Multi-agent system channel type area coverage control method based on arc length

Abstract

The invention relates to the field of area coverage control methods, and discloses a multi-agent system channel type area coverage control method based on arc length, which comprises the following steps: S1, target area division: dividing a channel type target area into a plurality of sequential sub-areas based on an arc length division method; s2, designing a distributed controller of a virtual leader agent, wherein the distributed controller of the virtual leader agent ensures that the arc length of a coverage area of each group of agents is in direct proportion to the number of the group of agents; and S3, designing an individual intelligent agent distributed controller, and enabling the intelligent agent to realize sequential team coverage control on the area S by combining the individual intelligent agent distributed controller with a distributed controller of a virtual leader intelligent agent. The distributed controller designed by the invention enables the intelligent agent to adjust the coverage area of the intelligent agent in real time according to the change of the actual environment.

Description

Technical Field

[0001] The present invention relates to the field of area coverage control methods, and in particular to an arc-length-based multi-agent system channel-type area coverage control method. Background Art

[0002] In the field of multi-agent systems, coverage control problems are widely used in many fields such as military surveillance, environmental monitoring, agricultural management, etc., especially in channel-type areas such as river monitoring and border patrol. These areas are usually non-convex and long and narrow, with uneven information distribution, which puts high demands on the deployment and control strategies of agents.

[0003] In the prior art, although a variety of coverage control methods have been proposed, such as Voronoi partitioning, power graph and weighted Voronoi partitioning, these methods have the following obvious disadvantages and shortcomings:

[0004] 1. Insufficient dynamic adaptability: Existing partitioning methods often lack dynamic adjustment capabilities and cannot flexibly adjust the coverage area according to changes in the number of agents, resulting in unbalanced agent loads during task execution;

[0005] 2. Slow response to boundary changes: Traditional coverage control methods are not sensitive enough to the dynamic changes of virtual leader agents and cannot adjust the positions of individual agents in time, thus affecting the overall coverage effect;

[0006] 3. Insufficient processing of information diversity: In channel-type areas where multiple types of information need to be detected, existing methods usually rely on a single group of agents for coverage, which results in the inability to effectively meet the detection needs of different types of information. Even if multiple heterogeneous sensors are considered for each agent, due to the differences in the distribution of different information in space, other information may not be fully detected, resulting in incomplete coverage and inability to fully detect the required information.

[0007] Based on this, the present invention proposes a channel-type area coverage control method for a multi-agent system based on arc length. Summary of the invention

[0008] The object of the present invention is to provide a channel-type area coverage control method for a multi-agent system based on arc length to solve the problems raised in the above-mentioned background technology.

[0009] To achieve the above object, the present invention provides the following technical solution: a channel-type area coverage control method of a multi-agent system based on arc length, comprising the following steps:

[0010] Step S1, target area division, based on the arc length partitioning method, the channel type target area is divided into multiple sequential sub-areas;

[0011] Step S2, designing a distributed controller of the virtual leader agent, the distributed controller of the virtual leader agent ensures that the arc length of the coverage area of ​​each group of agents is proportional to the number of agents in the group;

[0012] Step S3, the design of the distributed controller of the individual intelligent agent. The distributed controller of the individual intelligent agent combined with the distributed controller of the virtual leader intelligent agent can enable the intelligent agent to achieve sequential team coverage control of area S.

[0013] As a preferred embodiment, the target area division process in step S1 is to deploy n groups of heterogeneous multi-agent systems in a channel-type area S, the boundary of which is defined by two regular curves. and Definition, where the i-th group of agents contains n i agents, i=1,...,n, the center line of the channel area is a regular curve, defined as is a regular curve with the horizontal axis as parameter, and its parametric equation is γ(x)=(x,y(x)) Τ , on the midline of region S Deploy n+2 virtual leader agents on the network and define is the position of the ith virtual leader agent, where i = 0, 1, ..., n + 1. According to the initial position of the virtual leader agent, these agents are distributed in the order of their horizontal coordinates. On, that is l=(l 0 , l 1 ,…,l n+1 ) represents the location set of these virtual leader agents, and the coverage area of ​​each group of agents is The coverage area of ​​the entire intelligent group is Where Q = Q 1 ∪Q 2 ∪...∪Q n The coverage area Q is defined by l 0 and l n+1 The arc length of the curve between is determined by the specified fixed value. The boundaries of the region are defined as And the set of indicators of the groups adjacent to the i-th group of agents is The i-th group of agents covers an area Q i The range of the curve Decision, which is defined as follows:

