A networked nonholonomically constrained multi-robot grouping consistent tracking control method, micro-control unit and control system

Abstract

The invention discloses a networked non-complete constraint multi-robot group consistent tracking control method, which belongs to the field of control technology and comprises the following steps: step one, initializing and setting each mobile robot hardware system to obtain the initial position and posture information of each mobile robot; step two, analyzing multiple groups of non-complete constraint two-wheel drive mobile robot systems to establish a high-order nonlinear Euler-Lagrangian model; step three, designing an adaptive sliding mode torque controller based on the combination of dynamics and kinematics to determine a group control protocol; step four, according to the initial state information of the mobile robot, using the trajectory equation of the mobile robot obtained in step three, and then transmitting the control information to an execution module to realize real-time control of the mobile robot, and then setting the trajectory equation of each group, and the multiple mobile robots perform trajectory tracking of a composite path according to the trajectory route, so as to realize multi-target autonomous operation and coordinated cooperation of the non-complete constraint multi-mobile robots.

Description

Technical Field

[0001] The present invention belongs to the field of control technology, and in particular relates to a networked non-holonomically constrained multi-robot grouping consistent tracking control method and system. Background Art

[0002] With the continuous expansion of the application fields and scope of mobile robots and the urgent need to realize new technological revolutions such as industrial automation and intelligence, multi-mobile robots have received more and more attention due to their unparalleled advantages over single robots. Among them, the cooperative control of multi-mobile robots with non-holonomic constraints has a wide range of potential applications and development prospects in application scenarios such as automatic navigation vehicles, highway dispatching systems and environmental monitoring. The relevant research on the cooperative principles and technologies of non-holonomic constrained multi-mobile robot systems is an international frontier research topic in artificial intelligence and intelligent robots, and is also one of the hot and difficult issues in the development and research of multi-mobile robots.

[0003] The work of early researchers focused on the single target tracking task of non-holonomic constrained multi-mobile robot systems, that is, the control protocol developed makes all robots converge to the same state. However, modern industrial production tends to be large-scale, intelligent and refined. The tasks and target system processing to be completed by multiple robots are very large and complex. At the same time, in order to cope with unforeseen situations or any unexpected changes in practice, the robot team may reach more than one consistent state. Since such systems are subject to a set of non-integrable constraints, the mechanical system is under-driven and does not satisfy the Brockett smooth feedback stability condition, that is, continuous controller design cannot guarantee system stability. On the other hand, the Lagrangian dynamics equation itself has time-varying, strongly coupled and nonlinear dynamic characteristics, which makes the design of non-holonomic constrained multi-mobile robot control system very complicated.

[0004] Sliding mode control has unique advantages in dealing with disturbances and uncertainties. However, the prerequisite is that the system parameters are known. In practical applications, when the data is inaccurate and the information is incomplete, it is difficult to obtain the system parameter values ​​of the control system. Therefore, when the system parameters of the non-holonomic constrained multi-mobile robot are unknown, sliding mode control is difficult to apply. On the other hand, early research on sliding mode control only considered the signal converted from the kinematic model as the input of the non-holonomic constrained multi-mobile robot, while in real scenarios, torque drive input is usually more appropriate. Summary of the invention

[0005] The object of the present invention is to provide a networked non-holonomic constrained multi-robot grouping consistent tracking control method.

[0006] Based on the above purpose, the present invention adopts the following technical solution:

[0007] The first aspect of the present invention is: a networked nonholonomically constrained multi-robot grouping consistent tracking control method, comprising the following steps:

[0008] Step 1: Initialize the hardware system of each mobile robot to obtain the initial position and posture information of each mobile robot;

[0009] Step 2: Analyze multiple sets of nonholonomic constrained two-wheel drive mobile robot systems and establish a high-order nonlinear Euler-Lagrangian model:

[0010]

[0011] In the above kinetic equation are the generalized coordinates and generalized velocity, M i (q i )∈R n×n is a symmetric positive definite inertia matrix, which is only related to generalized coordinates. is the Coriolis and centrifugal force matrix, G i (q i )∈R n It is powerful in a broad sense.

