A bidirectional formation tracking control method, micro-control unit and control system for a networked multi-robot system

Abstract

The present invention discloses a bidirectional formation tracking control method for a networked multi-robot system, which belongs to the field of control technology and comprises the following steps: S1: establishing a networked communication topology with a cooperative competition structure; S2: building a Lagrangian robot model; S3: determining a formation control protocol for a distributed formation; S4: adding and setting a virtual leader; S5: setting the trajectory equation of the virtual leader; S6: determining a tracking control protocol for a distributed formation; S7: according to the system equation of the virtual leader described in step S5, transmitting the tracking control protocol to an execution module to realize formation tracking control, so that multiple robots can perform tracking task collaboration under the restriction of the formation space position.

Description

Technical Field

[0001] The present invention belongs to the field of control technology, and in particular relates to a two-way formation tracking control method, a micro-control unit and a control system for a networked multi-robot system. Background Art

[0002] The rapid development of robotics has brought revolutionary impacts on people's production and life. For example, in industrial production, military reconnaissance, domestic services, space operations and other fields, robotics technology is everywhere. Single robots can generally be used to complete simple tasks, but they have disadvantages such as large size, high energy consumption, complex structure and poor flexibility. In terms of information acquisition, information processing and control capabilities, the technical level of single robots is limited, especially when the tasks are complicated and the working environment is changeable, it is difficult for single robots to cope with it. Therefore, with the accelerated development of "robotization" in the industrial field, the workload, variability of the working environment and the heavy and complex tasks are constantly increasing. Single robot operations can no longer meet complex working conditions, and multi-robot systems are born. In this context, the key technology of collaborative control of multi-robot systems is particularly important.

[0003] Compared with centralized control, the advantage of distributed control is that it can complete the task while overcoming the defects of large computational complexity and energy consumption caused by centralized control, and has higher application value. Formation control is a hot research issue in the collaborative control of multi-agent systems. It requires each individual in the system to maintain a certain geometric shape during the execution of the task to adapt to the environmental constraints in which it is located. For example, in the seabed survey mission, there are certain requirements for the location of the submarine carrying the detector to ensure the coverage of the survey range and improve the validity of the data.

[0004] In recent years, a large number of scholars at home and abroad have conducted in-depth research on the distributed formation control of multi-agent systems and have achieved fruitful research results. However, the current technology of bidirectional formation control of multi-agent systems still has a large gap in the diversity of control algorithms and control systems. Summary of the invention

[0005] In view of the problems and shortcomings in the prior art, the purpose of the present invention is to provide a two-way formation tracking control method, a micro-control unit and a control system for a networked multi-robot system.

[0006] To achieve the purpose of the invention, the technical solution adopted by the present invention is as follows:

[0007] A first aspect of the present invention provides a bidirectional formation tracking control method for a networked multi-robot system, comprising the following steps:

[0008] S1: Network each robot and design a networked communication topology with a cooperative competition structure;

[0009] S2: Analyze the kinematics and dynamics of multiple groups of single robots and establish a high-order nonlinear Lagrangian robot model;

[0010]

[0011] in 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 a broadly powerful i ∈R n is the input moment vector;

[0012] When considering the case of a kinetic equation with uncertain parameters, the Lagrangian kinetic expression should be used, which has the characteristic of linear regression with respect to a certain constant parameter:

[0013]

[0014] in is the parameter uncertainty equation with respect to the constant parameter θ i The linear regression matrix, x, y is the space R n Any differentiable vector in ;

[0015] S3: Based on the structure of the networked communication topology designed in step S1 and the robot dynamics built in step S2, an adaptive torque controller is designed to determine a distributed formation control protocol.