[0014]

[0015] in represents the arc length of the curve, n i represents the number of agents in the i-th group, |S i | represents the curve S i The length of p i,j For curve S i With curve S j The intersection of satisfies the following relationship:

[0016]

[0017] in Let p 1,0 = l 0 ,p n,n+1 = l n+1 , Q i With Q j The shared boundary of is defined as:

[0018]

[0019] in It passes through point p i,j And with the curve The line segment perpendicular to the tangent direction of For curve At point p i,j Tangent line at i=1,...,nl 0 and l n Located at the back end and front end of area Q respectively.

[0020] As a preferred embodiment: the coverage area Q of the i-th group of agents i Is and is the internal area of ​​the boundary, and its interior is a road-connected area, satisfying where i=1,2,...,n, Let p i,m represents the position of the mth agent in the i-th group of agents, where i=1,...,n,m=1,...,n i ,definition is the position set of the i-th group of agents, and P = (P 1 ,P 2 ,...,P n ) is the location set of this group of agents, for those distributed in area Q i Agent p in i,m , its coverage area Q im It is defined by the following Voronoi partitioning:

[0021] Q im= {q∈Q i ∣||qp im || 2 ≤||qp is || 2 ,s=1,...,n i ,s≠m}, (1.6)

[0022] where n i represents the number of agents in the i-th group, It is area Q im The boundary of the agent p im It shares some region boundaries with its Voronoi partitioning neighbors, and the set of neighbor indices is where s=1,...,n i ,s≠m.

[0023] As a preferred embodiment: the design process of the virtual leader agent distributed controller in step S2 is as follows: i The following first-order distributed controller is designed:

[0024]

[0025] in Indicates that the curve γ is at point l i The tangent vector at

[0026]

[0027] and Represents the arc length of the curve, i=1,2,...,n.

[0028] As a preferred embodiment: the distributed controller of the individual intelligent body in step S3 is as follows:

[0029]

[0030] Among them, k im >0, and Respectively represent the area Q im The mass and center of mass are defined as:

[0031]

[0032] Defined by (1.11), i = 1, 2, ..., n, m = 1, 2, ..., n i .

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] The distributed controller with dynamic adaptability enhancement design of the present invention enables the intelligent agent to adjust its coverage area in real time according to the changes in the actual environment. When the number of intelligent agents changes, each team can reasonably adjust the size of the coverage area according to the number of intelligent agents to achieve load balancing. This improvement significantly enhances the adaptability of the system in a dynamic environment.

[0035] Improved boundary response speed, where the controller of each individual agent can quickly respond to boundary changes of the virtual leader agent, ensuring optimal local deployment in dynamic environments;

[0036] Diversified information detection capabilities. Through the collaborative work of a heterogeneous intelligent team, the present invention enables the system to effectively process different types of information. For example, in a river monitoring scenario, the system can simultaneously detect water quality indicators, temperature, and radioactivity, etc. Compared with the traditional single sensor solution, the information collection is more comprehensive. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 is a flow chart of the method of the present invention;

[0038] Figure 2 It is a schematic diagram of the coverage area division in the channel type area S;

[0039] Figure 3 It is the motion trajectory diagram covered by the agent in sequence;

[0040] Figure 4 The arc length variation diagram of the coverage area of ​​each group of agents;

[0041] Figure 5 is the overall cost function;

[0042] Figure 6 This is a graph showing the arc length changes in the coverage area of ​​each group of agents. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions 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. 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.

[0044] Example

[0045] See also Figure 1 , a channel-type area coverage control method of a multi-agent system based on arc length shown in the figure includes the following steps:

[0046] Step S1, target area division, based on the arc length partitioning method, the channel type target area is divided into multiple sequential sub-areas;

[0047] Step S2, designing a distributed controller of the virtual leader agent, the distributed controller of the virtual leader agent ensures that the arc length of the coverage area of ​​each group of agents is proportional to the number of agents in the group;

[0048] Step S3, the design of the distributed controller of the individual intelligent agent. The distributed controller of the individual intelligent agent combined with the distributed controller of the virtual leader intelligent agent can enable the intelligent agent to achieve sequential team coverage control of area S.

