A Packet Swarm Control Method Based on Multi-hop Information Transmission

Abstract

The present invention provides a grouped flocking control method based on multi-hop information transmission, including: constructing a cluster V including a plurality of agents i; dividing the cluster V into M sub-clusters V1,..., V M , all agents belonging to the same sub-cluster are expected to achieve flocking behavior, that is, to reach a consistent speed and maintain a relative distance of r from each other d , enabling agent i to interact with all agents within the communication radius r; agent i calculates the control rate u i and implements it, so as to maintain flocking behavior with the agents of the same sub-cluster within the communication range, perform collision avoidance behavior with all agents within the radius d, estimate the center and average speed of the sub-cluster and judge whether it needs to be tracked, until the aggregation of the same sub-cluster is completed, thereby completing the grouped flocking control.

Description

Technical Field

[0001] The present invention relates to the technical field of swarming control of a multi-agent system cluster, and in particular to a group swarming control method based on multi-hop information transmission. Background Art

[0002] The study of swarming behavior comes from animal groups in nature, such as schools of fish, flocks of birds, and swarms of bees, which often show obvious group movement in a certain structure and order. Each individual in a swarming group has limited capabilities in terms of movement, perception, and calculation, but through a large number of simple interactions between group members, a large-scale group can be formed and exhibit a variety of coordinated group behaviors, such as avoiding collisions with each other, keeping a certain distance from neighboring individuals, and all individuals maintaining a consistent movement speed. In practical applications, such as in multi-agent systems such as unmanned system clusters and social networks, swarming control methods are designed based on the limited interaction range and simple interaction rules between agents to achieve coordinated movement of large-scale clusters, which has important research significance and application value.

[0003] Considering that it is difficult for a single cluster to handle multiple tasks at the same time and its ability to handle complex tasks and environments is weak, dividing a large cluster into multiple subclusters with different goals can effectively solve the above problems. Therefore, for an intelligent system composed of multiple subclusters, designing a swarming control algorithm to prompt each subcluster to achieve swarming behavior has a more general research significance and has gradually become a research hotspot.

[0004] At present, the design of group swarming control is mainly based on the Cucker-Smale model and the Olfati-Saber algorithm. In the Cucker-Smale model, the mutual influence between agents weakens as the distance increases, but this influence does not disappear completely; while the Olfati-Saber algorithm is suitable for the swarming control problem of agents with limited communication range, which is more in line with engineering practice, but the algorithm design is also more complicated. There are two main ideas for group swarming control based on the Olfati-Saber algorithm. One is to assume that all agents in each sub-cluster have connectivity at the initial state, and then ensure that the agents in the same group always maintain communication connection by designing a connectivity maintenance algorithm, thereby realizing group swarming control of each sub-cluster. Obviously, this method has strict requirements on the initial state, so its scope of application is limited. Another method is to assume that all agents in each sub-cluster know the target position and expected speed of the cluster exactly, and realize the swarming control of each sub-cluster based on this global information. However, under the limited communication range and distributed interaction architecture, it is difficult to share this global information in a large cluster. Summary of the invention

[0005] For the group swarming control problem of multi-agent system clusters, the existing solutions have great limitations in applicable scenarios. The present invention designs a group swarming control algorithm based on multi-hop information transmission between agents, which only requires that the agents in the same group have an (indirect) connection path at the initial moment, thus providing a new solution to the group swarming control problem.

[0006] The technical means adopted by the present invention are as follows:

[0007] A packet swarming control method based on multi-hop information transmission, comprising:

[0008] Construct a cluster V containing multiple agents i;

[0009] Divide cluster V into M subclusters V1,...,V M , all agents belonging to the same sub-cluster are expected to achieve swarming behavior, that is, to reach a consistent speed and maintain an r d The relative distance between agent i and all agents within the communication radius r is realized;

[0010] Agent i calculates the control rate u based on the information obtained i And implement it, so as to maintain swarming behavior with the same sub-cluster agents within the communication range, perform collision avoidance behavior with all agents within the radius d, estimate the center and average speed of the sub-cluster and determine whether it needs to be tracked, until the aggregation of the same sub-cluster is completed, thereby completing group swarming control.

