodiment of the present invention improves the utilization rate of the robotic arm communication channel and improves the use of limited channels by designing a channel scheduling strategy based on event triggering under limited channel conditions.

Description

Technical Field

[0001] The present invention relates to the technical field of multi-robot arm control, and in particular to a multi-robot arm consistency control method based on event triggering under limited communication. Background Art

[0002] With the rapid development of science and technology, the robotics industry is playing an increasingly important role in today's industrial landscape. As a key component of robots, robotic arms are increasingly appearing on industrial production lines. These arms, known as the "bots," possess multiple inputs and outputs, are nonlinear, and exhibit strong coupling.

[0003] However, on a production line, multiple robotic arms operate together, making their control more challenging. Furthermore, due to limited communication resources between the individual robotic arms, information from each arm cannot be transmitted to the others in a timely manner, making conventional robotic arm control algorithms ineffective in effectively controlling multi-arm systems.

[0004] Therefore, how to effectively utilize communication resources, reduce the communication frequency between robotic arms, and improve the utilization of robotic arm communication channels is an urgent problem to be solved. Summary of the Invention

[0005] In view of this, the purpose of the present invention is to provide a multi-manipulator consistency control method based on event triggering under communication constraints, and to improve the utilization rate of the manipulator communication channel and the use of limited channels by designing a channel scheduling strategy based on event triggering under channel constraints.

[0006] To achieve the above-mentioned object of the invention, the present invention provides a multi-manipulator consistency control method based on event triggering under limited communication, the method comprising:

[0007] Establish a multi-manipulator system model based on algebraic graph theory;

[0008] For the multi-manipulator system model, each manipulator is controlled by a distributed consistency control algorithm;

[0009] When performing consistency control on each robotic arm, the communication protocol is triggered by preset events to control the communication between the robotic arms;

[0010] When multiple robotic arms need to send status information, communication channels are allocated to the multiple robotic arms through a preset channel scheduling strategy.

[0011] Furthermore, the establishment of the multi-manipulator system model includes:

[0012] Constructing a communication topology of a weighted undirected graph of the multi-manipulator system;

[0013] In the communication topology, establishing a communication link between any robotic arm and its neighboring robotic arms;

[0014] Each robotic arm is used as a node of the communication topology to construct a dynamic model of any robotic arm.

[0015] Furthermore, the dynamic model of the i-th robotic arm is:

[0016]

[0017] Where i represents any robot arm, Z refers to the number of nodes in the communication topology, and M i (θ i ) is the system generalized inertia matrix, is the Coriolis matrix of the system including the centrifugal force, G i (θ i ) is the generalized gravity vector, u i (t) is the control input of the i-th manipulator at time t, θ i is the generalized coordinate of the i-th manipulator, is the generalized velocity of the i-th robot arm.

[0018] Furthermore, the construction process of the distributed consistency control algorithm includes: designing a multi-manipulator distributed consistency control input based on the multi-agent consistency theory.

[0019] Furthermore, it is characterized in that the function formula of the control input is:

[0020]

[0021] Among them, i refers to the i-th robot arm, j refers to the j-th neighbor robot arm of the i-th robot arm, N refers to the number of neighbor robots of the i-th robot arm, and u i (t) is the control input of the i-th manipulator at time t, θ i is the generalized coordinate of the i-th manipulator, θ j are the generalized coordinates of the jth neighbor robot of the i-th robot, is the generalized velocity of the i-th manipulator, a ij is an element in the adjacency matrix of the communication topology, is the event triggering moment of the i-th robotic arm, is the next event triggering time of the i-th robotic arm, is the jth neighbor robot of the i-th robot in the interval The event triggering time in T i is the gain matrix of the i-th robot arm, G i (θ i ) is the generalized gravity vector of the i-th manipulator.

[0022] Furthermore, an event trigger function and an event trigger condition are set in the event trigger communication protocol;

[0023] The event detector of any robotic arm samples local sensor information, performs calculations based on the event trigger function, and determines whether the robotic arm meets the event trigger condition;

[0024] When the event triggering condition is met, the trigger switch is closed, the control input of any one of the robotic arms is updated, and the state information at the triggering moment is sent to the neighboring robotic arm.