[0049] In the present invention, the symbols are used represents a one-dimensional Euclidean space, represents a non-negative real number, the symbol and Represents n-dimensional Euclidean space and its corresponding n×n matrix space respectively. For any real number Define its absolute value |x|, for the vector Its Euclidean norm is expressed as ||x||, x=(x 1 ,x 2 ,...,x n ) Τ >>0 means x i >0,i=1,2,...,n, definition is a matrix, and its transpose is represented by A Τ , while row(A) i represents the row vector of the elements in the ith row of matrix A. If all eigenvalues ​​of matrix A have negative real parts, then A is called a Hurwitz matrix. If all off-diagonal elements of A are non-negative, then A is called a Metzler matrix. Definition is a two-dimensional region, if for any If there exists a continuous mapping τ:[0,1]→X such that τ(0)=a, τ(1)=b, then the region X is called road connected.

[0050] In two-dimensional space In , consider a regular curve γ with the horizontal axis as parameter: The coordinates of the curve satisfy a certain functional relationship y=y(x), so the regular curve can be expressed as

[0051] γ(x)=(x,y(x)) Τ .(1.1)

[0052] On the curve γ, the tangent vector at point p = (x, y(x)) is expressed as γ′(x) = (1, y′(x)), which points to the positive direction of the curve.a ,y(x a )) to point b = (x b ,y(x b The arc length of )) is,

[0053]

[0054] The curvature κ(p) of the curve γ at point p = (x, y(x)) is defined as,

[0055]

[0056] The present invention is defined as deploying n groups of heterogeneous multi-agent systems in a channel-shaped area S, the boundary of which is defined by two regular curves and Definition, where the i-th group of agents contains n i agents, i=1,...,n, the center line of the channel area is also a regular curve, defined as is a regular curve with the horizontal axis as parameter, and its parametric equation is γ(x)=(x,y(x)) Τ In order to define the coverage area between different agent groups, the midline of area S Deploy n+2 virtual leader agents on the network and define is the position of the i-th virtual leader agent, where i = 0, 1, ..., n + 1. According to the initial position of the virtual leader agent, these agents are distributed in the order of their horizontal coordinates. On, that is l=(l 0 , l 1 ,…,l n+1 ) represents the location set of these virtual leader agents, and the coverage area of ​​each group of agents is The coverage area of ​​the entire intelligent group is Where Q = Q 1 ∪Q 2 ∪…∪Q n , the coverage area Q is defined by l 0 and l n+1 The arc length of the curve between is determined by the specified fixed value. The boundaries of the region are defined as And the set of indicators of the groups adjacent to the i-th group of agents is The i-th group of agents covers an area Q i The range of the curve Decision, which is defined as follows:

[0057]

[0058] in represents the arc length of the curve, n i represents the number of agents in the i-th group, |S i | represents the curve S i The length of p i,j For curve S i With curve S j The intersection of satisfies the following relationship:

[0059]

[0060] in In particular, let p 1,0 = l 0 , p n,n+1 = l n+1 ., Q i With Q j The shared boundary of is defined as:

[0061]

[0062] in It passes through point p i,j And with the curve The line segment perpendicular to the tangent direction of For curve At point p i,j Tangent line at i = 1,…,n., l 0 and l n They are located at the back end and front end of region Q respectively. At this time, no agent is deployed in the group, that is, n 0 =n n+1 =0, is a line passing through point p 1,0 And with Directions are perpendicular to each other, and accordingly, Similar conditions are also met.

[0063] Next, the present invention gives the coverage area Q of the i-th group of agents: i Definition of .

[0064] Definition 1: The coverage area Q of the i-th group of agents i Is and is the internal area of ​​the boundary, and its interior is a road-connected area, satisfying where i=1,2,...,n,

[0065] Let p i,mrepresents the position of the mth agent in the i-th group of agents, where i=1,...,n,m=1,...,n i ,definition is the position set of the i-th group of agents, and P = (P 1 ,P 2 ,…,P n ) is the location set of this group of agents, for those distributed in area Q i Agent p in i,m , which covers an area Q im It is defined by the following Voronoi partitioning:

[0066] Q im = {q∈Q i ∣||qp im || 2 ≤||qp is || 2 ,s=1,...,n i ,s≠m}, (1.6)

[0067] where n i represents the number of agents in the i-th group, It is area Q im The boundary of the agent p im It shares some region boundaries with its Voronoi partitioning neighbors, and the set of neighbor indices is where s=1,...,n i , s≠m.

