An ANFIS-based multi-sensor structure for a mobile robotic system

Abstract

The control of a nonlinear system is a challenging problem particularly when the system has some uncertainty or there are imperfections in the model dynamics. One approach that has gained some success employs a fuzzy structure in concert with a neural network (ANFIS); the fuzzy component compensates for the uncertainty while the neural network component models the underlying system dynamics. This paper presents a system architecture for a mobile robotic system that employs an ANFIS controller for path tracking, a virtual field strategy for obstacle avoidance and path planning, and multiple sensors (an ultrasonic array, a thermal sensor, and a video streaming system) to obtain information about the environment. Simulation results and preliminary evaluation show that the proposed architecture is a feasible one for autonomous mobile robotic systems.