Fuzzy decision mechanism combined with neuro-fuzzy controller for behavior based robot navigation

Abstract

This work describes the method to encode fuzzy sets, fuzzy rules and a procedure to perform fuzzy inference into an expert system for behavior based robot navigation. In this paper, we briefly present the design, coordination and fusion of the elementary behaviors for robot navigation using a fuzzy logic expert system. In this work the design of the behavior is based on regulatory control using fuzzy logic and the coordination and integration is defined by fuzzy rules, which define the context of applicability for each behavior. The complexity of robot behavior is reduced by breaking down robot behaviors into simple behaviors or units, and then combined with others to produce more complex actions. In this paper the decision making process of a few behaviors are illustrated specifically for an Active Media Pioneer Robot. The fuzzy logic decision mechanism, used here simplifies the design of the robotic controller and reduces the number of rules to be determined. The decision making process uses fuzzy logic for coordination, which provides a smooth transition between behaviors with a consequent smooth output response. In addition, the new behavior can be added or modified easily. Some of the experimental results are also shown for the obstacle avoidance, wall following and seek-goal behaviors.