[0068] Figure 2 The figure shows the deployment of three groups of agents in a channel-shaped region S. The green curve represents the boundary of region S. and The grey dashed line indicates the midline of region S The blue solid dot indicates the position of the virtual leader agent, the blue dotted line indicates the boundary between different groups, the red solid dot indicates the position of the third group of agents, the red dotted line indicates the shared boundary between agents in the same group, and the brown arrow indicates the unit external normal vector at the boundary. Area Q moves from left to right along area S under the drive of the virtual leader. In this process, the length of the area Remain unchanged.

[0069] Among them, the coverage area Q of each group of agents is i is a connected region. The scope of region Q is not necessarily limited to and Between, if and intersect, then Q i The inclusion curve S iA simply connected region, region Q i-1 and Q i+1 There is a partial shared area Q i-1 ∩Q i+1 , which may lead to a collision between the i-1th group of agents and the i+1th group of agents. Therefore, the present invention requires that the agents between different groups have an obstacle avoidance mechanism, such as a method based on potential field or control obstacle function.

[0070] To describe the coverage effect of this multi-agent system on area Q, we first define the coverage area Q of the i-th group of agents: i The cost function is:

[0071]

[0072] where α i >0 indicates the gain coefficient of the i-th group of agents, represents the density function value of the agent detection point q, i = 1, 2, ..., n. At this time, the cost function of n groups of agents can be expressed as:

[0073]

[0074] in represents the coverage cost function of the i-th group of agents. Since different groups of agents are equipped with different sensors, they can only identify specific targets in the coverage area, which leads to the different groups of agents detecting The content is different. This optimization problem involves two levels of area division. First, each group of agents divides the coverage area of ​​the group according to the position of the virtual leader. On this basis, each group of agents is deployed to the local optimal position of its coverage area so that (1.7) reaches the local minimum.

[0075] The coverage control problem in the above channel-type region can be defined as follows.

[0076] Definition 2: Sequential coverage control deploys n sets of heterogeneous multi-agent systems in a channel-shaped area S. The coverage area Q of these agents moves along the positive direction of the area and maintains The coverage area between different groups is divided by Definition 1, while the coverage area of ​​agents in the same group is divided by Voronoi partitioning (1.6). The dynamics of the virtual leader agent and each agent are described by the following first-order integrator:

[0077]

[0078]

[0079] Where s=0,1,...,n+1,i=1,2,...,n,m=1,2,...,n i , in order to achieve sequential coverage control of area S, the designed controller must meet the following conditions:

[0080] (i)

[0081]

[0082] (ii) Minimize the cost function (1.7).

[0083] The present invention considers that region Q is a dynamic situation, and at this time the requirement is to satisfy Where v>0, the virtual leader agent l 0 and l n+1 Moving along the positive direction of the curve γ at the same rate ensures that the curve of the coverage area of ​​the agent The length remains the same.

[0084] For the virtual leader agent l i , the present invention designs the following first-order distributed controller:

[0085]

[0086] in Indicates that the curve γ is at point l i The tangent vector at

[0087]

[0088] and Represents the arc length of the curve, i=1,2,...,n.

[0089] Before presenting the first theoretical result, we first give the following lemma about positive systems.

[0090] Lemma 1: Let is a Metzler matrix, then A is Hurwitz if and only if there exists a vector θ>>0 such that Aθ<<0.

[0091] Lemma 2: When the area Q is stationary, the virtual leader is driven by the controller (1.11), and each group of agents covers the area Q i The corresponding arc length satisfies (1.10).

[0092] Furthermore, the controller (1.11) of the virtual leader ensures that the arc length of the coverage area of ​​each group of intelligent agents is proportional to the number of intelligent agents in the group. At the same time, the controller designed by the present invention realizes the flexible deployment of intelligent agents. When a new intelligent agent is added to a group or an intelligent agent fails and needs to exit, the controller can dynamically adjust the size of the coverage area of ​​the group to ensure load balance of the group of intelligent agents.

[0093] Then a controller is designed for each agent to minimize the cost function (1.7). Before designing the controller, it is necessary to analyze the impact of the virtual leader agent and each agent on the value of the cost function (1.7).

