An Incremental Control Method, Device and Equipment for Robot Cluster System

Abstract

The present invention discloses a control method, device and equipment for an incremental robot cluster system, which relates to the field of the present invention and is used to solve the problem in the prior art that the number of robots cannot be flexibly increased. It includes: establishing a second-order communication topology of an initial robot cluster system; obtaining a robot increment instruction including an incremental robot set; grading the incremental robot set based on the second-order communication topology and adding it to the second-order communication topology to form an incremental robot cluster system; calculating the control quantity of the incremental robot cluster system, and updating the robot state according to the control quantity to control the incremental robots to move to the target position. When the number of robots increases, the second-order communication topology is used to perform grading operations on the robot cluster system, which improves the robustness and flexibility of the system on the basis of reducing the storage and computing pressure caused by the incremental subsystem on the cluster system, and enhances the efficiency and success rate of the robot cluster in completing tasks.

Description

Technical Field

[0001] The present invention relates to the technical field of swarm control, and in particular, to a control method, device and equipment for an incremental robot swarm system. Background Art

[0002] With the continuous development of engineering technology and the rapid progress of robot technology, robots have been widely used in fields such as industry, healthcare, and military. For complex application scenarios, multi-robot cooperation has gradually become an effective way to improve task execution efficiency.

[0003] Traditional central control methods plan the behaviors of all robots uniformly according to the system state, which solves the problem of multi-robot cooperation to a certain extent. However, when applied to a large-scale system, it faces challenges such as large computational complexity and difficulty in constructing communication topologies. Swarm systems aim to make the local interactions of simple robots emerge complex swarm behaviors through a large number of self-organizing cooperative controls, and at the same time enable the system to possess the swarm intelligence to complete complex tasks. The related control research of swarm systems has successfully solved problems such as insufficient system fault tolerance, large computational overhead, and limited system dynamic adjustment ability caused by central control methods, and has high robustness, scalability, and flexibility, providing an efficient solution for the control of large-scale robot swarm systems and realizing the evolution from individual intelligence to swarm intelligence.

[0004] With the increase in the number of tasks and environmental complexity, in addition to certain requirements for the coverage of the robot swarm system, higher requirements are also put forward for the flexibility of the system.

[0005] Therefore, there is an urgent need to provide a more reliable control method for an incremental robot swarm system. Summary of the Invention

[0006] The purpose of the present invention is to provide a control method, device and equipment for an incremental robot swarm system, which is used to solve the problem that the number of robots cannot be increased flexibly in the prior art.

[0007] To achieve the above purpose, the present invention provides the following technical solutions:

[0008] In a first aspect, the present invention provides a control method for an incremental robot swarm system, the method comprising:

[0009] Establish a second-order communication topology of an initial robot swarm system;

[0010] Obtain a robot increment instruction; the robot increment instruction at least includes an increment robot set;

[0011] Classify the increment robot set based on the second-order communication topology to obtain a classified increment robot set;

[0012] Add the set of incremental robots after grading to the second-order communication topology and combine it with the initial robot cluster system to form an incremental robot cluster system;

[0013] Determine the target position corresponding to the incremental robot cluster system;

[0014] Calculate the control quantity of the incremental robot cluster system, update the robot state according to the calculated control quantity, and control the robots in the incremental robot cluster system to move to the target position.

[0015] In a second aspect, the present invention provides a control device for an incremental robot cluster system, and the device includes:

[0016] An initial second-order communication topology establishment module for establishing a second-order communication topology of an initial robot cluster system;

[0017] A robot incremental instruction acquisition module for acquiring robot incremental instructions; at least an incremental robot set is included in the robot incremental instructions;

[0018] A grading module for grading the incremental robot set based on the second-order communication topology to obtain a graded incremental robot set;

[0019] A grading fusion module for adding the graded incremental robot set to the second-order communication topology and combining it with the initial robot cluster system to form an incremental robot cluster system;

[0020] A target position determination module for determining the target position corresponding to the incremental robot cluster system;

[0021] An incremental robot cluster system state control module for calculating the control quantity of the incremental robot cluster system, updating the robot state according to the calculated control quantity, and controlling the robots in the incremental robot cluster system to move to the target position.

[0022] In a third aspect, the present invention provides a control device for an incremental robot cluster system, characterized in that the device includes:

[0023] A communication unit / communication interface for establishing a second-order communication topology of an initial robot cluster system;

[0024] Acquire robot incremental instructions; at least an incremental robot set is included in the robot incremental instructions;

[0025] A processing unit / processor for grading the incremental robot set based on the second-order communication topology to obtain a graded incremental robot set;

[0026] Add the set of classified incremental robots to the second-order communication topology, and combine it with the initial robot cluster system to form an incremental robot cluster system;

[0027] Determine the target position corresponding to the incremental robot cluster system;

[0028] Calculate the control quantity of the incremental robot cluster system, and update the robot state according to the calculated control quantity, and control the robots in the incremental robot cluster system to move to the target position.

[0029] In a fourth aspect, the present invention provides a computer storage medium, in which instructions are stored, and when the instructions are run, the above-mentioned control method of the incremental robot cluster system is implemented.

