Abstract
It is necessary for a robot to have environmental information in order to move autonomously. Although we can usually give a map to the robot, making such a map is quite a tedious work. So we propose a navigation strategy which requires the minimum user assistance. In the method, we first guide a mobile robot to a destination. During this movement, the robot observes the surrounding environment to make a map. Once the map is generated, the robot computes and follows the shortest path to the destination. To realize this navigation strategy, we develop: (1) a method of map generation by integrating multiple observation results considering the uncertainties in observation and motion, and (2) a fast robot localization method which does not use explicit feature correspondence. We also propose an observation planning for efficient autonomous navigation, which takes advantage of human-guided experience. Experimental results using a real robot show the feasibility of the proposed strategy.