[0012] B i (q i )∈R n×p is the input transformation matrix, p = nm, τ i ∈R p is the input torque vector, A i (q i )∈R m×n is the constraint matrix, λ i ∈R m is the constraint matrix vector; assuming S i (q i )∈R n×p is a full rank matrix, which consists of A i (q i ) is composed of linearly independent basis vectors of the null space, that is, The original nonholonomic constrained dynamic equation can be written as

[0013]

[0014]

[0015] In the above formula, ξ i (t)∈R p is the velocity vector, valid for time t;

[0016] Step 4: According to The initial state information of the mobile robot is obtained by using the step 3 The trajectory equation of each mobile robot is calculated, and the control information is then transmitted to the execution module to realize the real-time control of the mobile robot. Then, the trajectory equation of each group is set, and multiple mobile robots perform trajectory tracking of the composite path according to the trajectory route, realizing the multi-target autonomous operation and coordinated cooperation of non-holonomic constrained multi-mobile robots.

[0017] Furthermore, in step three, an adaptive sliding mode torque controller is designed based on the combination of dynamics and kinematics to determine the grouping control protocol;

[0018] First, for robots, introducing smooth auxiliary velocity vector

[0019]

[0020] where e i =(e i1 , e i2 , e i3 ) T is the corresponding tracking position error, is the reference velocity vector, K i =(k i1 , k i2 , k i3 ) T is the control gain vector;

[0021] Then, the sliding mode auxiliary vector ξ is introduced ri ,ξ ri ∈R p

[0022]

[0023] Among them, α>0 is a designed normal number, β i >0 indicates the speed ξ of the i-th robot i With smooth velocity ξ iα The control feedback gain of

[0024] Define the sliding vector

[0025] s i =ξ i -ξ ri ,s i ∈R p ,

[0026] Give the group control protocol

[0027]

[0028] Among them, K i is a symmetric positive definite matrix, is the constant parameter ζ iThe estimated value of B i :B i (q i )∈R n×p The input transformation matrix

[0029] The adaptive law is

[0030]

[0031] Here i is a symmetric positive definite matrix, is the regression matrix of the dynamics equation, where x, y: differentiable vectors in space;

[0032] Furthermore, before designing the adaptive sliding mode torque controller in step 3, for multiple mobile robots, the robot teams can be grouped. The grouping rule is: Assume that there is a corresponding topological graph for the system composed of d robots yes The division of Divide the robot team into k groups, Represents The l-th group, l = 1, 2, ..., k, the corresponding graph is denoted by

[0033] In order to realize the control of compound trajectory tracking of multiple sets of nonholonomic constraints of two-wheel drive mobile robot system, the following assumptions are given: Assume that each has a directed spanning tree, l = 1, 2, ..., k, and The corresponding Laplacian matrix has a row sum of zero. about is in-degree balanced, m>n, m, n∈{1, 2, …, k};

[0034] Then, the trajectory equations of each group of mobile robots are set according to the adaptive torque control protocol, and each mobile robot performs trajectory tracking of the composite path according to the trajectory route, realizing multi-target autonomous operation, coordinated cooperation, and information interaction of non-holonomically constrained multi-mobile robots.

[0035] Furthermore, the process of each mobile robot tracking the trajectory of the composite path according to the trajectory route is as follows:

[0036] Given the reference trajectory of the lth group of robots

[0037]

[0038] l = 1, 2, ..., k is a grouping division of a multi-robot network. In the control protocol τ iIn the following example, i = 1, 2, ..., d, we say that we have achieved the cluster-consistent trajectory tracking of d nonholonomic constrained mobile multi-robot systems, that is, for the i-th robot, If a smooth auxiliary velocity vector is found Satisfy i → iα , where e i =(e i1 , e i2 , e i3 ) T is the corresponding tracking position error, is the reference velocity vector, K i =(k i1 , k i2 , k i3 ) T is the control gain vector. In addition, if That is, i and j are in the same group, The composite trajectory tracking goal is achieved.

[0039] The second aspect of the present invention that is sought to be protected is: a micro control unit carrying an adaptive torque control protocol or program that can execute the above-mentioned control method.

[0040] The third aspect of the present invention is: a networked non-holonomic constrained multi-robot swarm consistent tracking control system, comprising a plurality of mobile robots, each of which comprises a power module, a communication module, an information collection module, a control module and an execution module; the control module is provided with a micro-control unit as claimed in claim 5; the information collection module transmits the collected information to the control module; the control module outputs the control information to the execution module, and the execution module controls the autonomous movement and coordinated cooperation of the plurality of mobile robots according to the obtained control information, and executes the control method as described in the first aspect;

[0041] Furthermore, the information collection module includes an inertial transmitter, which is mounted on the mobile robot to obtain real-time position information and posture information of the mobile robot; the execution module is configured with an encoder, which can obtain the speed information of the motor in real time.