[0030] Compared with the prior art, the present invention provides a control method, device and equipment for an incremental robot cluster system. The solution includes: establishing a second-order communication topology of an initial robot cluster system; obtaining a robot incremental instruction including a set of incremental robots; grading the set of incremental robots based on the second-order communication topology, adding the graded set of incremental robots to the second-order communication topology, and combining it with the initial robot cluster system to form an incremental robot cluster system; determining the target position corresponding to the incremental robot cluster system; calculating the control quantity of the incremental robot cluster system, and updating the robot state according to the calculated control quantity, and controlling the robots in the incremental robot cluster system to move to the target position. In this solution, the number of robots can be increased at any time, and when the number of robots increases, the second-order communication topology is used to grade the robot cluster system. On the basis of reducing the storage and computing pressure caused by the incremental subsystem on the cluster system, the robustness and flexibility of the system are improved, and the efficiency and success rate of the robot cluster to complete tasks are improved. Description of the Drawings

[0031] The drawings described herein are used to provide a further understanding of the present invention, and constitute a part of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention, and do not constitute an improper limitation of the present invention. In the drawings:

[0032] Figure 1 It is a schematic flowchart of the control method of the incremental robot cluster system provided by the present invention;

[0033] Figure 2 It is a schematic diagram of the second-order communication topology of the incremental robot cluster system;

[0034] Figure 3 It is a diagram of the position evolution of the robot cluster system;

[0035] Figure 4Schematic diagram of the principle of the control method for the incremental robot cluster system provided in the embodiments of this specification;

[0036] Figure 5 Schematic diagram of the control device for the incremental robot cluster system;

[0037] Figure 6 Schematic diagram of the structure of the control device for the incremental robot cluster system provided by the present invention. Specific embodiments

[0038] In order to facilitate a clear description of the technical solutions in the embodiments of the present invention, in the embodiments of the present invention, terms such as "first" and "second" are used to distinguish the same items or similar items with basically the same functions and roles. For example, the first threshold and the second threshold are only used to distinguish different thresholds, and do not limit their sequence. Those skilled in the art can understand that terms such as "first" and "second" do not limit the quantity and execution order, and "first" and "second" do not necessarily mean different.

[0039] It should be noted that in the present invention, words such as "exemplary" or "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as "exemplary" or "for example" in the present invention should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific manner.

[0040] In the present invention, "at least one" means one or more, and "a plurality" means two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone, where A and B can be singular or plural. The character " / " generally represents an "or" relationship between the associated objects before and after. "At least one (item)" or its similar expression below refers to any combination of these items, including any combination of single item (item) or plural items (items). For example, at least one (item) of a, b or c can represent: a, b, c, the combination of a and b, the combination of a and c, the combination of b and c, or the combination of a, b and c, where a, b and c can be single or multiple.

[0041] In the prior art, in the current research on robot cluster systems, limitations such as a small number of robots and a fixed number of robots restrict the application of robot cluster systems in complex and changeable tasks. In actual application scenarios, when the number of robots in the existing robot formation is insufficient to complete the work, more robots need to be added to the formation to ensure efficient and timely completion of the task.

[0042] According to the traditional central control method, the central control node recalls the existing robot formation, expands the scale, re-plans, and then starts to execute the task again. It can be seen that this method is very resource-consuming and time-consuming for the system. At the same time, the currently proposed incremental robot cluster control method focuses on systems with a small number of robots. However, as the number of robots increases, the system faces problems such as large amounts of transmitted data, high computational complexity, and high costs for storing data, which is not conducive to the rapid control of the cluster system. Therefore, only by proposing an efficient incremental formation control method for the robot cluster system can the storage and computational pressure on the cluster system caused by the incremental subsystem be reduced, the robustness and flexibility of the system be improved, and the efficiency and success rate of the robot cluster in completing tasks be enhanced.

[0043] In response to this, the present invention provides a control solution for an incremental robot cluster system.

[0044] Next, the solution provided in the embodiments of this specification will be described in conjunction with the accompanying drawings:

[0045] Figure 1 It is a schematic flowchart of the incremental robot cluster system control method provided by the present invention. As Figure 1 shown, this process may include the following steps:

[0046] Step 110: Establish a second-order communication topology of the initial robot cluster system.

[0047] The second-order communication topology of the initial robot cluster system may include a first-order communication topology and a second-order communication topology. Among them, in the second-order communication topology, there are also multiple robot subgroup systems. The number and form of robots in any topology can be adjusted according to the actual situation. The initial robot cluster system includes the robots in the first-order communication topology and their corresponding robot subgroup in the second-order communication topology, including the global leader. The initial robot cluster system may represent the system composed of the currently available robot clusters.

[0048] Step 120: Obtain a robot increment instruction; the robot increment instruction includes at least an incremental robot set.

[0049] In the actual application process, when it is necessary to increase the number of robots, a robot increment instruction can be obtained. The robot increment instruction can at least include the set of robots to be added, that is, the incremental robot set. Of course, it can also include information such as the number of robots to be added and the robot identifiers.

[0050] Step 130: Classify the incremental robot set based on the second-order communication topology to obtain a classified incremental robot set.