[0025] Furthermore, for any of the robotic arms, at other times except the event triggering moment, the robotic arm is controlled not to transmit information with its neighboring robotic arms.

[0026] Furthermore, the channel scheduling strategy divides the sending of status information by the robotic arm into two stages;

[0027] The first stage uses the calculated value of the event trigger function to provide a corresponding probability information transmission strategy based on the size of the calculated value to transmit state information; the information transmission strategy determines whether to initiate a communication request based on the probability result and uses the communication channel when initiating the communication request;

[0028] In the second phase, for the robotic arms that meet the event triggering conditions but do not initiate a communication request in the first phase, the CSMA / CA communication strategy is used to transmit status information.

[0029] Furthermore, the workflow of any robotic arm is:

[0030] The event detector performs real-time detection on any of the robotic arms, wherein any of the robotic arms obtains its own state information and the state information of its neighboring robotic arms, and then determines whether any of the robotic arms meets the event triggering condition. If the event triggering condition is not met, the event detector continues to obtain the state information of any of the robotic arms itself and the state information of its neighboring robotic arms in real time;

[0031] If the event triggering condition is met, any one of the robotic arms updates its own control input using its own state information and the state information of its neighboring robotic arms, and finally updates the state information.

[0032] Furthermore, if the event triggering condition is met, the method further includes: any one of the manipulators enters a first-stage information transmission strategy, determines whether a communication request is initiated probabilistically and a communication channel is used in the first stage; if any one of the manipulators does not initiate a communication request in the first stage, enters a second stage using a CSMA / CA communication mechanism, accesses a communication channel, and sends the state information of any one of the manipulators;

[0033] If a communication request is initiated with probability in the first stage, the communication channel is accessed to send any of the robotic arm status information.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] The technical solution of the present invention, when the communication channel of the robotic arm is limited, is based on an event-triggered channel scheduling strategy. When the number of robotic arms that meet the event triggering conditions is greater than the limited number of communication channels in the wireless communication network, it can effectively encourage the robotic arm with a large calculated value of the event triggering function to more actively send status information to the neighboring robotic arm, which helps to improve the utilization rate of the robotic arm communication channel and improve the use of limited channels.

[0036] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only preferred embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0038] Figure 1 This is a method flow chart of a multi-manipulator consistency control method based on event triggering under limited communication provided by an embodiment of the present invention;

[0039] Figure 2 This is a schematic diagram of the structure of an event-triggered communication protocol provided by an embodiment of the present invention;

[0040] Figure 3 This is a workflow diagram of a single robotic arm provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0041] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0042] It should be noted that the terms "including" and "having" and any variations thereof in the specification and claims of the present invention and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or are inherent to these processes, methods, products or apparatuses.

[0043] Example 1

[0044] Prior to the introduction of the specific embodiments of the present invention, existing patent CN118848995A already provided an event-triggered fault-tolerant control method for a robotic arm system. This method detects faults by real-time monitoring of robotic arm data, matches faults using a preset fault adjustment rule library, and executes corresponding control strategies. The real-time robotic arm data is compared with the preset motion trajectory, errors are analyzed, and the control strategy is dynamically adjusted using a fuzzy control algorithm. An optimized motion trajectory command is generated, and then safety checks are performed on the robotic arm executing the optimized trajectory command. However, communication resources between robotic arms are limited, and currently, there is still no event-triggered channel scheduling strategy for channel-limited situations.

[0045] The embodiment of the present invention proposes a multi-manipulator consistency control method based on event triggering under limited communication. Figure 1 The flowchart of the method for controlling the consistency of multiple robotic arms based on event triggering under limited communication provided by the first embodiment of the present invention is applicable to the situation where communication resources between robotic arms are limited. The method can be executed by a multi-robotic arm control system based on event triggering, and the multi-robotic arm control system based on event triggering can be configured in a multi-robotic arm system. Figure 1 As shown, the method specifically includes the following steps:

[0046] S101. Establish a multi-manipulator system model based on algebraic graph theory.