[0094] First, consider the impact of the virtual leader agent on the value of the cost function (1.7) and find l for (1.7). i The partial derivative of , we can get:

[0095]

[0096] in, Indicates that the i-th group of agents is located in region Q i The number of agents at the boundary that are Share some area boundaries, and these agents are called the boundary group of the i-th group of agents; similarly, Indicates that the i-th group of agents is located in region Q i The number of agents inside, which are related to There is no shared region boundary, and these agents are called the internal group of the i-th group of agents. Here, i=1,2,...,n,N ij Representing Boundaries The unit external normal vector, it is worth noting that N ij and N ji are two unit vectors with opposite directions, namely N ij =-N ji . Represents the unit external normal vector of the boundary of region S, where b = 1, 2, for The boundaries of the coverage areas of different groups of agents are determined by equation (1.5). Therefore, The partial derivatives of The following lemma gives the calculation result of the partial derivative.

[0097] Lemma 3: For qAbout l i The partial derivative of is,

[0098]

[0099] in

[0100]

[0101]

[0102] κ(p i,j ) indicates that the curve γ is at point p i,j The curvature at λ satisfies i=1,2,...,n.

[0103] Next, consider agent p im The local optimal position of the cost function (1.7) about p im The partial derivative of can be obtained:

[0104]

[0105] in, Representing Boundaries The unit external normal vector at , N im,s Represents the shared boundary among the i-th group of agents The unit external normal vector at .

[0106] According to the Voronoi segmentation definition (1.6), for any ||qp im || 2 =||qp is || 2 Established, N im,s and N is,m is a unit vector with opposite directions, that is, N im,s =-N is,m , so the third line of formula (1.14) can be eliminated, for any Established.

[0107] Considering the virtual leader i The movement will result in area Q i The border Change, when the agent p im The area and Q i When there is a shared boundary, the agent also needs to consider the dynamic changes of the boundary. Therefore, when designing the agent p im When designing a controller, the influence of the dynamic boundary on the cost function (1.7) needs to be considered. According to the above analysis, the present invention provides a controller for the agent p. im The following controller is designed:

[0108]

[0109] Among them, k im >0, and Respectively represent the area Q im The mass and center of mass are defined as:

[0110]

[0111] By Lemma 3, Defined by (1.11), i = 1, 2, ..., n, m = 1, 2, ..., n i .

[0112] Furthermore, the agent's controller (1.15) is a distributed controller. The first part of the controller requires the use of p im The information of Voronoi segmentation neighbors, η im Item and Region Dynamic Boundaries Therefore, this item needs to consider l i and l j To the regional boundary Due to the influence of , the agents in the boundary group can obtain the dynamic state information of the virtual leader agents in their adjacent groups, which can be obtained by the agents in the adjacent boundary groups.

[0113] At the same time, in formula (1.16), when i = 1, j = 0, is fixed, at this time Since the virtual leader agent l 0 The group has no agents, so When i=n, ​​j=n+1, similar results can be obtained.

[0114] Therefore, n groups of heterogeneous multi-agents are deployed in the channel-type region S. When the region Q is dynamic, given the virtual leader agent and the initial position of each group of agents l(0) = (l 0 (0), l 1 (0), ..., l n+1 (0)) and P(0)=(P 1 (0),P 2 (0),...,P n (0)), driven by controllers (1.11) and (1.15), this group of agents can achieve sequential team coverage control of area S.

[0115] The specific implementation mode of the present invention aims to elaborate on the innovative methods and control strategies proposed in the content of the present invention in detail, so as to facilitate effective coverage control in practical applications. In order to demonstrate the effectiveness of the coverage control strategy proposed by the invention, the effectiveness of the present invention will be explained by mathematical proof and numerical simulation respectively.

[0116] Mathematical proof, replacing the valence function (1.7) with the Lyapunov function:

[0117]

[0118] Obviously, V(t)≥0 is true. Taking the derivative of the function V(t) with respect to time t, we can get:

[0119]

[0120] Among them, λ im and η im Defined by equation (1.16), the first term on the right side of equation (1.18) is only related to the region boundary about, and is related to the agents in the boundary groups in each group, so this term can be rewritten as:

[0121]

[0122] The first integral on the right side of equation (1.19) represents the effect of the i-th virtual leader's movement on the cost function of the boundary group in the i-th group of agents, so this term is related to The second integral on the right represents the virtual leader l adjacent to the i-th group. j The impact of movement on the cost function of the boundary group in the i-th group of agents, so this term is related to about, among which It can be seen that the cost function of the boundary group is affected by the virtual leader that determines the shared boundary, which can be seen by Definition (1.5) yields.