[0051] Step 140: Add the sorted incremental robot set to the second-order communication topology and combine it with the initial robot cluster system to form an incremental robot cluster system.

[0052] In Steps 130 and 140, when increasing the number of robots, it is necessary to integrate the incremental robots into the original initial robot cluster system. The initial robot cluster system corresponds to the second-order communication topology. Therefore, it is necessary to sort the incremental robot set. Sorting can also be understood as grading. After grading, the corresponding data is added to the corresponding communication topology.

[0053] Step 150: Determine the target position corresponding to the incremental robot cluster system.

[0054] In actual application scenarios, robots can be used in various fields to perform tasks. Robots can replace or assist humans in completing various tasks. For example, they are widely used in the manufacturing field and also in other fields such as resource exploration and development, disaster relief and rescue, medical services, home entertainment, military, and aerospace. Robots are important production and service equipment in the industrial and non-industrial sectors and are also indispensable automation equipment in the field of advanced manufacturing technology.

[0055] The initial robot cluster system can be a system composed of robot clusters that have been put into use. When the number of robots increases, it is necessary to determine the target positions that the added robots need to reach. The incremental robots need to start performing tasks at the target positions.

[0056] Step 160: Calculate the control quantity of the incremental robot cluster system, update the robot state according to the calculated control quantity, and control the robots in the incremental robot cluster system to move to the target position.

[0057] The control quantity can represent the control input of the incremental robot cluster system. Based on the control input, the robot state is updated. The state of the robot can include the running state of the robot, such as information on changing actions, moving distances, changing orientations, etc. Based on the state update, the incremental robots can be controlled to move to the target position.

[0058] Figure 1In the method, a second-order communication topology of the initial robot cluster system is established; a robot increment instruction including an increment robot set is obtained; the increment robot set is classified based on the second-order communication topology, and the classified increment robot set is added to the second-order communication topology and combined with the initial robot cluster system to form an increment robot cluster system; a target position corresponding to the increment robot cluster system is determined; a control amount of the increment robot cluster system is calculated, and the state of the robot is updated according to the calculated control amount, and the robot in the increment robot cluster system is controlled to move to the target position. In this solution, the number of robots can be increased at any time. When the number of robots increases, the second-order communication topology is used to classify the robot cluster system. On the basis of reducing the storage and calculation pressure caused by the increment subsystem on the cluster system, the robustness and flexibility of the system are improved, and the efficiency and success rate of the robot cluster to complete tasks are enhanced.

[0059] Based on Figure 1 the method, some specific implementation manners of the method are further provided in the embodiments of this specification, and the following is an illustration.

[0060] Optionally, classifying the increment robot set based on the second-order communication topology to obtain a classified increment robot set may specifically include:

[0061] Based on the second-order communication topology, the increment robot set is split, where the leader robot is added to the first-order communication topology of the initial robot cluster system; the follower robots maintain the original formation and are added to the second-order communication topology of the initial robot cluster system in the form of a robot subgroup to obtain a classified increment robot set.

[0062] Specifically, the follower robots maintain the original formation and are added to the second-order communication topology of the initial robot cluster system in the form of a robot subgroup, and according to formula (1):

[0063]

[0064] the state of the increment robot cluster system is updated, where X is the state variable of the increment robot cluster system, A is the adjacency matrix, 1 n = [1,..., 1] is an n-dimensional vector, X M represents the robot state in the M case, B stores the identity information, and 1 M = [1,..., 1] is an M-dimensional vector.

[0065] Furthermore, the incremental robot system is hierarchically operated by using a second-order communication topology. The leader robots in the incremental robot set are added to the first-order communication topology of the initial robot cluster system, and the remaining follower robots are added to the second-order communication topology of the initial robot cluster system. The hierarchical incremental robot set is added to the initial robot cluster system to form an incremental robot cluster system; the state vector of the constructed incremental robot cluster system is updated and extended; a state update law is constructed to obtain the state variable matrix of the incremental robot cluster system.

[0066] 1) Based on the second-order communication topology, the incremental robot set is split, specifically including:

[0067] Using the second-order communication topology:

[0068]

[0069] The initial robot cluster system is hierarchically operated, where represents the first-order communication topology, represents the second-order communication topology;

[0070] The first-order communication topology of the initial robot cluster system based on the second-order communication topology is expressed as:

[0071]

[0072] where V (1) represents the node set in the first-order communication topology, E (1) represents the edge set in the first-order communication topology, and A (1) represents the adjacency matrix of the first-stage communication topology;

[0073] The kth robot subgroup in the second-order communication topology is expressed as:

[0074]

[0075] where V k (2) represents the node set of the kth robot subgroup in the second-order communication topology, E k (2) represents the edge set of the kth robot subgroup in the second-order communication topology, and A k (1) represents the adjacency matrix of the kth robot subgroup in the second-order communication topology;

[0076] After the hierarchical operation of the incremental robot set, the first-order communication topology of the incremental robot set is:

[0077]

[0078] Among them, it is assumed that the number of robots in the first-order communication topology is M (1) , and there are M (2) robot subgroups in the second-order communication topology. Among them, the number of robots in the k + -th subgroup is V +(1) denotes the node set in the first-order communication topology of the incremental robot set, and E +(1) denotes the edge set of the first-order communication topology of the incremental robot, and A +(1) denotes the adjacency matrix of the first-stage communication topology of the incremental robot;

[0079] The k + -th robot subgroup in the second-order communication topology is expressed as:

[0080]

[0081] Among them, V k +(2) denotes the node set of the k-th robot subgroup in the second-order communication topology of the incremental robot set, and E k +(2) denotes the edge set of the k-th robot subgroup in the second-order communication topology of the incremental robot set, and A k +(1) denotes the adjacency matrix of the k-th robot subgroup in the second-order communication topology of the incremental robot set.