[0047] To design a good control algorithm for a multi-manipulator system, a model for the multi-manipulator system is developed based on algebraic graph theory. This embodiment of the present invention considers a system consisting of N rigid manipulators with n degrees of freedom. Using graph theory, the multi-manipulator system is described as a multi-agent system. The dynamic equations satisfied by the multi-manipulator system and the physical parameter descriptions are derived based on actual physical laws.

[0048] It should be noted that algebraic graph theory is an important branch of graph theory that focuses on the relationship and properties between graphs and matrices. It uses algebraic tools and methods to solve problems in graph theory, especially in graph representation, basic relations, subgraphs, and spanning trees.

[0049] Among them, the establishment of a multi-manipulator system model includes:

[0050] S1011. Construct a communication topology of a weighted undirected graph for a multi-manipulator system.

[0051] In an embodiment of the present invention, in order to design a good control algorithm for a multi-manipulator system, a model is constructed for the multi-manipulator system based on algebraic graph theory. In a system consisting of N manipulators, the communication topology of the weighted undirected graph of the multi-manipulator system is defined as G = (Z, E), where Z is the set of nodes in the topology graph, Z = {1, 2, ..., N}, and E is the set of edges in the topology graph. N is the number of robotic arms.

[0052] S1012: In the communication topology, establish a communication link between any robotic arm and its neighboring robotic arms.

[0053] It should be noted that in a multi-robotic arm system, all robotic arms can be regarded as independent intelligent agents. The intelligent agent is an entity that resides in the environment. It can interpret the data obtained from the environment that reflects the events occurring in the environment and perform actions that affect the environment. It can be either hardware (such as a robot) or software.

[0054] For ease of description, the following will abbreviate "the i-th robotic arm" as "robotic arm i", and "the j-th neighbor robotic arm of the i-th robotic arm" as "robotic arm j".

[0055] The set of agents adjacent to the robot arm i can be expressed as N i , N i There exists a neighboring robot j of robot i, satisfying j∈Z and (j,i)∈E, |N i |YesN i The cardinality of .

[0056] It should be noted that for any robot arm i, it is also considered as its neighboring robot arm, that is, its neighboring robot arms include all robot arms. Among them, it is meaningless for robot arm i to communicate with robot arm i, that is, a ii = 0; There are two situations when robot i communicates with a neighbor robot j other than itself. The first is: robot i and robot j do not communicate, that is, a ij =0; The second type is: Robotic arm i communicates with robotic arm j, using a ij Indicates that i and j both belong to N.

[0057] Construct the adjacency matrix A of the system communication topology graph, A=[a ij ]∈R N×N And satisfy the non-negative element a ij =a ji . a ijIt is the element in the i-th row and j-th column of the adjacency matrix A, representing the communication link between robot i and robot j. The degree of robot i in the communication topology is defined as

[0058] Specifically, an edge in the topology graph G is defined as (i, j), which represents the communication link between agent i and agent j. In the communication topology graph, no agent is allowed to communicate with itself, so we can get a ii = 0. When robot i communicates with robot j, a ij >0.

[0059] Furthermore, we can get the Laplace matrix of the topological graph L = [l ij ]∈R N×N ,definition Among them, l ij With l ii are the elements in the Laplacian matrix.

[0060] S1013: Take each robotic arm as a node of the communication topology and construct a dynamic model of any robotic arm.

[0061] For the dynamics of the N-manipulator system, each manipulator is considered as a node in the communication topology graph, whose set is Z = {1, 2, ..., N}. The dynamic model of manipulator i is:

[0062]

[0063] Among them, M i (θ i )∈R N×N is the system generalized inertia matrix, is the Coriolis matrix of the system including the centrifugal force, G i (θ i )∈R N×N is the generalized gravity vector, u i (t)∈R N is the control input of robot arm i, θ i ∈R N is the generalized coordinate of robot arm i, is the generalized velocity of robot arm i.

