A data-driven fuzzy approach to robot navigation among moving obstacles

Abstract

In this paper, a data-driven fuzzy approach is developed for solving the motion planning problem of a mobile robot in the presence of moving obstacles. The approach consists of using a recent data-driven fuzzy controller modeling algorithm, and a devised general method for the derivation of inputoutput data to construct a fuzzy logic controller off-line. The constructed FLC can then be used on-line by the robot to navigate among moving obstacles. The novelty in the presented approach, as compared to the most recent fuzzy ones, stems from its generality. That is, the devised data-derivation method enables the construction of a single FLC to accommodate a wide range of scenarios. Also, care has been taken to find optimal or near optimal FLC solution in the sense of leading to a sufficiently small robot travel time and collision-free path between the start and target points.