[0082] 2) At the current moment, the incremental robot set is added to the initial robot cluster system to form an incremental robot cluster system. The adjacency matrix of the communication topology of this incremental robot cluster system is expressed as:

[0083]

[0084] Among them, denotes the additional edge connection relationship when the incremental system is merged with the original cluster system. For the second-order communication topology of this incremental robot cluster system, each robot subgroup is independent of each other:

[0085]

[0086] The communication topology of the merged incremental cluster system is expressed as:

[0087]

[0088] Update and expand the state vector of the constructed incremental robot cluster system, which can specifically include:

[0089] The merging process can be expressed as: Assume that there are M (1) +M (2)A robot. In the initial robot cluster system, there are N (1) +N (2) robots. Then the state variables of the incremental robot cluster system are as follows:

[0090]

[0091] Among them, X (1) , X (2) represent the state variables of the robots in the first and second-order communication topologies of the initial robot cluster system. X +(1) , X +(2) represent the state variables of the robots in the first and second-order communication topologies of the incremental robot set. X (1) , X (2) represent the state variables of the robots in the first and second-order communication topologies of the incremental robot cluster system. When another incremental robot set is added, the state variables of the incremental robot cluster system are expressed as:

[0092]

[0093] Among them, r represents the number of incremental robot sets in the robot cluster system that have been added at the current moment. represents the state variable of the robots in the first-order communication topology of the incremental robot cluster system after adding r incremental robot sets. represents the state variable of the robots in the second-order communication topology of the incremental robot cluster system after adding r incremental robot sets.

[0094] The calculation method of the state variables of the robots in the incremental robot cluster system is as follows:

[0095]

[0096] Among them, represents the nth-order state variable of the robots in the first-order communication topology of the incremental robot cluster system. represents the nth-order state variable of the robots in the kth robot subgroup in the second-order communication topology of the incremental robot cluster system. respectively represent the number of robots in the first-order communication topology of the incremental robot cluster system, the number of robot subgroups included in the second-order communication topology, and the number of robots in the kth robot subgroup. The calculation method of the state variables can also be expressed as:

[0097]

[0098] Among them, the value of M takes different values according to different situations.

[0099] Situation 1: When calculating the state of the robots in the first-order communication topology of the incremental robot cluster system:

[0100] M = rM (1) + N (1) (14)

[0101] Case 2: When calculating the k-th robot subgroup in the second-order communication topology of the incremental robot cluster system:

[0102]

[0103] Construct a state update law to obtain the state variable matrix of the incremental robot cluster system, which may specifically include:

[0104] According to the constructed state update law, calculate the state variable matrix of the incremental robot cluster system:

[0105]

[0106] Calculate the control quantity of the incremental robot cluster system, and update the robot state according to the calculated control quantity, and control the robots in the incremental robot cluster system to move to the target position, which may specifically include:

[0107] Input the position and velocity state information of each robot, and calculate the position error using formula (17):

[0108]

[0109] where x1 = (x 1，1 , x 2，1 , …, x N，1 ) is the current position information of the follower robots in the communication topology, x 0，1 is the current position information of the leader robot in the communication topology, and f0 is the formation scaling function;

[0110] Calculate the high-order position error through the command filter where ω n is a constant, and ε1 are the command filter and input respectively, is the accumulated value at the previous moment;

[0111] Calculate the virtual controller using formula (18):

[0112]

[0113] where c1 is a constant, and x2 = (x 1，2 , x 2，2 , …, x N，2 ) is the current velocity information of the follower robots in the communication topology;

[0114] The velocity error is calculated using Equation (19):

[0115] ε2 = x2 - α1 (19)

[0116] The high-order velocity error is calculated using Equation (20) through an instruction filter:

[0117]

[0118] The unknown non-linear terms existing in the robot dynamics equation are fitted using an RBF-NN neural network to obtain: θ T h(X),

[0119] where is a Gaussian fit, and the update rate of the parameter matrix θ is:

[0120]

[0121] The control quantity is calculated. Among them, the control quantity of the leader robot is an external input, and the control quantity of the follower robot is:

[0122] u = -(c2ε2 + θ T h(X) + ε1) (22)

[0123] For the leader robot in the first-order communication topology, its external input can be set to [cost, sint]. For the leader robot in the second-order communication topology, i.e., the follower robot in the first-order communication topology, its input is the control input u of the follower robot calculated in the first order followers .

[0124] Update the position and velocity state information of the robot according to the control quantity:

[0125] x = x + Δx·dt (23)

[0126] where

[0127] Optionally, a second-order communication topology of the robot cluster system is established, which may specifically include:

[0128] Set the number of robots in the first-order communication topology of the initial robot cluster system;

[0129] Based on the number of robots in the first-order communication topology, establish the directed graph of the first-order communication topology and the directed graph of the second-order communication topology.