[0064] In the dynamic model of the robot arm, the state error of the robot arm can be obtained based on the generalized coordinate measurement error and the generalized velocity measurement error of the robot arm.

[0065] The generalized coordinate measurement error of robot arm i is:

[0066]

[0067] The measurement error of the generalized velocity of robot arm i is:

[0068]

[0069] According to the measurement errors of generalized coordinates and generalized velocities, the state error of robot arm i can be obtained as:

[0070]

[0071] in, is the event triggering moment of robot arm i, which satisfies the condition k∈N. This moment is obtained by robot arm i calculating its own event triggering condition.

[0072] It should be noted that the state of each robotic arm is updated through the dynamic model.

[0073] S102: For the multi-manipulator system model, each manipulator is controlled by a distributed consistency control algorithm.

[0074] To achieve consistent control of a multi-manipulator system, this paper proposes a distributed consensus controller algorithm for this system. By measuring the error between each manipulator's actual state and the state at the trigger moment, and integrating this with multi-agent system consistency theory, a distributed consensus control protocol for each manipulator is designed. This allows for effective consistent control of a multi-agent system composed of multiple manipulators.

[0075] Specifically, the distributed controller algorithm of the multi-robotic arm system includes: designing the distributed consistency control input of the multi-robotic arm based on the multi-agent consistency theory.

[0076] Among them, the function formula of control input is:

[0077]

[0078] in, is the event triggering moment of robot arm i, is the next event triggering time of robot arm i, is the neighbor robot j in the interval The event triggering time in T i is the gain matrix of robot arm i, G i (θ i ) is the generalized gravity vector of robot arm i.

[0079] It can be seen from the consistency control input expression of robot arm i that the consistency control input of robot arm i is not only related to the state of robot arm i, but also to the state of robot arm j adjacent to robot arm i. That is, the consistency control input of robot arm i is at the time when robot arm i triggers its own event. The update is also implemented at the time of the event triggering of the neighbor robot arm j To achieve the update, the distributed consistency control input of multiple robotic arms can be rewritten as:

[0080]

[0081] S103 , when performing consistency algorithm control on each robotic arm, triggering a communication protocol through a preset event to control the communication between the robotic arms.

[0082] To effectively reduce the communication burden within a robotic arm system and the frequency of inter-arm communication, an embodiment of the present invention designs an event-triggered communication protocol based on an event-triggered mechanism. The event-triggered function in the communication protocol consists of a state error function for each robotic arm and a designed threshold function. This event-triggered communication protocol effectively reduces the frequency of inter-arm communication and alleviates the communication burden.

[0083] In order to effectively reduce the communication burden in a multi-manipulator system and reduce the communication frequency between each manipulator, an embodiment of the present invention designs an event-triggered communication protocol based on an event-triggered mechanism.

[0084] Figure 2 This is a schematic diagram of the structure of an event-triggered communication protocol provided by an embodiment of the present invention. Figure 2 As shown, the event-triggered communication scheme uses event-triggered detection to determine whether robot arm i updates its own control input and sends status information to neighboring robot arms.

[0085] The principle is as follows: an event trigger function and event trigger conditions are pre-set in the event-triggered communication protocol. Robot i's event detector samples local sensor information and performs calculations based on the pre-defined event trigger function to determine whether robot i meets the event trigger conditions. When the event trigger conditions are met, the trigger switch closes. Robot i uses the status information received from neighboring robots and its own status information to update its control inputs and transmit the status information at the time of triggering to the neighboring robot.