[0011] Furthermore, the construction of a cluster V comprising a plurality of agents i includes:

[0012] Consider a cluster V containing n agents, and the dynamics equation of each agent i∈V is as follows:

[0013]

[0014] Where: x i ,v i , They represent the position, speed and control input of agent i respectively. The maximum communication distance of each agent is r>0. The agent only communicates and transmits information with neighboring agents within its communication range. The transmitted information includes its own position and speed as well as the positions and speeds of other agents received. Therefore, multi-hop information transmission can be carried out between agents, but the information of other agents transmitted will have transmission delay.

[0015] Furthermore, the agent i calculates the control rate u according to the acquired information.i ,include:

[0016] Each agent i∈V k ,k=1,2,... The control input consists of three parts:

[0017]

[0018] in, represents the swarming control item, which is used to realize the swarming behavior of the same group of agents within the communication range. Represents the collision avoidance term, which is used to achieve mutual collision avoidance between any two agents. Represents the cohesive item within the same group, which is used to achieve aggregation between agents in the same group.

[0019] Furthermore, the swarming control item is defined as:

[0020]

[0021] in, is the set of agents that are within the communication range of agent i and belong to the same subcluster as it; Where ε>0 is a sufficiently small constant; represents the gradient of the function ψ(·), where ψ(·) is a non-negative potential function that produces finite attractive and repulsive forces only at the desired swarming distance r d The minimum value is zero.

[0022] Furthermore, the collision avoidance item is defined as:

[0023]

[0024] in, is the set of all agents within the collision avoidance range d of agent i.

[0025] Furthermore, the cohesive items in the same group is defined as:

[0026]

[0027] in, and is a positive constant, and Respectively represent the intelligent agent i∈V k The estimation of the center position and speed of the subcluster is calculated as follows:

[0028]

[0029] in, represents the number of agents in the same group that agent i receives information from, m ii′ Represents the same group of agents i′∈V k The information is transmitted to the agent i∈V k The number of intermediate transfers required, τ represents the time delay required for a single information transfer; assuming that there is no delay in the information transmission of the agents within the communication range, while the information of the agents outside the communication range is delayed because it needs to be transferred by other agents, the grouping coefficient With the following definition:

[0030]

[0031] This grouping coefficient is used to determine whether the agent needs to track the estimated center. When the agent reaches the vicinity of the center or encounters an agent that is closer to the center than itself during the process of tracking the center, it will give up tracking the center and set the grouping coefficient Set to 0, otherwise 1; due to the existence of multi-hop information transmission communication delay, each agent has different estimates of the center of its subcluster. This discriminant can avoid the failure of cohesion caused by the same group of agents always tracking different centers.

[0032] Compared with the prior art, the present invention has the following advantages:

[0033] 1. The group swarming control method based on multi-hop information transmission provided by the present invention aims at the multi-cluster group swarming control problem under limited communication range, introduces multi-hop information transmission in information interaction, so that the intelligent agents on the communication link can obtain the information of the same group intelligent agents with delay.

[0034] 2. The group swarming control method based on multi-hop information transmission provided by the present invention enables intelligent agents belonging to the same sub-cluster but without direct communication connection to complete the aggregation behavior by introducing an estimation item for the sub-cluster center.

[0035] 3. The group swarming control method based on multi-hop information transmission provided by the present invention takes into account the deviation of the center estimation of the same group of intelligent agents caused by communication delay, and improves the ability of intelligent agents to track the center and aggregate by introducing a grouping coefficient to determine whether tracking is required.

[0036] 3. The group swarming control method based on multi-hop information transmission provided by the present invention, wherein the intelligent agent and the intelligent agents in the same group within their communication range follow the Olfati-Saber algorithm to implement the swarming behavior of the same sub-cluster and avoid collisions with all intelligent agents within the collision avoidance range; the central position and average speed of the sub-cluster are estimated using the information transmitted by the multi-hop communication connection, and a discriminant item is used to determine whether the estimated central position and average speed need to be tracked.