[0016] S4: adding and setting a virtual leader to the robot system on the basis of ensuring the formation in step S3;

[0017] S5: Set the trajectory equation of the virtual guide based on the requirements of the target task;

[0018] S6: Under the premise of maintaining the same adaptive control mode as in step S3, based on the trajectory equation of the virtual leader, determine the distributed formation tracking control protocol (protocols for distributed formation tracking control);

[0019] S7: According to the trajectory equation of the virtual leader described in step S5, the tracking control protocol of the distributed formation is transmitted to the execution module to realize the formation tracking control, so that multiple robots can perform tracking task collaboration under the constraints of the formation space position.

[0020] Furthermore, in step S1, each robot is networked and the specific process of designing a network communication topology with a cooperative competition structure is as follows:

[0021] Determine the information collection authority and the information access authority of the communication part according to the edge set, set the information use to be one-way according to the directed graph, and adjust the sign of the system feedback as input in the control part according to the positive and negative signs of the edge weights. The above process is that the closed-loop system divides the feedback into two types as input in a distributed form for adaptive adjustment to achieve collaborative formation;

[0022] Design The information topology diagram corresponding to the networked system composed of N robots, yes The node set of yes The edge set of is the index set; accordingly, let The adjacency matrix of Let its Laplace matrix be

[0023] In order to realize the control of bidirectional tracking of multi-robot system, it is assumed that There are edges with positive and negative weight values, and they meet the following requirements: is a directed graph and there exists a directed spanning tree; is structurally balanced; accordingly, there is a normative matrix Φ = diag{φ1, φ2, …, φ N} makes all elements of ΦAΦ non-negative, where

[0024] Furthermore, the specific process of determining the distributed formation control protocol in step S3 is:

[0025] If in a control mode, the system state has Then the system is said to form a formation F;

[0026] First, for robot i, (i = 1, 2, ..., N) a reference velocity vector is introduced: in are the generalized coordinates and generalized velocity of robot i, a ij For edge e ij The weight of , sgn(·) is the sign function;

[0027] Then, determine the error vector (auxiliary velocity vector) s i =q i -r i ,

[0028] Finally, the control protocol that the i-th robot obeys regarding the formation of the formation is given Among them, K i is a symmetric positive definite matrix, is a constant parameter vector θ i The estimated value of and satisfies the adaptive law:

[0029]

[0030] Here Δ i is a symmetric positive definite coupling matrix, is the dynamic equation with respect to the constant parameter vector θ i The regression matrix.

[0031] Furthermore, the specific contents of adding and setting a virtual guide to the robot system in step S4 are:

[0032] Update the communication topology according to the conditions in step S1 to Considering that the virtual guide is used to provide reference routes and is not used to complete complex tasks, a first-order robot system is built for it;

[0033] The first-order linear system of the leader robot is: Let it be node o, and The corresponding adjacency matrix is ​​expanded to in Is Column vector composed of .

[0034] Furthermore, the system equation of the virtual guide in step S5 is:

[0035] Furthermore, the process of determining the tracking control protocol of the distributed formation in step S6 includes:

[0036] The reference velocity vector of robot i, (i=1, 2, ..., N) is: Among them, a ij For edge e ij The weight, l i is the connection relationship and weight between the leader and robot i in the communication topology graph, are the generalized coordinates and generalized velocity of robot i, For the index set.

[0037] A second aspect of the present invention provides a universal micro control unit carrying an adaptive torque control protocol or program capable of executing the above control method.

[0038] The third part of the present invention provides a networked multi-robot system bidirectional formation tracking control system, including multiple mobile robots, each mobile robot includes a power module, a communication module, a data collection module, a control module and an execution module; the control module is provided with a micro-control unit; the data collection module transmits the collected information to the control module; the control module converts the control protocol into a control language readable by the execution module, and outputs it to the execution module, and the execution module controls the autonomous movement and coordinated cooperation of the multiple mobile robots according to the instructions of the control information, and executes the control method described in the first aspect.

[0039] 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.

[0040] A fourth aspect of the present invention provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and wherein the processor, when executing the computer program, implements any step in the method for bidirectional formation tracking control of a networked multi-robot system as described in any one of claims 1-6.

