Real-time phase-based stereo for a mobile robot

The performance of a mobile robot crucially depends on the accuracy, duration and reliability of its sensor interpretation. A major source of information are CCD-cameras which provide a detailed view of the robot's environment. This paper presents a real-time stereo algorithm implemented on the mobile robot RHINO of the University of Bonn. The algorithm exploit the phases of wavelet-filtered image pairs to localize edges and to estimate their disparities with subpixel accuracy. The disparities are computed by an initial search for corresponding points within a given interval and a subsequent measurement of phase-differences. The real-time constraints of autonomous object detection and navigation are fulfilled by partially implementing the stereo algorithm on a pipeline computer Datacube. Experimental results on real world scenes under real world conditions demonstrate the stereo algorithm's robustness and suitability for autonomous robot applications.