Mobile agents path planning based on an extension of Bug-Algorithms and applied to the pursuit-evasion game

Pursuit-evasion game is a known problem in Multi-agent systems. This problem is approached through the elaboration of different task coordination and path planning mechanisms. This paper proposes a new sensor-based obstacle avoidance method extended from Bug-Algorithms with the aim of providing an efficient path planning to the pursuers during the targets' capture. Noting that, the environment is decomposed on a grid of cells, in which Markov Decision Process (MDP) principles are implemented to lead the motion of the agents. In relation to Bug-Algorithms, this method increases the utilization of the sensors data to improve the decision making regarding the obstacle's leaving point. This fact makes this method goal-oriented and decreases the pursuers' path to the goal. Moreover, we showcase the performance of this method through a comparative study with our previous works in which Bug-2 algorithm was used to avoid the obstacles encountered.