Multiagent Pursuit-Evasion Problem with the Pursuers Moving at Uncertain Speeds

Yan, Fuhan; Jiang, Jiuchuan; Di, Kai; Jiang, Yichuan; Hao, Zhifeng

doi:10.1007/s10846-018-0841-5

Cited by 21 publications

(13 citation statements)

References 19 publications

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“…Firstly, one of underwater robots is designated as the leader. When receiving the when the leader appears faults a 3 when one of the underwater robots finds the target a 4 when one of the underwater robots finds the target a 5 when the underwater robots can't detect the target a 6 when the leader appears faults a 7 when the distance between the leader and the target is less than or equal to the pursuit distance R a 8 when the underwater robots form the circular encirclement, but not satisfy the condition in the desired pursuit distance a 9 when the leader appears faults a 10 when the leader appears faults a 11 when the underwater robots can't detect the target a 12 when the leader appears faults accusation instruction of starting the pursuit from shore or mother ship, the leader issues the assemble instruction (a 0 ). Multiple underwater robots form the initial formation, and enter into the initial motion state (Q 1 ).…”

Section: Synergy Pursuit Model Based On Finite State Machinementioning

confidence: 99%

“…Pursuit problem [1][2][3][4][5][6][7][8][9][10][11][12][13] is one of the hot spots in the field of artificial intelligence, and it is also a typical problem to study the cooperation and confrontation of multiple robots. Pursuit problem originates from the predatory behavior of the animal kingdom, such as coyotes to hunt preys.…”

Section: Introductionmentioning

confidence: 99%

“…As long as the pursuers adopt the corresponding strategies, the pursuers should capture the evaders when the time is allowed. The literatures [7][8][9][10] propose different pursuit methods to pursue the invader whose speed is faster than the pursuit robot. These methods require that the pursuit robot and the invader must know the intentions with each other.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Research on Synergy Pursuit Strategy of Multiple Underwater Robots

Jia

et al. 2019

J Intell Robot Syst

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This paper presents a synergy pursuit strategy that multiple underwater robots pursue a single moving target based on finite state machine. The processes of the pursuit are defined as seven different states, and to implement each state, the corresponding strategies are designed. As the strategy for each state is implemented by a corresponding formation control, a synergy control law is also designed for multiple underwater robots. In the design of the pursuit strategy, the definition of encirclement is put forward for the underwater robots. Furthermore, the proof that a point is encircled by other points on the plane is given. To solve the problem of the concealment in the tracking and the pursuit, a semicircular pursuit strategy and a circular pursuit strategy are also proposed. Finally, based on this pursuit strategy, the simulation of whole process is carried out with the MOOS(Mission Oriented Operating Suite) platform, and the effectiveness of the semicircular and circular pursuit strategy are verified by lake experiment with practical robots. The results of simulation and lake experiment prove that this pursuit strategy can realize synergy tracking and pursuit for a single moving target under the given conditions.

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Section: Synergy Pursuit Model Based On Finite State Machinementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Research on Synergy Pursuit Strategy of Multiple Underwater Robots

Jia

et al. 2019

J Intell Robot Syst

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“…The analysis assumes that the speed of the predator is certain. The case where the pursuers move at uncertain speeds have been studied in [44]. Reference [45] proposed solutions to the flocking and target interception problems of multiple nonholonomic unicycle-type robots using a distance-based framework.…”

Section: Introductionmentioning

confidence: 99%

Biologically Based Control of a Fleet of Unmanned Aerial Vehicles Facing Multiple Threats

El-Férik

2020

IEEE Access

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This paper addresses a set of multiagent, unmanned, aerial vehicles (UAVs) in a mission within a threat-prone environment. Each UAV is considered as a nonholonomic, nonlinear model moving in a two dimensional space. The system is composed of a fleet of UAVs, competing UAVs and a target. The approach proposed in this paper is based on a biological model representing collective behavior in predator-prey systems. The fleet of UAV's (prey) is moving cohesively towards a target and they can come under attack from competing UAV's (predators) which are also expected to avoid a certain area around the target, treating it as an obstacle that they have to avoid. Prey and predators are expected to obey certain social behaviors within their respective species that include coherent motion, separation to avoid collision, and alignment. The prey are also connected through an adaptable network. During attacks, this networked population of prey could be divided into several small groups that are still connected and naturally observe the same social behavior. To identify these groups and their members, the density-based algorithm DBSCAN is used. The aim of this work is to use this biologically inspired model along with a robust feedback linearization controller to achieve both target pursuance and effective evasion from two predators. Simulation results demonstrate the different aspects and features provided in the proposed approach. INDEX TERMS Nonlinear nonholonomic system; Biology-based control; Density-based clustering, Adapt-then-combine (ATC) algorithm;

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“…As long as the pursuer adopts the corresponding pursuit strategy, the escapee must be captured. The literatures [6][7][8] propose different pursuit methods to pursue the escapee, and use the method of Apollo circle to pursue the fast escapee, but it is very difficult to ensure that adjacent Apollo circles can intersect with each other. Literature [6] uses the method of reinforcement learning to realize the pursuit, but in practical ocean environment, this method can hardly meet the high realtime environment.…”

Section: Introductionmentioning

confidence: 99%

A Novel Cooperative Pursuit Strategy in Multiple Underwater robots

Jia

Feng

et al. 2019

OCEANS 2019 - Marseille

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A novel cooperative pursuit strategy for multiple underwater robots is proposed in this paper. In this pursuit strategy, the pursuit-evasion game is studied in two stages. In the first stages, when the target keeps the static state, the rapidlyexploring random tree (RRT) search algorithm is used to realize the real-time path replanning for multiple underwater robots, so as to avoid the target detection range and reach the desired precapture position. Therefore, the concealed problem of encircling the static target is solved. In the second stages, when multiple underwater robots enter into the target detection range, the target will start to escape. In order to solve the problem of capturing a moving target, the cooperative control law for multiple underwater robots is proposed. A circular formation is formed to pursue the target using the cooperative control law so that the capture error can meet a certain performance indexes. Finally, the simulation results show the effectiveness and feasibility of the proposed cooperative pursuit strategy.

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Multiagent Pursuit-Evasion Problem with the Pursuers Moving at Uncertain Speeds

Cited by 21 publications

References 19 publications

Research on Synergy Pursuit Strategy of Multiple Underwater Robots

Research on Synergy Pursuit Strategy of Multiple Underwater Robots

Biologically Based Control of a Fleet of Unmanned Aerial Vehicles Facing Multiple Threats

A Novel Cooperative Pursuit Strategy in Multiple Underwater robots

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