[0041] A fifth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a computer processor, any step of the method for bidirectional formation tracking control of a networked multi-robot system described in the first aspect is implemented.

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] The present invention is used to solve the problems of formation and formation collaborative control of a multi-robot system. A consistency algorithm is used under a bilateral communication mechanism and torque is used to perform distributed control of multiple robots to achieve formation formation and formation tracking control, so that multiple robots can collaborate in tracking tasks under the constraints of the formation's spatial position.

[0044] Compared with the prior art, the present invention adopts a bilateral communication mechanism to greatly reduce the amount of calculation of the system, making the system have a faster response, and the Lagrangian robot has a wider range of scene applications. At the same time, the control algorithm constructed by the present invention has high stability, can reduce the communication burden of the network, and reduce its requirements for network communication capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1It is a flow chart of the bidirectional formation tracking control system of the networked multi-robot system of the present invention;

[0046] Figure 2 An information topology diagram of the networked system in the present invention;

[0047] Figure 3 is a position change diagram of the robot in Example 3 of the present invention;

[0048] Figure 4 is a speed variation diagram of the robot in Example 3 of the present invention;

[0049] Figure 5 is a relative position diagram of the robot in Example 3 of the present invention;

[0050] Figure 6 is a random sampling of the robot formation process in Example 3 of the present invention;

[0051] Figure 7 This is a diagram of the robot formation and tracking trajectory in Example 3 of the present invention. DETAILED DESCRIPTION

[0052] The present invention will be further described below in conjunction with specific embodiments.

[0053] Embodiment 1:

[0054] A bidirectional formation tracking control method for a networked multi-robot system comprises the following steps:

[0055] S1: Network each robot and design a networked communication topology with a cooperative competition structure;

[0056] Determine the information collection authority and the information access authority of the communication part according to the edge set, set the information use to be one-way according to the directed graph, and adjust the sign of the system feedback as input in the control part according to the positive and negative signs of the edge weights. The above process is that the closed-loop system divides the feedback into two types as input in a distributed form for adaptive adjustment to achieve collaborative formation;

[0057] Design The information topology diagram corresponding to the networked system composed of N robots, yes The node set of yes The edge set of is the index set. Correspondingly, let The adjacency matrix of Let its Laplace matrix be

[0058] In order to realize the control of bidirectional tracking of multi-robot system, it is assumed that There are edges with positive and negative weight values, and they meet the requirements: is a directed graph and there exists a directed spanning tree; is structurally balanced; accordingly, there is a normative matrix Φ = diag{φ1, φ2, …, φ N} makes all elements of ΦAΦ non-negative, where

[0059] S2: Analyze the kinematics and dynamics of multiple groups of single robots and establish a high-order nonlinear Lagrangian robot model;

[0060]

[0061] in, 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 a broadly powerful i ∈R n is the input moment vector;

[0062] When considering the case of a kinetic equation with uncertain parameters, the Lagrangian kinetic expression should be used, which has the characteristic of linear regression with respect to a certain constant parameter:

[0063]

[0064] in is the parameter uncertainty equation with respect to the constant parameter θ i The linear regression matrix, x, y is the space R n Any differentiable vector in .

[0065] S3: Based on the structure of the networked communication topology designed in step S1 and the robot model built in step S2, an adaptive torque controller is designed to determine the formation control protocol of the distributed formation;

[0066] If in a control mode, the system state has Then the system is said to form a formation F;

[0067] First, for robot i, (i = 1, 2, ..., N), a reference velocity vector is introduced:

[0068]

[0069] in are the generalized coordinates and generalized velocity of robot i, aij For edge e ij The weight of , sgn(·) is the sign function;

[0070] Then, determine the error vector (auxiliary velocity vector)

[0071] s i =q i -r i , (4)

[0072] Finally, the control protocol that the i-th robot obeys regarding the formation of the formation is given

[0073]

[0074] Among them, K i is a symmetric positive definite matrix, is a constant parameter vector θ i The estimated value of and satisfies the adaptive law:

[0075]

[0076] Here Δ i is a symmetric positive definite coupling matrix, is the dynamic equation with respect to the constant parameter vector θ i The regression matrix.

