Visual algorithms for autonomous navigation

The Computer Vision Laboratory at the University of Maryland is designing and developing a vision system for autonomous ground navigation. Our approach to visual navigation segments the task into three levels called long range, intermediate range and short range navigation. At the long range, one would first generate a plan for the day´s outing, identifying the starting location, the goal, and a low resolution path for moving from the start to the goal. From time to time, during the course of the outing, one may want to establish his position with respect to the long range plan. This could be accomplished by visually identifying landmarks of known location, and then triangulating to determine current position. We describe a vision system for position determination that we have developed as part of this project. At the intermediate range, one would look ahead to determine generally safe directions of travel called corridors of free space. Short range navigation is the process that, based on a detailed topographic analysis of one´s immediate environment, enables us to safely navigate around obstacles in the current corridor of free space along a track of safe passage. We describe a quadtree based path planning algorithm which could serve as the basis for identifying such tracks of safe passage.