[0037] Based on the above reasons, the present invention can be widely promoted in fields such as swarming control of multi-agent system clusters. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0039] Figure 1 The figure is a flow chart of the method of the present invention.

[0040] Figure 2 An initial state diagram of 20 agents divided into 3 sub-clusters provided in an embodiment of the present invention.

[0041] Figure 3 This is a cluster status diagram after 70 seconds provided by an embodiment of the present invention.

[0042] Figure 4 This is a cluster status diagram after 200 seconds provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0043] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0044] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and is by no means intended to limit the present invention and its application or use. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0045] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0046] Unless otherwise specifically stated, the relative arrangement of the parts and steps described in these embodiments, the numerical expressions and numerical values ​​do not limit the scope of the present invention. At the same time, it should be clear that, for ease of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship. The technology, methods and equipment known to ordinary technicians in the relevant field may not be discussed in detail, but in appropriate cases, the technology, methods and equipment should be regarded as part of the authorization specification. In all examples shown and discussed here, any specific value should be interpreted as merely exemplary, rather than as a limitation. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar numbers and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further discussed in subsequent drawings.

[0047] In the description of the present invention, it is necessary to understand that the directions or positional relationships indicated by directional words such as "front, back, up, down, left, right", "lateral, vertical, perpendicular, horizontal" and "top, bottom" are usually based on the directions or positional relationships shown in the drawings. They are only for the convenience of describing the present invention and simplifying the description. Unless otherwise specified, these directional words do not indicate or imply that the device or element referred to must have a specific direction or be constructed and operated in a specific direction. Therefore, they cannot be understood as limiting the scope of protection of the present invention: the directional words "inside and outside" refer to the inside and outside relative to the contours of each component itself.

[0048] For ease of description, spatially relative terms such as "above", "above", "on the upper surface of", "above", etc. may be used here to describe the spatial positional relationship between a device or feature and other devices or features as shown in the figure. It should be understood that spatially relative terms are intended to include different orientations of the device in use or operation in addition to the orientation described in the figure. For example, if the device in the accompanying drawings is inverted, the device described as "above other devices or structures" or "above other devices or structures" will be positioned as "below other devices or structures" or "below their position devices or structures". Thus, the exemplary term "above" can include both "above" and "below". The device can also be positioned in other different ways (rotated 90 degrees or in other orientations), and the spatially relative descriptions used here are interpreted accordingly.

[0049] In addition, it should be noted that the use of terms such as "first" and "second" to limit components is only for the convenience of distinguishing the corresponding components. If not otherwise stated, the above terms have no special meaning and therefore cannot be understood as limiting the scope of protection of the present invention.

[0050] like Figure 1As shown, the present invention provides a packet crowding control method based on multi-hop information transmission, comprising:

[0051] S1, build a cluster V containing multiple agents i;

[0052] S2, divide the cluster V into M subclusters V1,...,V M , all agents belonging to the same sub-cluster are expected to achieve swarming behavior, that is, to reach a consistent speed and maintain an r d The relative distance between agents i and all agents within the communication radius r is used to realize information exchange between agents i and all agents within the communication radius r; (At the initial moment, there is an information transmission path between agents in each sub-cluster, and this path allows the existence of agents belonging to other sub-clusters to complete the multi-hop transfer of information.)

[0053] S3, agent i calculates the control rate u based on the information obtained i And implement it, so as to maintain swarming behavior with the same sub-cluster agents within the communication range, perform collision avoidance behavior with all agents within the radius d, estimate the center and average speed of the sub-cluster and determine whether it needs to be tracked, until the aggregation of the same sub-cluster is completed, thereby completing group swarming control.

