A Stereo Vision Based Target Tracking and Obstacle Avoidance

Abstract

Designing a visual tracking system to track an object is a complex task because a large amount of video data must be transmitted and processed in real time. In this study, a stereo vision system is used to acquire the 3D positions of the target, tracking can be achieved by applying the CAMSHIFT algorithm, then apply the fuzzy reasoning control to steer the mobile robot to follow the selected target and avoid the in-path obstacles. The adopted obstacle avoidance component is based on the Harris corner detection and the binocular stereo imaging, which performs the correspondence calculation. Therefore a depth map is created and showing the relative 3D distances of the detected substantial features to the robot, which provides the information of the in-path obstacles in front of the wheeled mobile robot. The designed visual tracking and servo system is less sensitive to lighting influences and thus performs more efficiently. Experimental results showed that the mobile robot vision system successfully finished the target-following task by avoiding obstacles.