Robust 3-D landmark tracking using trinocular vision

Position determination and verification of a mobile robot is a central theme in robotics research. Several methods have been proposed for this problem, including the use of visual feedback information. These vision systems typically aim to extract known or tracked landmarks from the environment to localise the robot. Detection and matching these landmarks is often the most computationally expensive and error prone component of the system. This paper presents a real-time system for robustly matching landmarks in complex. scenes, with subsequent tracking. The vision system comprises of a trinocular head, from which corner points are extracted. These are then matched with respect to robustness constraints in addition to the trinocular constraints. Finally, the resulting robustly extracted corners are tracked from frame to frame to determine the robot's rotational deviations.