[0054] In specific implementation, as a preferred embodiment of the present invention, in step S1, a cluster V including multiple agents i is constructed, including:

[0055] Consider a cluster V containing n agents, and the dynamics equation of each agent i∈V is as follows:

[0056]

[0057] Where: x i ,v i , They represent the position, speed and control input of agent i respectively. The maximum communication distance of each agent is r>0. The agent only communicates and transmits information with neighboring agents within its communication range. The transmitted information includes its own position and speed as well as the positions and speeds of other agents received. Therefore, multi-hop information transmission can be carried out between agents, but the information of other agents transmitted will have transmission delay.

[0058] In specific implementation, as a preferred embodiment of the present invention, in step S2, the agent i calculates the control rate u according to the acquired information. i ,include:

[0059] Each agent i∈V k ,k=1,2,... The control input consists of three parts:

[0060]

[0061] in, represents the swarming control item, which is used to realize the swarming behavior of the same group of agents within the communication range. Represents the collision avoidance term, which is used to achieve mutual collision avoidance between any two agents. Represents the cohesive item within the same group, which is used to achieve aggregation between agents in the same group.

[0062] The swarming control is defined as:

[0063]

[0064] in, is the set of agents that are within the communication range of agent i and belong to the same subcluster as it; Where ε>0 is a sufficiently small constant; represents the gradient of the function ψ(), where ψ() is a non-negative potential function that produces finite attractive and repulsive forces only at the desired swarming distance r d The minimum value is zero.

[0065] The collision avoidance item is defined as:

[0066]

[0067] in, is the set of all agents within the collision avoidance range d of agent i.

[0068] The same group of cohesive items is defined as:

[0069]

[0070] in, and is a positive constant, and Respectively represent the intelligent agent i∈V k The estimation of the center position and speed of the subcluster is calculated as follows:

[0071]

[0072] in, represents the number of agents in the same group that agent i receives information from, m ii′ Represents the same group of agents i′∈V k The information is transmitted to the agent i∈V kThe number of intermediate transfers required, τ represents the time delay required for a single information transfer; assuming that there is no delay in the information transmission of the agents within the communication range, while the information of the agents outside the communication range is delayed because it needs to be transferred by other agents, the grouping coefficient With the following definition:

[0073]

[0074] This grouping coefficient is used to determine whether the agent needs to track the estimated center. When the agent reaches the vicinity of the center or encounters an agent that is closer to the center than itself during the process of tracking the center, it will give up tracking the center and set the grouping coefficient Set to 0, otherwise 1; due to the existence of multi-hop information transmission communication delay, each agent has different estimates of the center of its subcluster. This discriminant can avoid the failure of cohesion caused by the same group of agents always tracking different centers.

[0075] Example

[0076] The simulation experiment was carried out on the Windows 10 operating system, and the algorithm running platform was MATLAB 2021B. The specific implementation steps of the group swarming control method based on multi-hop information transmission are as follows:

[0077] Step 1: Initialize the state parameters. Consider n = 20 agents, and the initial positions are as follows: Figure 2 As shown, it is divided into M = 3 sub-clusters: V1 = {1, 4, 5, 6, 7, 8}, V2 = {2, 9, 10, 11, 12, 13}, V3 = {3, 14, 15, 16, 17, 18, 19, 20}, and the expected swarming distance between agents is r d =7, communication perception radius r = 1.2r d , the unit delay is τ=0.03s, and the maximum running time of the simulation is T=200s.

[0078] Step 2: Agents within the communication range exchange information, transmit their own position and speed information, and forward the received position and speed information of other agents and the number of times the information has been forwarded. After each agent obtains the information transmitted by its neighbors, it selects the latest data for storage.

[0079] Step 3: Calculate the control rate u using the above calculation formulas (2)-(7) i Specifically, through formula (3), the intelligent agent completes the swarming behavior with the same group of intelligent agents within the communication range, including separation, aggregation and speed matching, so that the same group of intelligent agents within the communication range reach the desired distance r d; Formula (4) is used to ensure that the distance between any two agents is less than the expected distance r d When the agent moves, it will be subject to a repulsive force to avoid mutual collision. The center and average speed of the subcluster where the agent is located are calculated by formula (6), and the need for tracking is determined by formula (7). Finally, the agent tracks the estimated subcluster center and average speed by formula (5).

