Real-time omnidirectional stereo for obstacle detection and tracking in dynamic environments

This paper describes a real-time omnidirectional stereo system and its application to obstacle detection and tracking for a mobile robot. The stereo system uses two omnidirectional cameras aligned vertically. The images from the cameras are converted into panoramic images, which are then examined for stereo matching along vertical epipolar lines. A PC cluster system composed of 6 PCs can generate omnidirectional range data of 720×100 pixels with disparity range of 80 (about 5 frames per second). For obstacle detection, a map of static obstacles is first generated. The candidates for moving obstacles are then extracted by comparing the current observation with the map. The temporal correspondence between the candidates are established based on their estimated position and velocity which are calculated using Kalman filter-based tracking. Experimental results for a real scene are described