[0130] Before updating the robot state according to the calculated control quantity, it may further include:

[0131] Obtain the initial state information of the robots in the initial robot cluster system model; the initial state information includes: the current position coordinates, speed of the robots in the global coordinates under the first-order communication topology, the position coordinates and speed of the robots in the corresponding robot subsystem in the second-order communication topology.

[0132] Specifically, set the number of robots in the first-order system of the initial robot cluster system to be N (1) , where the N (1) th robot is the leader robot, and the remaining robots are follower robots. Set that the second-order communication topology of the initial robot cluster system contains N (2) robot subgroups, and each robot subgroup contains robots, where k = 1,..., N (2) . For the kth robot subgroup, its leader robot is a follower robot in the first-order system;

[0133] Establish a directed graph of the first-order communication topology Directed graph of the second-order subgroup system communication topology For each order of communication topology, their adjacency matrices are respectively Store the edge connection information, matrix Store the degree information, matrix Store the identity information, and the Laplacian matrix obtained is:

[0134] The initial state information may include: the current position coordinates (x i , y i ) of robot i in the global coordinates under the first-order communication topology, speed v i , the position coordinates (x k，i , y k，i ) of robot i in the kth robot subsystem in the second-order communication topology, and speed v k，i .

[0135] It should be noted that when the incremental robot cluster system does not exist, the initial robot cluster system remains unchanged.

[0136] When the number of robots increases, the second-order communication topology corresponding to the incremental robot cluster system can be described in combination with Figure 2 and Figure 3 as follows:

[0137] Figure 2 is the schematic diagram of the second-order communication topology of the incremental robot cluster system. Figure 3 is the position evolution diagram of the robot cluster system. As Figure 2-3 shown, the leader robot in the incremental robot set is robot No. 7, and the follower robot 72 -7 5 The second-order subgroup that maintains the formation to form the incremental robot set joins the initial robot cluster system to form an incremental robot cluster system. By implementing control based on the incremental robot cluster system in the case of input saturation, that is, during the operation of the initial robot cluster system, receiving the addition of the incremental robot set to form an incremental robot subgroup system, and maintaining the system stability during the simulation to demonstrate the effectiveness of the controller. The simulation duration can be set to 30s, and the incremental system joins the initial robot cluster system at 15s to form an incremental robot cluster system to achieve tracking control.

[0138] For the traditional communication topology form with the same number of robots, in order to construct this communication topology, the size of the adjacency matrix A is which causes great difficulties in storage, calculation, and construction. At this time, if the second-order communication topology is used to divide the robots into k subgroups, the computational complexity will be reduced from o(N 2N ) to o(N 2N / K ); when designing the controller using the traditional method, the calculation of the controller parameters is related to each robot.

[0139] In the solution of this specification, in specific implementation, its implementation principle can be combined with Figure 4 for description. Figure 4 It is a schematic diagram of the principle of the control method for the incremental robot cluster system provided in the embodiment of this specification. As Figure 4 shown, the incremental system can be a system composed of an incremental robot set. It should be noted that the "system" in this solution can refer to the virtual system formed by the cluster. Figure 4 In, the incremental system is graded. Among the leader robots (dots) and the follower robots, the leader robots join the first-order communication topology of the initial robot cluster system; the follower robots maintain the original formation and join the second-order communication topology of the initial robot cluster system in the form of robot subgroups; the original cluster system can be the initial robot cluster system in the above embodiment. The original cluster system includes a first-order communication topology and a second-order communication topology. The first-order communication topology includes a leader robot set, and the second-order communication topology includes a follower robot set. The incremental system is fused with the original cluster system to obtain an incremental cluster system.

[0140] The solution in this specification addresses the deficiencies in traditional robot cluster system control methods, such as the small number of robots and the immutability of the number of robots, and realizes the flexible change of the number of robots. For the storage and computing pressure brought about by the increase in the number of robots, a second-order communication topology is used to perform hierarchical operations on the robot cluster system. The incremental formation control method of the efficient cluster robot system improves the robustness and flexibility of the system while reducing the storage and computing pressure caused by the incremental subsystem on the cluster system, and enhances the efficiency and success rate of the robot cluster in completing tasks.

[0141] Based on the same idea, the present invention also provides a control device for an incremental robot cluster system. Figure 5 As shown in the schematic diagram of the control device for the incremental robot cluster system, Figure 5 the device may include:

[0142] An initial second-order communication topology establishment module 510 for establishing the second-order communication topology of the initial robot cluster system.

[0143] A robot increment instruction acquisition module 520 for acquiring robot increment instructions; at least an increment robot set is included in the robot increment instructions.

[0144] A hierarchical module 530 for hierarchically classifying the increment robot set based on the second-order communication topology to obtain a hierarchically classified increment robot set.

[0145] A hierarchical fusion module 540 for adding the hierarchically classified increment robot set into the second-order communication topology and combining it with the initial robot cluster system to form an incremental robot cluster system.