[0080] Step 4: Repeat steps 2 to 4 for the agent until the maximum running time T=200s is met, and then terminate the running.

[0081] The state of the agent cluster planned according to the above steps is as follows: Figure 2-Figure 4 As shown, at the initial moment ( Figure 2 ) There is no direct communication connection between some intelligent agents belonging to the same sub-cluster. Through multi-hop information transmission and the designed distributed control strategy, each sub-cluster finally achieves aggregation and maintains the desired distance, thereby realizing group swarming control.

[0082] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for controlling group swarming based on multi-hop information transmission, characterized in that: include: Construct a cluster V containing multiple agents i, including: Consider a cluster V containing n agents, and the dynamics equation of each agent i∈V is as follows: Where: x i ,v i , Represent the position, speed and control input of agent i respectively. The maximum communication distance of each agent is r>

0. The agent only communicates and transmits information with neighboring agents within its communication range. The transmitted information includes its own position and speed as well as the positions and speeds of other agents received. Therefore, multi-hop information transmission can be performed between agents, but the information of other agents transmitted will have transmission delay. Divide cluster V into M subclusters V1,...,V M , all agents belonging to the same sub-cluster are expected to achieve swarming behavior, that is, to reach a consistent speed and maintain an r d The relative distance between agent i and all agents within the communication radius r is realized; Agent i calculates the control rate u based on the information obtained i And implement, so as to maintain swarming behavior with the same sub-cluster agents within the communication range, perform collision avoidance behavior with all agents within the radius d, estimate the center and average speed of the sub-cluster and determine whether it needs to be tracked, until the same sub-cluster is gathered, thus completing the group swarming control; The agent i calculates the control rate u based on the information obtained i ,include: Each agent i∈V k ,k=1,2,... The control input consists of three parts: in, represents the swarming control item, which is used to realize the swarming behavior of the same group of agents within the communication range. Represents the collision avoidance term, which is used to achieve mutual collision avoidance between any two agents. Represents the cohesive item within the same group, which is used to achieve aggregation between agents in the same group.

2. The method for controlling packet swarming based on multi-hop information transmission according to claim 1, characterized in that: The swarming control is defined as: in, is the set of agents that are within the communication range of agent i and belong to the same subcluster as it; Where ε>0 is a sufficiently small constant; represents the gradient of the function ψ(·), where ψ(·) is a non-negative potential function that produces finite attractive and repulsive forces only at the desired swarming distance r d The minimum value is zero.

3. The method for controlling packet swarming based on multi-hop information transmission according to claim 1, characterized in that: The collision avoidance item is defined as: in, is the set of all agents within the collision avoidance range d of agent i.

4. The method for controlling packet swarming based on multi-hop information transmission according to claim 1, characterized in that: The same group of cohesive items is defined as: in, and is a normal number, and Respectively represent the intelligent agent i∈V k The estimation of the center position and speed of the subcluster is calculated as follows: in, represents the number of agents in the same group that agent i receives information from, m ii′ Represents the same group of agents i′∈V k The information is transmitted to the agent i∈V k The number of intermediate transfers required, τ represents the time delay required for a single information transfer; assuming that there is no delay in the information transmission of the agents within the communication range, while the information of the agents outside the communication range is delayed because it needs to be transferred by other agents, the grouping coefficient With the following definition: This grouping coefficient is used to determine whether the agent needs to track the estimated center. When the agent reaches the vicinity of the center or encounters an agent that is closer to the center than itself during the process of tracking the center, it will give up tracking the center and set the grouping coefficient Set to 0, otherwise 1; due to the existence of multi-hop information transmission communication delay, each agent has different estimates of the center of its subcluster. This discriminant can avoid the failure of cohesion caused by the same group of agents always tracking different centers.

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