[0086] The purpose of the event-triggered communication protocol is to achieve system consistency control while reducing the number of communications between each robot. The consistency control input expression for robot i shows that each robot updates its own event triggering time and the event triggering time of its neighboring robots. Based on event triggering theory, the next triggering time of robot i is defined as:

[0087]

[0088] For robot arm i, the event trigger function is designed as follows:

[0089]

[0090] in, β i are the preset coefficients, α, λ i , γ i , τ i are all constants, T i is the gain matrix of robot arm i, T max With T min Yes T i The largest and smallest elements in , σ i (t) is the function to be determined, T min =min{T i}, T max =max{T i}, 0<λ i <1, is the exponentially decaying gain, is an exponential decay rate and satisfies

[0091] It can be seen from the event trigger function that when the event trigger function meets the trigger condition When the event is triggered, the defined event is triggered. The triggering time of each robot is calculated by the state variable of the robot. Is the calculated value greater than or equal to 0? When it is greater than or equal to 0, the control input of the robot arm is updated and remains unchanged until the next event is triggered. For any robot, except when an event is triggered, it is controlled not to transmit information to its neighboring robots. That is, the control input remains unchanged between two consecutive event triggering times. During the interval between event triggering, robot i does not transmit information to its neighboring robots. This event-triggered strategy thus reduces the communication burden in the multi-robot system and reduces the frequency of communication between individual robots.

[0092] For a multi-robotic arm system, under the condition that the system communication topology is connected, any robotic arm in the multi-robotic arm system can reach consensus under the distributed consistency control algorithm and event triggering strategy.

[0093] S104: When multiple robotic arms need to send status information, communication channels are allocated to the multiple robotic arms using a preset channel scheduling strategy.

[0094] Due to the limited nature of communication resources, the robotic arms that meet the event triggering conditions at the same time cannot simultaneously use the limited communication channels for data transmission. To solve this problem, an embodiment of the present invention designs a channel scheduling strategy.

[0095] The channel scheduling strategy divides the period when the robot arm sends status information into two stages. In the first stage, the calculated value of the event trigger function is used to propose an information transmission strategy with corresponding probability according to the size of the calculated value. The probability is used to determine whether to initiate a communication request, and the communication channel is used when the communication request is initiated. In the second stage, for the robot arm that meets the event trigger conditions but does not initiate a communication request in the first stage, the CSMA / CA communication strategy is used to realize the transmission of the robot arm status information.

[0096] Specifically, based on the event-triggered communication strategy, define the binary variable ξ i ∈{1,0} indicates whether the robot arm i meets the event triggering condition

[0097] Definition ξ i = 0 means that robot arm i does not meet the event triggering condition and does not need to send its own status information to neighboring robot arm j. Define ξ i =1 means that the robot arm i meets the event triggering condition, and the robot arm i can access the communication channel to send its own status information to the neighboring robot arm j. i The expression is:

[0098]

[0099] All robotic arms in a multi-robotic system share the same wireless communication network with limited communication resources. Limited communication resources here refer to channel limitations caused by the limited bandwidth of the wireless spectrum. That is, at any time t, the wireless communication network allows at most ε robotic arms to successfully access the limited communication channel. This can be expressed as follows:

[0100]

[0101] The event-triggered communication strategy shows that at the same time, multiple robotic arms may meet the event triggering conditions and send status information to neighboring robotic arms. However, when robotic arm i initiates a request to access the communication channel, it may not successfully compete for the right to use the communication channel.

[0102] Defining binary variables It means that robot arm i initiates a request to access the communication channel at the moment of its event triggering and successfully accesses the communication channel.

[0103] make If robot arm i fails to access the channel successfully, it cannot send its own status information to its neighbor robot arm j. If robot i successfully accesses the channel, it can send its own status information to its neighbor robot j. The expression is:

[0104]

[0105] If at the same time, the number of robotic arms that meet the event triggering conditions is less than or equal to the limited number of communication channels in the wireless communication network ε, then all robotic arms that meet the event triggering conditions can successfully access the communication channel and send status information to neighboring robotic arms. However, when the number of robotic arms that meet the event triggering conditions is greater than the limited number of communication channels ε of the wireless communication network, The robotic arms that meet the event triggering conditions need to compete for limited communication channels. Obey the following Bernoulli distribution:

[0106]

[0107] From the above equation, we can see that at this point, the manipulators that meet the event triggering conditions have the same probability of successfully competing for the communication channel. In this case, only some of the manipulators that meet the event triggering conditions can send status information. At this moment, for the multi-manipulator system, some manipulators will be unable to update their control inputs because they cannot obtain the status information of their neighbors, thus failing to achieve consistent control of the multi-manipulator system.