[0146] A target position determination module 550 for determining the target position corresponding to the incremental robot cluster system.

[0147] An incremental robot cluster system state control module 560 for calculating the control quantity of the incremental robot cluster system and updating the robot state according to the calculated control quantity, and controlling the robots in the incremental robot cluster system to move to the target position.

[0148] Based on Figure 5 the device, some specific implementation units may also be included:

[0149] Optionally, the hierarchical module 530 may specifically include:

[0150] Split unit, based on the second-order communication topology, split the set of incremental robots, where the leader robot joins the first-order communication topology of the initial robot cluster system; the follower robots maintain their original formation and join the second-order communication topology of the initial robot cluster system in the form of robot subgroups, obtaining the graded set of incremental robots.

[0151] Optionally, the initial second-order communication topology establishment module 510 can be specifically used for:

[0152] Set the number of robots in the first-order communication topology of the initial robot cluster system;

[0153] Based on the number of robots in the first-order communication topology, establish the directed graph of the first-order communication topology and the directed graph of the second-order communication topology.

[0154] Optionally, the device may further include:

[0155] Initial state information acquisition unit, used to acquire the initial state information of the robots in the initial robot cluster system model; the initial state information includes: the current position coordinates, speed of the robots in the global coordinates under the first-order communication topology, and the position coordinates and speed of the robots in the corresponding robot subsystem in the second-order communication topology.

[0156] Optionally, the device may further include:

[0157] State vector update unit, used to update and expand the state vector of the incremental robot cluster system;

[0158] State variable matrix construction unit, used to construct the state variable matrix of the incremental robot cluster system through the state update law.

[0159] Optionally, the split unit can be specifically used for:

[0160] Utilize the second-order communication topology Perform a grading operation on the initial robot cluster system, where represents the first-order communication topology, represents the second-order communication topology;

[0161] The first-order communication topology of the initial robot cluster system based on the second-order communication topology is expressed as:

[0162]

[0163] where, V (1) represents the node set in the first-order communication topology, E (1) represents the edge set in the first-order communication topology, A (1) represents the adjacency matrix of the first-stage communication topology;

[0164] The k-th robot subgroup in the second-order communication topology is represented as:

[0165]

[0166] where V k (2) represents the node set of the k-th robot subgroup in the second-order communication topology, and E k (2) represents the edge set of the k-th robot subgroup in the second-order communication topology, and A k (1) represents the adjacency matrix of the k-th robot subgroup in the second-order communication topology;

[0167] After the incremental robot set undergoes hierarchical operations, the first-order communication topology of the incremental robot set is:

[0168]

[0169] where it is assumed that the number of robots included in the first-order communication topology is M (1) , and there are M (2) robot subgroups in the second-order communication topology, where the number of robots in the k + -th subgroup is V +(1) represents the node set in the first-order communication topology of the incremental robot set, and E +(1) represents the edge set of the first-order communication topology of the incremental robot, and A +(1) represents the adjacency matrix of the first-stage communication topology of the incremental robot;

[0170] The k + -th robot subgroup in the second-order communication topology is represented as:

[0171]

[0172] where V k +(2) represents the node set of the k-th robot subgroup in the second-order communication topology of the incremental robot set, and E k +(2) represents the edge set of the k-th robot subgroup in the second-order communication topology of the incremental robot set, and A k +(1) represents the adjacency matrix of the k-th robot subgroup in the second-order communication topology of the incremental robot set.

[0173] Based on the same idea, the embodiments of this specification also provide a control device for an incremental robot cluster system. Figure 6 The structural schematic diagram of the control device for the incremental robot cluster system provided by the present invention. It may include:

[0174] A communication unit / communication interface for establishing a second-order communication topology of an initial robot cluster system;

[0175] Obtain robot incremental instructions; at least an incremental robot set is included in the robot incremental instructions;

[0176] A processing unit / processor for grading the incremental robot set based on the second-order communication topology to obtain a graded incremental robot set;

[0177] Add the graded incremental robot set to the second-order communication topology and combine it with the initial robot cluster system to form an incremental robot cluster system;

[0178] Determine the target position corresponding to the incremental robot cluster system;

[0179] Calculate the control quantity of the incremental robot cluster system, update the robot state according to the calculated control quantity, and control the robots in the incremental robot cluster system to move to the target position.

[0180] As Figure 6 shown, the above terminal device may further include a communication line. The communication line may include a path for transmitting information between the above components.

[0181] Optionally, as Figure 6 shown, the terminal device may further include a memory. The memory is used to store computer execution instructions for executing the solution of the present invention and is controlled by the processor to execute. The processor is used to execute the computer execution instructions stored in the memory, thereby implementing the method provided by the embodiments of the present invention.

[0182] As Figure 6As shown in the figure, the memory can be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or it can also be an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM), or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media, or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory can exist independently and be connected to the processor through a communication line. The memory can also be integrated with the processor.

[0183] Optionally, the computer-executable instructions in the embodiments of the present invention can also be referred to as application program code, and the embodiments of the present invention do not make specific limitations thereto.