[0042] The fourth aspect of the present invention that is sought to be protected is: an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method for realizing consistent tracking control of networked non-completely constrained multi-robot clusters as described in the first aspect is implemented.

[0043] The fifth aspect of the present invention that is sought to be protected is: a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the networked non-holonomic constrained multi-robot group consistent tracking control method described in the first aspect is implemented.

[0044] Compared with the prior art, this application has the following advantages:

[0045] The present application can be used for the control of compound trajectory tracking of multiple groups of non-completely constrained two-wheel-driven mobile robot systems. By embedding the designed motion controller signal into the adaptive torque control protocol, based on the relative position and relative speed information of the non-completely constrained mobile robot neighbors, the autonomous operation and coordinated cooperation of multi-objective tasks of multiple groups of non-completely constrained two-wheel-driven mobile robot systems are realized; the application is also applicable to non-completely constrained multi-robot systems with uncertain parameters. The system parameters of the control system do not need to be accurately calculated. The true values ​​of the parameters are replaced by a designed estimator to ensure that the system tracking error converges to 0, that is, the mobile robots of each group are consistent with their respective reference trajectory paths and speeds, thereby realizing the control of compound trajectory tracking of multiple groups of non-completely constrained two-wheel-driven mobile robot systems.

[0046] The present invention does not require strict restrictions on algebraic conditions such as the eigenvalues ​​of the network Laplace matrix, and only relies on a simple network topology structure, which achieves the behavioral control of the ultimate goal. It overcomes the shortcomings of previous networked group control such as strict restrictions on the system algebraic structure and control gain, and is more widely applicable to actual situations. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 is a block diagram of a multi-robot system of the present invention;

[0048] Figure 2 is a simplified diagram of a nonholonomic constrained mobile robot;

[0049] Figure 3 For the demonstration of topology diagram;

[0050] Figure 4 This is the effect diagram of composite trajectory tracking;

[0051] Figure 5 This is the effect diagram of the speed output response. DETAILED DESCRIPTION

[0052] Example 1

[0053] A networked nonholonomically constrained multi-robot swarm tracking control method comprises the following steps:

[0054] Step 1: Initialize the hardware system of each mobile robot to obtain the initial position and posture information of each mobile robot.

[0055] Step 2: Analyze multiple sets of nonholonomic constraints on two-wheel-driven mobile robot systems: According to system dynamics, multiple sets of nonholonomic constraints on two-wheel-driven mobile robot systems are high-order nonlinear Euler-Lagrangian forms, and the model of the system is:

[0056]

[0057] here are the generalized coordinates and generalized velocity, M i (q i )∈R n×n is a symmetric positive definite inertia matrix, which is only related to generalized coordinates. is the Coriolis and centrifugal force matrix, G i (q i )∈R n is powerful in a broad sense, B i (q i )∈R n×p is the input transformation matrix, p = nm, τ i ∈R p is the input torque vector, A i (q i )∈R m×n is the constraint matrix, λ i ∈R m is the constraint matrix vector.

[0058] The motion constraint equation of the i-th mobile robot can be written as Assume S i (q i )∈R n×p is a full rank matrix, which consists of A i (q i ) is composed of linearly independent basis vectors in the null space, namely S i T (q i )A i T (q i )=0, the original nonholonomic constraint dynamic equation can be written as

[0059]

[0060]

[0061] In the above formula, ξ i (t)∈R p is the velocity vector, valid for time t.

[0062] Step 3: Group the robot teams. Assume that there is a corresponding topology for a system consisting of d robots. yes The division of Divide the robot team into k groups, Represents The l-th group, l = 1, 2, ..., k, the corresponding graph is denoted by

[0063] Let the generalized coordinates of system (1) be q i =[x i ,y i ,θ i ] T , the expression of the generalized velocity of the ith mobile robot is

[0064]

[0065] where ξ i =(υ i ,ω i ) T is the velocity vector of the center of mass, υ i ,ω i are the linear velocity and angular velocity respectively.