[0077] S4: adding and setting a virtual leader to the multi-robot system on the basis of ensuring the formation of the team in step S3;

[0078] First, update the communication topology according to the provisions of step S3 to

[0079] Second, considering that the virtual guide is used to provide reference routes and is not used to complete complex tasks, a first-order robot system is built for it;

[0080] The leader robot has a first-order linear system: Let it be node O, and The corresponding adjacency matrix is ​​expanded to in Is Column vector composed of .

[0081] S5: Set the system equation of the virtual guide based on the requirements of the target task;

[0082] The trajectory q of the formation tracking required in the mission objective l (t), the trajectory vector of the virtual leader is q l(t), so the system equation of the virtual leader with a first-order linear system described in S4 is

[0083] S6: Under the premise of maintaining the same adaptive control method as in step S3, determining the tracking control protocol of the distributed formation;

[0084] Set the trajectory vector of the virtual leader to q l (t)

[0085] First, for robot i, (i = 1, 2, ..., N), a reference velocity vector is introduced:

[0086]

[0087] Then, determine the error vector (auxiliary velocity vector) ξ i =q i -ζ i ,

[0088] Finally, the control protocol that the i-th robot follows regarding the formation is given

[0089]

[0090] in, is a symmetric positive definite matrix, is a constant parameter vector θ i The estimated value of and satisfies the adaptive law:

[0091]

[0092] here is a symmetric positive definite coupling matrix, is the dynamic equation with respect to the constant parameter vector θ i The regression matrix.

[0093] S7: According to the trajectory equation of the virtual leader described in step S5, the tracking control protocol of the distributed formation is transmitted to the execution module to realize the formation tracking control, so that multiple robots can perform tracking task collaboration under the constraints of the formation space position.

[0094] Embodiment 2:

[0095] A networked multi-robot system bidirectional formation tracking control system, the system comprising a plurality of independent mobile robots, each of which comprises a power module, a communication module, a data collection module, a control module and an execution module; each mobile robot is equipped with an inertial transducer for obtaining real-time position information L and posture information P of the mobile robot; the execution module is provided with an encoder for obtaining real-time speed information V of the motor; the control module is provided with a micro-control unit; the data collection module transmits the collected information to the control module, the control module converts the control protocol into a control language readable by the execution module, and outputs it to the execution module, the execution module controls the autonomous movement and coordinated cooperation of the plurality of mobile robots according to the instructions of the control information, and executes the control method described in Example 1;

[0096] like Figure 1 As shown, the specific process is as follows:

[0097] Step 1: The communication module provides a networked communication topology diagram with a cooperative competition structure, and allocates information rights to robot i according to the networked communication topology;

[0098] Step 2: The data collection module obtains the information q(t) of the multi-robot system at the current moment.

[0099] Step 3: According to the information permissions in step 1, robot i obtains the current data information q j (t)

[0100] Step 4: Robot i inputs the data information obtained in step 3 into its own controller, and updates the torque according to the distributed formation control protocol in step S3 of embodiment 1: τ i (t);

[0101] Step 5: Robot i converts the torque τ obtained in step 4 i (t) converted into control information and input into the actuator;

[0102] Step 6: According to the acceleration obtained by the actuator, robot i adjusts its speed and position;

[0103] Step 7: Based on step 6, the multi-robot system updates its status information;

[0104] Step 8: Repeat steps 2 to 7 until formation F is formed;

[0105] Step 9: Add a virtual leader and execute step 1;

[0106] Step 10: Define the trajectory of the virtual guide;

[0107] Step 11: Repeat the operations of step 2 to step 7 until the formation tracking task is completed; wherein the control protocol of step 4 is replaced with the tracking control protocol of the distributed formation of S6 in Example 1.