[0123] For the last term on the right side of (1.18), replace λ im η im Substituting the value of into , we get:

[0124]

[0125] (1.20) The last term in the intermediate equation is about the region boundary , so this term is only relevant for the agents in the boundary group.

[0126] Substituting (1.19) and (1.20) into (1.18) we obtain:

[0127]

[0128] Due to k im >0, so According to the LaSalle invariance principle, each agent p im Will converge to the centroid of its coverage area At the same time, the cost function (1.7) is minimized, so it can be concluded that the controllers (1.11) and (1.15) designed by the present invention can achieve sequential team coverage control of area S.

[0129] Among them, since the region S is a non-convex region, the agent p in the boundary group im The coverage area may be a non-convex area, where i = 1, 2, ..., n, If the coverage area Q of the boundary group agent im Centroid In area Q im If the agent still has a tendency to move outside the area, the agent is required to move along its or The projection direction of the tangent line moves to ensure that the agents in the boundary group remain in region Q im Inside.

[0130] Numerical simulation verifies the correctness of the theory proposed in this invention through numerical simulation. Simulation one is used to verify the applicability of sequential covering control theory in river areas; simulation two tests the robustness of the virtual leader intelligent agent controller to changes in the number of agents in each group.

[0131] Simulation 1

[0132] like Figure 3 As shown in the figure, a section of the Yellow River in Inner Mongolia Autonomous Region was selected for verification. The section is located at 111.4359°E east longitude and 39.9018°N north latitude. Figure 3 The figure shows the movement trajectory of the agents driven by the virtual leader agent, where the movement speed of the virtual leader agent is limited to 2m / s, and the movement speed of each group of agents is limited to 3m / s. In the figure, the solid dots represent the initial positions of the agents, the asterisks represent the final positions, the cyan curve represents the movement trajectory of the first group of agents, the blue curve represents the second group of agents, and the magenta curve represents the third group of agents.

[0133] In simulation 1, each group of agents uses a Gaussian density function of the following form:

[0134]

[0135] Where i = 1, 2, 3. For the first group of agents, the density function is defined as Let [x 1 x 2 x 3 ]=[150350 560],[y 1 y 2 y 3 ]=[50 200 300],σ 1 =σ 2 =σ 3 =150, let the density function of the second group of agents be a uniform density function For the density function of the third group of agents Let [x 1 x 2 ]=[200 300],[y 1 y 2 ]=[200 300],σ 1 =σ 2 =150.

[0136] The initial positions of the virtual leader agents are l 0 (0) = [50 145] Τ ,l 1 (0) = [90 131] Τ ,l 2 (0) = [153 152] Τ ,l 3 (0) = [250 181] Τ ,l 4 (0) = [300 219] Τ , the initial positions of the first group of agents are p 11 =[75 160] Τ ,p 12 =[60 120] Τ ,p 13 =[58 141] Τ ,p 14 =[100 110] Τ ,p 15 =[100 140] Τ , the initial positions of the second group of agents are p 21 =[170 160] Τ ,p 22 =[180 140] Τ ,p 23 =[170 100] Τ , the initial positions of the third group of agents are p 31 =[220 180]Τ ,p 32 =[250 130] Τ ,p 33 =[260 130] Τ ,p 34 =[270 170] Τ , let the gain coefficient of each group of agents be [α 1 α 2 α 3 ]=[1 2 3].

[0137] Figure 4 The changes in the arc length of the area covered by each group of agents are recorded. Figure 4 It can be seen that the arc length of the coverage area of ​​each group of agents is proportional to the number of agents in the group. Figure 5 It shows the change of the cost function of this group of agents, indicating that when the leader agent l 0 and l 4 When the motion stops, that is, when the dynamic area Q no longer moves, the cost function converges to the local minimum.

[0138] Simulation 2

[0139] In this part of the simulation, we consider the change in arc length of the area covered by each group of agents when a group of agents leaves the team or a new agent joins. This simulation uses the same task area, density function, initial position of the agents, and initial position of the leader agent as in simulation 1. At 200s, the agent p in the first group 15 Leave the team, and a new agent p joins the third group 35 , Figure 6 The changes in the arc length of the coverage area of ​​each group of intelligent agents are recorded, from which it can be seen that when the number of intelligent agents in each group changes, the controller (1.11) designed by the present invention can adjust the range of the coverage area of ​​the group in real time to ensure that the arc length of the coverage area of ​​each group of intelligent agents is proportional to the number of intelligent agents in the group.