[0066] For a system consisting of d nonholonomic mobile multi-robots, about In-degree balance, if i receives The sum of information transmission And said about is in-degree balanced if Each robot in the is in-degree balanced, m, n∈{1, 2, …, k}, m≠n;

[0067] In order to realize the control of compound trajectory tracking of multiple sets of nonholonomic constraints of two-wheel drive mobile robot system, the following assumptions are given: Assume that each has a directed spanning tree, l = 1, 2, ..., k, and The corresponding Laplacian matrix has a row sum of zero. about is in-degree equilibrium, m>n, m, n∈{1,2,…,k}, the kinetic equation (1) is about the kinetic constant parameter vector ζ i is parameterizable, that is,

[0068]

[0069] Here x,y∈R p is a differentiable vector, is the regression matrix of the kinetic equation.

[0070] According to formula (3), the dynamic equation is linearly related to the dynamic parameters. The expression of the regression matrix is ​​directly obtained through the dynamic equation. Here, the true value of the parameter is replaced by a designed estimator to ensure that the system tracking error asymptotically approaches 0.

[0071] The following is an explanation of how to achieve the trajectory tracking goal. Given the reference trajectory of the l-th group of robots

[0072]

[0073] l = 1, 2, ..., k, is a grouping division of a multi-robot network. In the control protocol τ i In the following example, i = 1, 2, ..., d, we say that we have achieved the cluster-consistent trajectory tracking of d nonholonomic constrained mobile multi-robot systems, that is, for the i-th robot, If a smooth auxiliary velocity vector is found Satisfy i → iα , where e i =(e i1 , e i2 , e i3 ) T is the corresponding tracking position error, is the reference velocity vector, K i =(k i1 , k i2 , k i3 ) T is the control gain vector. In addition, if That is, i and j are in the same group, The composite trajectory tracking goal is achieved.

[0074] Step 4: Design of adaptive torque controller based on the combination of dynamics and kinematics

[0075] First, the position error is expressed as

[0076]

[0077] i=1,2,…,d, The derivative of the position error (5) can be expressed as

[0078]

[0079] For robots, introducing smooth auxiliary velocity vector

[0080]

[0081] get

[0082]

[0083] Next, we introduce the sliding mode auxiliary vector ξ ri ,ξ ri ∈R p

[0084]

[0085] Among them, α>0 is a designed normal number, β i >0 indicates the speed ξ of the i-th robot i With smooth velocity ξ iα The control feedback gain.

[0086] get

[0087]

[0088] Define the sliding vector

[0089] s i =ξ i -ξ ri ,s i ∈R p , (11)

[0090] Combining formulas (2) to (11), the group control protocol is given:

[0091]

[0092] Among them, K i is a symmetric positive definite matrix, is the constant parameter ζ i The estimated value of , the adaptive law is

[0093]

[0094] Here i is a symmetric positive definite matrix.

[0095] Substituting (12) and (13) into system (1), system (1) can be rewritten as

[0096]

[0097] here Next, the closed-loop system stability analysis is performed according to (14).

[0098] By designing feasible control algorithms, the mutual influence between different groups in the composite trajectory tracking scenario of multiple mobile robot systems is eliminated. In essence, non-holonomic constrained mobile robots are high-order nonlinear systems with under-actuated characteristics. Another difficult problem is that the controlled wheeled mobile robot machine system with non-holonomic constrained behavior is under-actuated, that is, the motion state has three degrees of freedom in one plane, but only two control inputs are used under the non-holonomic constraints. The invention scheme ensures the pre-defined transient performance of the system by introducing a smooth motion reference vector encapsulated in the motion controller into the control algorithm. The network adopted satisfies one-way information transmission, has a stable structure, and integrates multiple subgroups, which better describes the actual situation of complex group tracking tasks in engineering applications.

[0099] Step 5: Realize multi-target autonomous operation and coordinated cooperation of non-holonomically constrained multi-mobile robots

[0100] For A mobile robot is provided with a microcontroller module (MCU), in which a first The initial state information of each mobile robot is obtained, and the controller algorithm information designed in step 4 is loaded into each mobile robot micro-control unit. The mobile robot realizes real-time movement through the control of the actuator motor. The encoder configured on the actuator can obtain the speed information of the motor in real time, and the inertial sensor (IMU) carried on the mobile robot can monitor the position and posture of the mobile robot in real time. At the same time, the communication module carried can exchange data with other mobile robots;

[0101] The trajectory equations of each group are set, and the multi-mobile robots track the trajectories of the composite path according to the trajectory routes, realizing the multi-target autonomous operation and coordinated cooperation of the non-holonomic constrained multi-mobile robots. The content of information interaction follows the rule that the information transmission between groups conforms to the in-degree balance rule of step two.

