Recent algorithms for fuzzy and neurofuzzy path planning and navigation of autonomous mobile robots.

Abstract

This paper reviews a number of recent algorithms for mobile robot path planning, navigation and motion control, which employ fuzzy logic and neurofuzzy learning and reasoning. Starting with a discussion of the structure of fuzzy and neurofuzzy systems, two fuzzy obstacle avoidance path planning algorithms are presented followed by a 3-level neurofuzzy local and global path planning scheme. Then the motion planning and control problem is considered. A fuzzy path tracking strategy is outlined, followed by a fuzzy navigation algorithm among polygonal obstacles and a learning-by-doing neurofuzzy motion planning scheme. The paper ends with a hybrid robust motion control technique which combines the minimum interference and sliding mode control principles with fuzzy inference. A representative set of examples are included which illustrate the performance of the algorithms under various realistic conditions.