[0108] Embodiment 3:

[0109] A method for performing bidirectional formation tracking of a networked multi-robot system using the control system described in Example 2 comprises the following steps:

[0110] S1: Network each robot and design a networked communication topology with a cooperative competition structure;

[0111] Determine the information collection authority and the information access authority of the communication part according to the edge set, set the information use to be one-way according to the directed graph, and adjust the sign of the system feedback as input in the control part according to the positive and negative signs of the edge weights. The above process is that the closed-loop system divides the feedback into two types as input in a distributed form for adaptive adjustment to achieve collaborative formation;

[0112] like Figure 2 As shown, The information topology diagram corresponding to the networked system composed of 8 robots, yes The node set of yes The edge set of is the index set. Correspondingly, let The adjacency matrix of Let its Laplace matrix be

[0113] To realize the bidirectional tracking control of the multi-robot system, Figure There are edges with positive and negative weight values, and they meet the requirements: is a directed graph and there exists a directed spanning tree; The structure is balanced.

[0114] The details are as follows:

[0115] Adjacency Matrix

[0116] Laplacian Matrix

[0117] Normalize the matrix

[0118] In the absence of a leader, the communication between the two groups of robots 1, 2, 3, 4 and 5, 6, 7, 8 is set to have a bilateral relationship. The edge relationship between the robots in is: l1 = -1, and li =0, i=2, 3, ..., 8, which means that the leader only communicates with robot number 1 in a one-way negative connection.

[0119] S2: Analyze the kinematics and dynamics of multiple groups of single robots and establish a high-order nonlinear Lagrangian robot model;

[0120]

[0121] in

[0122] The values ​​of the mass and length of the rod are shown in Table 1:

[0123] Table 1

[0124] Robot Number 1 2 3 4 5 6 7 8 Mass in x direction / kg 1.40 1.60 1.80 2.00 2.20 2.40 2.60 2.80 Mass in y direction / kg 1.52 1.64 1.76 1.88 2.00 2.12 2.24 2.36 Length in x direction / m 1.88 1.96 2.04 2.12 2.20 2.28 2.36 2.44 Length in y direction / m 2.34 2.38 2.42 2.46 2.50 2.54 2.58 2.62

[0125] S3: Design an adaptive torque controller based on the structure of the networked communication topology designed in step S1 and the robot model built in step S2, and determine the distributed formation control protocol;

[0126] If in a control mode, the system state has Then the system is said to form a formation F, and the control method of forming the formation is as follows:

[0127] First, for robot i, (i = 1, 2, ..., 8) a reference velocity vector is introduced:

[0128]

[0129] Then, determine the error vector (auxiliary velocity vector)

[0130] s i =q i -r i , (4)

[0131] Finally, the control protocol obeyed by the i-th robot is given

[0132]

[0133] Among them, K i is a symmetric positive definite matrix, is a constant parameter vector θ i The estimated value of and satisfies the adaptive law:

[0134]

[0135] Here Δ i is a symmetric positive definite coupling matrix, is the dynamic equation with respect to the constant parameter vector θ i The regression matrix.

[0136] S4: adding and setting a virtual leader to the multi-robot system on the basis of ensuring the formation of the team in step S3;

[0137] First, update the communication topology according to the provisions of step S3 to

[0138] Second, considering that the virtual guide is used to provide reference routes and is not used to complete complex tasks, a first-order robot system is built for it;

[0139] The leader robot has a first-order linear system: Let it be node O, and The corresponding adjacency matrix is ​​expanded to in Is

[0140] Column vector composed of .