[0102] Example 2

[0103] A networked nonholonomically constrained multi-robot swarm consensus tracking control system, such as Figure 1As shown, it includes multiple mobile robots, each of which includes a power module, a communication module, an information collection module, a control module and an execution module. Each mobile robot is equipped with an inertial transducer for obtaining the real-time position information L and posture information P of the mobile robot; the execution module is configured with an encoder, which can obtain the speed information V of the motor in real time; the control module is provided with a micro-control unit, and the micro-control unit carries an adaptive torque control protocol with multiple groups of incomplete constraints, and the adaptive torque control protocol is used to implement the control method of Example 1; the information collection module transmits the collected information to the control module, and the control module outputs the control information to the execution module, and the execution module controls the autonomous movement and coordinated cooperation of the multiple mobile robots according to the obtained control information, thereby realizing a networked incomplete constraint multi-robot group consistent tracking control method.

[0104] Example 3

[0105] The control method of Example 1 was used to experiment on a network model consisting of three groups and eight non-holonomic constrained multi-mobile robot systems. Figure 2 A schematic diagram of a non-holonomic constrained mobile robot, directed network topology like Figure 3 As shown, the solid line represents positive information transfer, and the dotted line represents negative information transfer. The division is The reference trajectory is given as follows

[0106]

[0107] The selected parameters are as follows

[0108]

[0109]

[0110]

[0111] m ci =30, m wi =1,I ci =15.625,I mi =0.0025, I wi =0.005, Λ i =10, a i =2, b i =0.75, d i =0.3, r i =0.15, here

[0112] m i =2m wi +mci , I i =2I mi +2m wi b i 2 +m ci d i 2 +I ci .

[0113] In network topology The desired tracking trajectory under is divided into three sub-trajectories, starting from Figure 4 It can be seen that each sub-track can be effectively tracked. Figure 5 The speed responses of the three groups are given, indicating that the eight robots in the three groups can work in coordination to complete different subtasks. Therefore, the embodiment effectively realizes the control of composite trajectory tracking of multiple groups of non-holonomic constrained two-wheel-driven mobile robot systems.

[0114] Example 4

[0115] An electronic device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, any step in a networked non-holonomic constrained multi-robot group consistent tracking control method as described in Example 1 is implemented.

[0116] Further, the process of the networked nonholonomic constrained multi-robot swarm consistent tracking control method described in Example 1 can be implemented as a computer software program. For example, this embodiment includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing the method. In such an embodiment, the computer program can be downloaded and installed from the network, and / or installed from a removable medium. When the computer program is executed by the processor, the above functions defined in the method of the present application are executed.

[0117] Example 5

[0118] A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements any step in a networked non-holonomic constrained multi-robot swarm consistent tracking control method as described in Example 1.

[0119] The computer-readable medium described in the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0120] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0121] In summary, the present invention effectively overcomes the deficiencies in the prior art and has a high industrial utilization value. The above embodiments serve to illustrate the substantive content of the present invention, but do not limit the protection scope of the present invention. Those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the essence and protection scope of the technical solution of the present invention.

Claims

1. A networked nonholonomically constrained multi-robot grouping consistent tracking control method, characterized in that: The following steps are involved: Step 1: Initialize the hardware system of each mobile robot to obtain the initial position and posture information of each mobile robot; Step 2: Analyze multiple sets of nonholonomic constrained two-wheel drive mobile robot systems and establish a high-order nonlinear Euler-Lagrangian model; In the above kinetic equation are the generalized coordinates and generalized velocity, M i (q i )∈R n×n is a symmetric positive definite inertia matrix, which is only related to generalized coordinates. is the Coriolis and centrifugal force matrix, G i (q i )∈R n is powerful in a broad sense, B i (q i )∈R n×p is the input transformation matrix, p = nm, τ i ∈R p is the input torque vector, A i (q i )∈R m×n is the constraint matrix, λ i ∈R m is the constraint matrix vector; assuming S i (q i )∈R n×p is a full rank matrix, which consists of A i (q i ) is composed of linearly independent basis vectors of the null space, that is, The original nonholonomic constrained dynamic equation can be written as In the above formula, ξ i (t)∈R p is the velocity vector, valid for time t; Step 3: Design an adaptive sliding mode torque controller based on dynamics and kinematics, and determine the group control protocol; Step 4: According to The initial state information of the mobile robot is obtained by using the step 3 The trajectory equation of each mobile robot is calculated, and the control information is then transmitted to the execution module to realize the real-time control of the mobile robot. Then, the trajectory equation of each group is set, and multiple mobile robots perform trajectory tracking of the composite path according to the trajectory route, realizing the multi-target autonomous operation and coordinated cooperation of non-holonomic constrained multi-mobile robots.

