Mobile robot Bayesian map building based on laser ranging and stereovision

In this paper, an effective map building approach based on range data from binocular stereo vision sensor and Laser Range Finder is introduced in detail. First of all, a local map temporal integration approach in which Bayesian filter based dynamic occupancy grid map modeling technique is employed to reasonably deal with measurement uncertainty involved in environment perception. In addition, as stereo vision is unreliable for building map autonomously and individually, an effective combination approach is proposed for fusing local stereo data derived map and laser range data derive map together and producing a reliable spatial model for robot path planning or obstacle avoidance. Advantages of our proposal are validated by real experimental results carried on Pioneer robot.