[0141] S5: Based on the requirements of the target task, set the system equation of the virtual guide. The specific process is as follows:

[0142] The objectives of the formation tracking control are:

[0143]

[0144] The first row of F represents the horizontal coordinates of multiple robots in the expected formation, and the second row represents the vertical coordinates of multiple robots in the expected formation;

[0145] Based on the trajectory required by the target task, the trajectory equation of the virtual guide is set as: And the system of the virtual leader satisfies the first-order linear equation:

[0146] S6: Under the premise of maintaining the same adaptive control method as in step S3, a distributed formation tracking control protocol is determined, and the specific process is as follows;

[0147] First, for robot i, (i = 1, 2, ..., 8), a reference velocity vector is introduced:

[0148]

[0149] Then, determine the error vector (auxiliary velocity vector) ξ i =q i -ζ i ,

[0150] Finally, the control protocol obeyed by the i-th robot is given

[0151]

[0152] in, is a symmetric positive definite matrix, is a constant parameter vector θ i The estimated value of and satisfies the adaptive law:

[0153]

[0154] here is a symmetric positive definite coupling matrix, is the dynamic equation with respect to the constant parameter vector θ i The regression matrix of

[0155] S7: According to the trajectory equation of the virtual leader described in step S5, the tracking control protocol of the distributed formation is transmitted to the execution module to realize the tracking control of the formation, so that multiple robots can coordinate the tracking task under the restriction of the spatial position of the formation.

[0156] Figure 3 The following are the changes in the horizontal and vertical coordinate positions of the eight robots with a guide. Figure 3 It can be seen that the eight robots first completed the formation control, and the two groups of robots with bilateral communication relations obviously maintained the formation in two directions and performed trajectory tracking after 15s.

[0157] Figure 4 The speed change trends of the eight robots in the x-axis and y-axis directions are given. Figure 4 It can be seen that after the system reached stability for the first time (17s-22s), it became unstable again (22s-25s), and then returned to the stable point again. This is because the rigid structure of the robot model selected by this group must maintain the stability of the formation and follow the given trajectory in the case of bilateral communication, resulting in the constant coupling coefficient being unable to satisfy the system's adaptive adjustment instantaneously, so internal disturbances occurred.

[0158] Figure 5 This is the relative position diagram of robot 1, robot 2, robot 3, and robot 4. It can be seen from the figure that the relative positions of these four robots remain fixed after 17 seconds, and their relative positions can meet the formation requirements in a relatively neat manner within a similar time.

[0159] pass Figure 6 Random sampling of the formation tracking process and Figure 7 The complete reproduction of the trajectory tracking process under formation control can intuitively show that the multi-robot system of the present invention can better complete the formation task and formation tracking task under the above control method.

[0160] Embodiment 4:

[0161] 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.

[0162] 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.

[0163] Embodiment 5:

[0164] 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.

[0165] 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.

[0166] 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 via 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).

[0167] 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. It should be understood by those skilled in the art 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 bidirectional formation tracking control method for a networked multi-robot system, comprising the following steps: S1: Network each robot and design a networked communication topology with a cooperative competition structure; S2: Analyze the kinematics and dynamics of multiple groups of single robots and establish a high-order nonlinear Lagrangian robot model; in 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 a broadly powerful i ∈R n is the input moment vector; When considering the case of a kinetic equation with uncertain parameters, the Lagrangian kinetic expression should be used, which has the characteristic of linear regression with respect to a certain constant parameter: in is the parameter uncertainty equation with respect to the constant parameter θ i The linear regression matrix, x, y is the space R n Any differentiable vector in ; S3: Based on the structure of the networked communication topology designed in step S1 and the robot model built in step S2, an adaptive torque controller is designed to determine the formation control protocol of the distributed formation; S4: adding and setting a virtual leader to the robot system on the basis of ensuring the formation in step S3; S5: Set the system equation of the virtual guide based on the requirements of the target task; S6: Under the premise of maintaining the same adaptive control method as in step S3, a tracking control protocol of the distributed formation is determined based on the system equation of the virtual leader; S7: According to the trajectory equation of the virtual leader described in step S5, the tracking control protocol of the distributed formation is transmitted to the execution module to realize the formation tracking control, so that multiple robots can perform tracking task collaboration under the constraints of the formation space position.