2. The control method according to claim 1, characterized in that: In step 3, the adaptive sliding mode torque controller is designed based on the combination of dynamics and kinematics, and the specific process of determining the group control protocol is as follows: First, for robots, introducing smooth auxiliary velocity vector where e i =(e i1 , e i2 , e i3 ) T is the corresponding tracking position error, is the reference velocity vector, K i =(k i1 , k i2 , k i3 ) T is the control gain vector; Then, the sliding mode auxiliary vector ξ is introduced ri ,ξ ri ∈R p Among them, α>0 is a designed normal number, β i >0 indicates the velocity ξ of the i-th robot i With smooth velocity ξ iα The control feedback gain of Define the sliding vector s i =ξ i -x ri ,s i ∈R p , Give the group control protocol Among them, K i is a symmetric positive definite matrix, is the constant parameter ζ i The estimated value of B i :B i (q i )∈R n×p The input transformation matrix adaptive law is Here i is a symmetric positive definite matrix, is the regression matrix of the dynamics equation, where x,y: differentiable vectors in space.

3. The control method according to claim 2, characterized in that: Before designing the adaptive sliding mode torque controller in step 3, for multiple mobile robots, the team of robots can be grouped. The grouping rule is: Assume that there is a corresponding topological graph for the system composed of d robots yes The division of Divide the robot team into k groups, Represents The l-th group, l = 1, 2, ..., k, the corresponding graph is denoted by In order to realize the control of compound trajectory tracking of multiple sets of nonholonomic constraints of two-wheel drive mobile robot system, the following assumptions are given: Assume that each has a directed spanning tree, l = 1, 2, ..., k, and The corresponding Laplacian matrix has a row sum of zero. about is in-degree balanced, m>n, m, n∈{1, 2, …, k}; Then, the trajectory equations of each group of mobile robots are set according to the adaptive torque control protocol, and each mobile robot performs trajectory tracking of the composite path according to the trajectory route, realizing multi-target autonomous operation, coordinated cooperation, and information interaction of non-holonomically constrained multi-mobile robots.

4. The control method according to claim 3, characterized in that: The process of each mobile robot tracking the trajectory of the composite path according to the trajectory route is: Given the reference trajectory of the lth group of robots l = 1, 2, ..., k, is a grouping division of a multi-robot network. In the control protocol τ i In the following, i = 1, 2, ..., d, it is said that the cluster-consistent trajectory tracking of d nonholonomic constrained mobile multi-robot systems is achieved, that is, for the i-th robot, If a smooth auxiliary velocity vector is found Satisfy i → iα , where e i =(e i1 , e i2 , e i3 ) T is the corresponding tracking position error, is the reference velocity vector, K i =(k i1 , k i2 , k i3 ) T is the control gain vector. In addition, if That is, i and j are in the same group, and there are The composite trajectory tracking goal is achieved.

5. A micro control unit, characterized in that: An adaptive torque control protocol or program capable of executing the control method described in any one of claims 1-4 is contained.

6. A networked nonholonomically constrained multi-robot swarm tracking control system, characterized in that: It comprises a plurality of mobile robots, each of which comprises a power supply module, a communication module, an information collection module, a control module and an execution module; the control module is provided with a micro-control unit as claimed in claim 5; the information collection module transmits the collected information to the control module; the control module outputs the control information to the execution module, and the execution module controls the autonomous movement and coordinated cooperation of the plurality of mobile robots according to the obtained control information, and executes the control method as claimed in any one of claims 1 to 4.

7. The control system according to claim 6, characterized in that: The information collection module includes an inertial transmitter, which is mounted on the mobile robot to obtain the real-time position information and posture information of the mobile robot; the execution module is equipped with an encoder to obtain the speed information of the motor in real time.

8. An electronic device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the processor executes the computer program, it implements the method for realizing consistent tracking control of networked non-holonomic constrained multi-robot swarm as described in any one of claims 1-4.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, the networked non-holonomic constrained multi-robot swarm consistent tracking control method as described in any one of claims 1-4 is implemented.

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