[0140] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0141] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A channel-type area coverage control method for a multi-agent system based on arc length, characterized in that: The steps include: Step S1, target area division, based on the arc length partitioning method, the channel type target area is divided into multiple sequential sub-areas; Step S2, designing a distributed controller of the virtual leader agent, the distributed controller of the virtual leader agent ensures that the arc length of the coverage area of ​​each group of agents is proportional to the number of agents in the group; Step S3, the design of the distributed controller of the individual intelligent agent. The distributed controller of the individual intelligent agent combined with the distributed controller of the virtual leader intelligent agent can enable the intelligent agent to achieve sequential team coverage control of area S.

2. The arc-length-based channel-type area coverage control method for a multi-agent system according to claim 1, characterized in that: The target area division process in step S1 is to deploy n groups of heterogeneous multi-agent systems in a channel-type area S, the boundary of which is defined by two regular curves. and Definition, where the i-th group of agents contains n i agents, i=1,...,n, the center line of the channel area is a regular curve, defined as is a regular curve with the horizontal axis as parameter, and its parametric equation is γ(x)=(x,y(x)) Τ , on the midline of region S Deploy n+2 virtual leader agents on the network and define is the position of the i-th virtual leader agent, where i = 0, 1, ..., n + 1. According to the initial position of the virtual leader agent, these agents are distributed in the order of their horizontal coordinates. On, that is l=(l0,l1,...,l n+1 ) represents the location set of these virtual leader agents, and the coverage area of ​​each group of agents is The coverage area of ​​the entire intelligent group is where Q = Q1∪Q2∪…∪Q n The coverage area Q is composed of l0 and l n+1 The arc length of the curve between is determined by the specified fixed value. The boundaries of the region are defined as And the set of indicators of the groups adjacent to the i-th group of agents is The i-th group of agents covers an area Q i The range of the curve Decision, which is defined as follows: in represents the arc length of the curve, n i represents the number of agents in the i-th group, |S i | represents the curve S i The length of p i,j For curve S i With curve S j The intersection of satisfies the following relationship: in Let p 1,0 =l0,p n,n+1 = l n+1 , Q i With Q j The shared boundary of is defined as: in is a point passing through pi,j and connected to the curve γ′(xp i,j ) is a line segment perpendicular to the tangent direction of For curve At point p i,j Tangent lines at i = 1, ..., n.l0 and l n Located at the back end and front end of area Q respectively.

3. The arc-length-based channel-type area coverage control method for a multi-agent system according to claim 2, characterized in that: The coverage area Q of the i-th group of agents i Is and is the internal area of ​​the boundary, and its interior is a road-connected area, satisfying where i=1,2,...,n, Let p i,m represents the position of the mth agent in the i-th group of agents, where i=1,...,n,m=1,...,n i ,definition is the position set of the i-th group of agents, and P = (P1, P2, ..., P n ) is the location set of this group of agents, for those distributed in area Q i Agent p in i,m , its coverage area Q im It is defined by the following Voronoi partitioning: Q im ={q∈Q i ||∣q-p im || 2 ≤||q-p is || 2 ,s=1,...,n i ,s≠m}, (1.6) Where n i represents the number of agents in the i-th group, It is area Q im The boundary of the agent p im It shares some region boundaries with its Voronoi partitioning neighbors, and the set of neighbor indices is where s=1,...,n i ,s≠m.

4. The arc-length-based channel-type area coverage control method for a multi-agent system according to claim 3, characterized in that: The design process of the virtual leader agent distributed controller in step S2 is as follows: i The following first-order distributed controller is designed: in Indicates that the curve γ is at point l i The tangent vector at and Represents the arc length of the curve, i=1,2,...,n.

5. The arc-length-based channel-type area coverage control method for a multi-agent system according to claim 4, characterized in that: The distributed controller of the individual agents in step S3 is as follows: Among them, k im >0, and Respectively represent the area Q im The mass and center of mass are defined as: Defined by equation (1.11), i=1,2,v,n,m=1,2,...,n i .

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