Mobile Robot Obstacle Avoidance Algorithms Based on Information Fusion of Vision and Sonar

Abstract

In view of the problem of AS-R autonomous wheeled mobile robot obstacle avoidance, a rapid convergence of sonar and binocular stereovision sensor distance information in order to detect and avoid obstacle algorithm is proposed in this paper. The algorithm first uses binocular camera (CCD) to get three-dimensional image of the real environment, through the stereo matching and V-disparity method which is used to calculate disparity map, then obstacles is extracted by Hough lines detection algorithm, finally we will get information about obstacles and sonar return information with T-S fuzzy neural network fusion, then it will output walking controlled decisions. Experimental results proved that the algorithm is effective and practical.