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

Article type: Research Article

Authors: Souidi, Mohammed El Habib^{a; b; *} | Piao, Songhao^b | Li, Guo^b

Affiliations: [a] Department of Computer Science, University of Khenchela, 40000 Khenchela, Algeria. E-mail: [email protected] | [b] School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, China. E-mails: [email protected], [email protected]

Correspondence: [*] Corresponding author. E-mail: [email protected].

Abstract: 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.

Keywords: Obstacle avoidance, path planning, pursuit-evasion, mobile agents

DOI: 10.3233/WEB-170369

Journal: Web Intelligence, vol. 15, no. 4, pp. 325-334, 2017