Title: Experimental evaluation of new navigator of mobile robot using fuzzy Q-learning

Authors: Fadhila Lachekhab; Mohamed Tadjine; Mohamed Kesraoui

Addresses: Applied Automatics and Signal Processing Laboratory, University of Mhamed Bougara, Boumerdes BP3500, Algeria ' Process Control Laboratory, Polytechnic National School, Algiers, Algeria ' Applied Automatics and Signal Processing Laboratory, University of Mhamed Bougara, Boumerdes BP3500, Algeria

Abstract: In this paper, we propose an approach of fusing the fuzzy control actions of the obstacle avoidance and goal-seeking which utilises fuzzy logic and reinforcement learning for navigation of a mobile robot in unknown environments. The proposed reactive navigator consists of three modules: move to goal, obstacle avoidance, and fuzzy behaviour supervisor. The selection of the actions available in each fuzzy rule is learned through reinforcement learning (Q-learning algorithm). A new and powerful method is used to construct automatically these rules. The experiments carried out on the Pioneer 2P mobile robot have shown that the navigator is able to perform a successful navigation task in various unknown environments with smooth action and exceptionally good robustness.

Keywords: fuzzy Q-learning; FQL; fuzzy inference system; fusing behaviours; mobile robot; Pioneer 2P; unknown environment; temporal difference; reinforcement learning.

DOI: 10.1504/IJESMS.2019.101670

International Journal of Engineering Systems Modelling and Simulation, 2019 Vol.11 No.2, pp.50 - 59

Accepted: 02 Mar 2019
Published online: 15 Aug 2019 *

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