[0184] In a specific implementation, as an embodiment, as Figure 6 shown, the processor can include one or more CPUs, such as Figure 6 CPU0 and CPU1 in

[0185] In a specific implementation, as an embodiment, as Figure 6 shown, the terminal device can include multiple processors, such as Figure 6 the processors in

[0186] Based on the same idea, the embodiments of this specification also provide a computer storage medium corresponding to the above embodiments. Instructions are stored in the computer storage medium, and when the instructions are run, the above method is implemented.

[0187] The above mainly introduces the solution provided by the embodiments of the present invention from the perspective of the interaction between various modules. It can be understood that, in order to implement the above functions, each module includes the corresponding hardware structure and / or software unit for executing each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of the examples described in the embodiments disclosed herein, the present invention can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described function for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0188] The embodiments of the present invention can perform the division of functional modules according to the above method examples. For example, each functional module can be divided corresponding to each function, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware or in the form of a software functional module. It should be noted that the division of modules in the embodiments of the present invention is illustrative, only a logical functional division, and there may be other division methods in actual implementation.

[0189] The processor in this specification can also have the function of a memory. The memory is used to store the computer execution instructions for executing the solution of the present invention and is controlled by the processor for execution. The processor is used to execute the computer execution instructions stored in the memory, thereby implementing the method provided by the embodiments of the present invention.

[0190] The memory can be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory can exist independently and be connected to the processor through a communication line. The memory can also be integrated with the processor.

[0191] Optionally, the computer-executable instructions in the embodiments of the present invention may also be referred to as application program code, and the embodiments of the present invention do not make specific limitations thereto.

[0192] The methods disclosed in the embodiments of the present invention described above may be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. During implementation, the steps of the above methods may be completed by the integrated logic circuit in the hardware of the processor or by instructions in software form. The above-mentioned processor may be a general-purpose processor, a digital signal processor (DSP), an ASIC, a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiments of the present invention may be directly embodied as being executed and completed by a hardware decoding processor, or executed and completed by a combination of hardware and software modules in the decoding processor. The software module may be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. This storage medium is located in the memory, and the processor reads the information in the memory and combines its hardware to complete the steps of the above method.

[0193] In a possible implementation manner, a computer-readable storage medium is provided, and instructions are stored in the computer-readable storage medium. When the instructions are run, they are used to implement the logical operation control method and / or the logical operation reading method in the above embodiments.

[0194] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present invention are executed in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, a terminal, a user device, or other programmable devices. The computer program or instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer program or instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center in a wired or wireless manner. The computer-readable storage medium can be any available medium that can be accessed by a computer, or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium, such as a floppy disk, a hard disk, or a magnetic tape; it can also be an optical medium, such as a digital video disc (DVD); or it can be a semiconductor medium, such as a solid state drive (SSD).

[0195] Although the present invention has been described in conjunction with various embodiments, however, in the process of implementing the claimed invention, those skilled in the art can understand and implement other variations of the disclosed embodiments by viewing the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude a plurality. A single processor or other unit can implement several functions recited in the claims. Certain measures are recited in mutually different dependent claims, but this does not mean that these measures cannot be combined to produce good results.

[0196] Although the present invention has been described in connection with specific features and their embodiments, it is obvious that various modifications and combinations can be made without departing from the spirit and scope of the present invention. Accordingly, the present specification and the drawings are merely exemplary illustrations of the invention defined by the appended claims, and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of the present invention. Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these changes and modifications.

Claims

1. A control method for an incremental robot cluster system, characterized in that the method Including: Establishing a second-order communication topology of an initial robot cluster system; Obtaining robot incremental instructions; at least an incremental robot set is included in the robot incremental instructions; Hierarchically classifying the incremental robot set based on the second-order communication topology to obtain a hierarchically classified incremental robot set; Adding the hierarchically classified incremental robot set into the second-order communication topology and combining it with the initial robot cluster system to form an incremental robot cluster system; Determining a target position corresponding to the incremental robot cluster system; Calculating a control quantity of the incremental robot cluster system and updating the robot state according to the calculated control quantity, and controlling the robots in the incremental robot cluster system to move to the target position; Hierarchically classifying the incremental robot set based on the second-order communication topology to obtain a hierarchically classified incremental robot set, specifically including: Based on the second-order communication topology, splitting the incremental robot set, wherein the leader robot is added into the first-order communication topology of the initial robot cluster system; the follower robots maintain the original formation and are added into the second-order communication topology of the initial robot cluster system in the form of robot subgroups to obtain a hierarchically classified incremental robot set; Establishing a second-order communication topology of an initial robot cluster system, specifically including: Setting the number of robots in the first-order communication topology of the initial robot cluster system; Based on the number of robots in the first-order communication topology, establishing a directed graph of the first-order communication topology and a directed graph of the second-order communication topology.

2. The method according to claim 1, characterized in that, Before updating the robot state according to the calculated control quantity, it further includes: Obtaining initial state information of robots in the initial robot cluster system model; the initial state information includes: the current position coordinates, speed of the robots in the global coordinates under the first-order communication topology, the position coordinates and speed of the robots in the corresponding robot subsystem in the second-order communication topology.

3. The method according to claim 1, characterized in that, After adding the hierarchically classified incremental robot set into the second-order communication topology and combining it with the initial robot cluster system to form an incremental robot cluster system, it further includes: Updating and expanding the state vector of the incremental robot cluster system; Constructing a state variable matrix of the incremental robot cluster system through a state update law.