2. The control method according to claim 1, characterized in that: In step S1, each robot is networked and the specific process of designing a network communication topology with a cooperative competition structure is as follows: Determine the information collection authority and the information access authority of the communication part according to the edge set, set the information use to be one-way according to the directed graph, and adjust the sign of the system feedback as input in the control part according to the positive and negative signs of the edge weights. The above process is that the closed-loop system divides the feedback into two types as input in a distributed form for adaptive adjustment to achieve collaborative formation; Design The information topology diagram corresponding to the networked system composed of N robots, yes The node set of yes The edge set of is the index set; accordingly, let The adjacency matrix of Let its Laplace matrix be In order to realize the control of bidirectional tracking of multi-robot system, it is assumed that There are edges with positive and negative weight values, and they meet the following requirements: is a directed graph and there exists a directed spanning tree; is structurally balanced; accordingly, there is a normative matrix Φ = diag{φ1, φ2, ..., φ N } makes all elements of ΦAΦ non-negative, where 3. The control method according to claim 2, characterized in that: The specific process of determining the formation control protocol of the distributed formation in step S3 is: If in a control mode, the system state has Then the system is said to form a formation F; First, for robot i, (i = 1, 2, ..., N) a reference velocity vector is introduced: in, are the generalized coordinates and generalized velocity of robot i, a ij For edge e ij The weight of , sgn(·) is the sign function; Then, determine the error vector (auxiliary velocity vector) s i =q i -r i , Finally, the control protocol that the i-th robot obeys regarding the formation of the formation is given Among them, K i is a symmetric positive definite matrix, is a constant parameter vector θ i The estimated value of and satisfies the adaptive law: Here Δ i is a symmetric positive definite coupling matrix, is the dynamic equation with respect to the constant parameter vector θ i The regression matrix.

4. The control method according to claim 3, characterized in that: The specific contents of adding and setting a virtual guide to the robot system in step S4 are: Update the communication topology according to the conditions in step S1 to Considering that the virtual guide is used to provide reference routes and is not used to complete complex tasks, a first-order robot system is built for it; The first-order linear system of the leader robot is: Let it be node o, and The corresponding adjacency matrix is ​​expanded to in Is Column vector composed of .

5. The control method according to claim 4, characterized in that: The system equation of the virtual guide in step S5 is:

6. The control method according to claim 5, characterized in that: The process of determining the tracking control protocol of the distributed formation in step S6 includes: The reference velocity vector of robot i, (i=1, 2, ..., N) is: Among them, a ij For edge e ij The weight, l i is the connection relationship and weight between the leader and robot i in the communication topology graph, are the generalized coordinates and generalized velocity of robot i, For the index set.

7. A universal micro control unit, characterized in that: An adaptive torque control protocol or program is provided which can execute the control method described in any one of claims 1 to 6.

8. A networked multi-robot system bidirectional formation tracking control system, characterized in that: It comprises a plurality of mobile robots, each of which comprises a power supply module, a communication module, a data collection module, a control module and an execution module; the control module is provided with a micro-control unit as claimed in claim 7; the data collection module transmits the collected information to the control module; the control module converts the control protocol into a control language readable by the execution module and outputs it to the execution module, and the execution module controls the autonomous movement and coordinated cooperation of the plurality of mobile robots according to the instructions of the control information, and executes the control method as claimed in any one of claims 1 to 6.

9. 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 any step in the method for realizing bidirectional formation tracking control of a networked multi-robot system as described in any one of claims 1-6.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which, when executed by a computer processor, implements any step in the method for bidirectional formation tracking control of a networked multi-robot system as described in any one of claims 1-6.

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