Probabilistic and Self-Organized Strategies to Coordinate Multiple Robotic Pursuers in the Pursuit o

Abstract this paper addresses the problem of coordinating multiple robotic pursuers in tracking and catching an adversarial evader in a dynamic environment. We assume that the adversarial evader can be detected independently by one pursuer but two pursuers are needed for a successful capture. We aim to reduce the capture time of the evader. Therefore, we model the motion of the evader by the probabilistic method and incorporate the model into directing the motion of the pursuers. In addition, we keep the pursuer communicating with at least another pursuer so that the evader found can be known immediately by another pursuer and then a quick capture can be produced by these two pursuers. By combining the two issues above, the evader can be detected and captured as quickly as possible. Finally, we present the simulation results to demonstrate the performance of our algorithm in an indoor environment. The results show that our method can greatly reduce the capture time of the evader.

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