[0108] The embodiment of the present invention designs a channel scheduling strategy. The strategy is divided into two stages. The first stage designs the information transmission strategy corresponding to the probability based on the calculated value of the event trigger function. The strategy has the following structure

[0109]

[0110] in, It is a parameter defined based on the calculated value of the event trigger function of the robot arm i, specifically: The larger the calculated value of is, the greater the calculated probability ω i The bigger.

[0111] Based on the above probability, the information transmission strategy can be obtained. In the first stage, the event triggering conditions are met and The robotic arm with a larger calculation value is more likely to successfully initiate a communication request and use the communication channel.

[0112] For the robotic arms that meet the event triggering conditions but do not initiate a communication request in the first phase, they will enter the second phase.

[0113] In the second phase of the designed channel scheduling strategy, the robotic arm will adopt the CSMA / CA communication mechanism to realize the transmission of robotic arm status information.

[0114] CSMA / CA stands for Carrier Sense Multiple Access. This access method is used for carrier transmission in wireless networks. Just like wired networks, wireless networks also need to avoid collisions in communication information. However, since wireless networks lack cables, systems connected to the network cannot sense or monitor whether there are any collisions in the network when sending data. Therefore, in this method, when a system wants to send data, it first senses whether there are other information transmissions in progress. If other transmissions are detected, the system waits for a short period of time before checking the network again. If no other transmissions are detected, the system waits for a random short period of time before sending the data. When the destination receives the data, it responds to the sending system with a received message to inform it of the data. However, if the sending system does not receive the received message from the destination, the sending system starts the above process again.

[0115] For the robotic arms in the second stage, each robotic arm will use the CSMA / CA communication mechanism to send its own status information to its neighboring robotic arms. The robotic arms entering the second stage must compete for the remaining idle channels with equal probability to ensure that all robotic arms that meet the event trigger conditions at that moment send status information, thereby achieving good control of the multi-robotic arm system.

[0116] Figure 3 This is a workflow diagram of a single robotic arm provided by an embodiment of the present invention, such as Figure 3 As shown, under the method provided in the embodiment of the present invention, the workflow of a single robotic arm i is as follows:

[0117] Event detector i performs real-time detection on robot arm i, obtains the state information of robot arm i itself, and then determines whether robot arm i meets the event triggering condition. If the condition is not met, it continues to obtain the state information of robot arm i itself in real time;

[0118] If the trigger condition is met, on the one hand, robot i obtains the status information of the neighboring robot arm, then updates its own control input, and finally updates the status information;

[0119] On the other hand, if the robot arm i meets the event trigger condition, it will enter the first stage of information transmission strategy. According to the calculated value of the event trigger function, it will determine whether to initiate a communication request and use the communication channel in the first stage. If the robot arm i meets the event trigger condition but does not initiate a communication request in the first stage, that is, the channel cannot be obtained in the first stage, it will enter the second stage using the CSMA / CA communication mechanism and access the communication channel to send the robot arm i status information.

[0120] If a communication request is initiated with probability in the first stage, the communication channel is accessed to send the state information of the robot arm i.

[0121] The technical solution of this embodiment of the present invention effectively controls a multi-manipulator system based on multi-agent theory. Each manipulator is considered an agent in the multi-agent system, facilitating the description of complex multi-manipulator systems. It also employs an event-triggered communication mechanism and a channel scheduling strategy based on event triggering results, effectively reducing the frequency of inter-manipulator communication, minimizing communication resource usage, and improving communication channel utilization.