4. The method according to claim 1, characterized in that Based on the second-order communication topology, splitting the incremental robot set, specifically including: Using a second-order communication topology Perform a hierarchical operation on the initial robot cluster system, where represents a first-order communication topology represents a second-order communication topology The first-order communication topology of the initial robot cluster system based on the second-order communication topology is expressed as: ； Among them, V (1) represents the node set in the first-order communication topology, and E (1) represents the edge set of the first-order communication topology, and A (1) represents the adjacency matrix of the first-stage communication topology; The th subgroup of robots in the second-order communication topology is denoted as: ； Among them, V k (2) represents the node set of the k-th robot subgroup in the second-order communication topology, and E k (2) represents the edge set of the k-th robot subgroup in the second-order communication topology, and A k (1) represents the adjacency matrix of the k-th robot subgroup in the second-order communication topology; After the hierarchical operation of the incremental robot set, the first-order communication topology of the incremental robot set is: ； Among them, it is assumed that the number of robots in the first-order communication topology is , and the second-order communication topology contains robot subgroups. Among them, the number of robots in the -th subgroup is , V +(1) represents the node set in the first-order communication topology of the incremental robot set, and E +(1) represents the edge set of the first-order communication topology of the incremental robot, and A +(1) represents the adjacency matrix of the first-stage communication topology of the incremental robot; The th subgroup of robots in the second-order communication topology is denoted as: ； Among them, V k +(2) represents the node set of the k-th robot subgroup in the second-order communication topology of the incremental robot set, and E k +(2) represents the edge set of the k-th robot subgroup in the second-order communication topology of the incremental robot set, and A k +(1) represents the adjacency matrix of the k-th robot subgroup in the second-order communication topology of the incremental robot set.

5. The method according to claim 2, wherein Calculating a control quantity of the incremental robot cluster system and updating the robot state according to the calculated control quantity, and controlling the robots in the incremental robot cluster system to move to the target position, specifically including: Obtaining the position information and speed state information of each robot in the incremental robot cluster system; Calculating a position error according to the position information and speed state information; Calculating a high-order position error through an instruction filter according to the position error; Based on the position error and the high-order position error, a control quantity is calculated, and the initial state information is updated based on the control quantity.

6. An incremental robot cluster system control device, characterized in that, The device includes: An initial second-order communication topology establishment module, configured to establish a second-order communication topology of an initial robot cluster system; A robot incremental instruction acquisition module, configured to acquire robot incremental instructions; at least an incremental robot set is included in the robot incremental instructions; A grading module, configured to grade the incremental robot set based on the second-order communication topology to obtain a graded incremental robot set; A grading fusion module, configured to add the graded incremental robot set into the second-order communication topology and combine it with the initial robot cluster system to form an incremental robot cluster system; A target position determination module, configured to determine a target position corresponding to the incremental robot cluster system; An incremental robot cluster system state control module, configured to calculate a control quantity of the incremental robot cluster system, update the robot state according to the calculated control quantity, and control the robots in the incremental robot cluster system to move to the target position; The grading module specifically includes: A splitting unit, based on the second-order communication topology, splits the incremental robot set, wherein the leader robot joins the first-order communication topology of the initial robot cluster system; the follower robots maintain the original formation and join the second-order communication topology of the initial robot cluster system in the form of a robot subgroup to obtain a graded incremental robot set; The initial second-order communication topology establishment module is specifically configured to: Set the number of robots in the first-order communication topology of the initial robot cluster system; Based on the number of robots in the first-order communication topology, establish a directed graph of the first-order communication topology and a directed graph of the second-order communication topology.

7. An incremental robot cluster system control device, characterized in that the device It includes: A communication unit / communication interface, configured to establish a second-order communication topology of an initial robot cluster system; Acquire robot incremental instructions; at least an incremental robot set is included in the robot incremental instructions; A processing unit / processor, configured to grade the incremental robot set based on the second-order communication topology to obtain a graded incremental robot set; Add the graded incremental robot set into the second-order communication topology and combine it with the initial robot cluster system to form an incremental robot cluster system; Determine a target position corresponding to the incremental robot cluster system; Calculate a control quantity of the incremental robot cluster system, update the robot state according to the calculated control quantity, and control the robots in the incremental robot cluster system to move to the target position; Based on the second-order communication topology, grading the incremental robot set to obtain a graded incremental robot set specifically includes: Based on the second-order communication topology, split the incremental robot set, wherein the leader robot joins the first-order communication topology of the initial robot cluster system; the follower robots maintain the original formation and join the second-order communication topology of the initial robot cluster system in the form of a robot subgroup to obtain a graded incremental robot set; Establish a second-order communication topology for the initial robot cluster system, specifically including: Set the number of robots in the first-order communication topology of the initial robot cluster system; Based on the number of robots in the first-order communication topology, establish a directed graph of the first-order communication topology and a directed graph of the second-order communication topology.

8. A computer storage medium, characterized in that, The computer storage medium stores instructions, which, when run, implement the incremental robot cluster system control method according to any one of claims 1 to 5.

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