[0122] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A multi-manipulator consistency control method based on event triggering under communication constraints, characterized in that: include: Establish a multi-manipulator system model based on algebraic graph theory; For the multi-manipulator system model, each manipulator is controlled by a distributed consistency control algorithm; When performing consistency control on each robotic arm, the communication protocol is triggered by preset events to control the communication between the robotic arms; When multiple robotic arms need to send status information, communication channels are allocated to the multiple robotic arms using a preset channel scheduling strategy; The construction process of the distributed consensus control algorithm includes: designing the distributed consensus control input of multiple robotic arms based on the state error of the robotic arms and the multi-agent consensus theory; The function formula of the consistency control input is: ； Where i refers to the i-th robot arm, j refers to the j-th neighbor robot arm of the i-th robot arm, and N refers to the number of neighbor robots of the i-th robot arm. is the control input of the i-th robot at time t, is the generalized coordinate of the i-th manipulator, are the generalized coordinates of the jth neighbor robot of the i-th robot, is the generalized velocity of the ith manipulator, are the elements in the adjacency matrix of the communication topology, is the event triggering moment of the i-th robotic arm, is the next event triggering time of the i-th robotic arm, is the jth neighbor robot of the i-th robot in the interval The event triggering moment in is the gain matrix of the i-th robot arm, is the generalized gravity vector of the i-th manipulator.

2. The method according to claim 1, characterized in that The multi-manipulator system model is established, including: Constructing a communication topology of a weighted undirected graph of the multi-manipulator system; In the communication topology, establishing a communication link between any robotic arm and its neighboring robotic arms; Each robotic arm is used as a node of the communication topology to construct a dynamic model of any robotic arm.

3. The method according to claim 2, characterized in that The dynamic model of the i-th robotic arm is: ； Where i represents any robot arm, Z refers to the number of nodes in the communication topology, is the system generalized inertia matrix, is the Coriolis matrix of the system including the centrifugal force, is the generalized gravity vector, is the control input of the i-th robot at time t, is the generalized coordinate of the i-th manipulator, is the generalized velocity of the i-th robot arm.

4. The method according to claim 1, wherein Setting an event trigger function and event trigger conditions in the event trigger communication protocol; The event detector of any robotic arm samples local sensor information, performs calculations based on the event trigger function, and determines whether the robotic arm meets the event trigger condition; When the event triggering condition is met, the trigger switch is closed, the control input of any one of the robotic arms is updated, and the state information at the triggering moment is sent to the neighboring robotic arm.

5. The method according to claim 4, characterized in that For any of the robotic arms, at other times except the event triggering moment, control the robotic arm not to transmit information with its neighboring robotic arms.

6. The method according to claim 4, characterized in that The channel scheduling strategy divides the sending of status information by the robot arm into two stages; The first stage uses the calculated value of the event trigger function to provide a corresponding probability information transmission strategy based on the size of the calculated value to transmit state information; the information transmission strategy determines whether to initiate a communication request based on the probability result and uses the communication channel when initiating the communication request; In the second phase, for the robotic arms that meet the event triggering conditions but do not initiate a communication request in the first phase, the CSMA / CA communication strategy is used to transmit status information.

7. The method according to claim 6, characterized in that The workflow of any robotic arm is: The event detector performs real-time detection on any of the robotic arms, wherein any of the robotic arms obtains its own state information and the state information of its neighboring robotic arms, and then determines whether any of the robotic arms meets the event triggering condition. If the event triggering condition is not met, the event detector continues to obtain the state information of any of the robotic arms itself and the state information of its neighboring robotic arms in real time; If the event triggering condition is met, any one of the robotic arms updates its own control input using its own state information and the state information of its neighboring robotic arms, and finally updates the state information.

8. The method according to claim 7, characterized in that If the event triggering condition is met, the method further includes: any one of the robotic arms enters the first phase of the information transmission strategy, and determines whether to initiate a communication request to access the wireless communication network and use the communication channel with probability in the first phase according to the calculated value of the event triggering function; if any one of the robotic arms does not initiate a communication request in the first phase, then enters the second phase using the CSMA / CA communication mechanism, accesses the communication channel and sends the state information of any one of the robotic arms; If communication is initiated probabilistically in the first stage, the communication channel is accessed to send any of the robotic arm status information.

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