Particle filtering for people following behavior using laser scans and stereo vision

Mobile robots have a large application potential in everyday life. To build those applications some common and basic behaviors should be initially consolidated, including a people following behavior. In this paper a system able to follow a person based on information provided by a laser scan and a mono and stereo camera is presented. In order to accomplish this goal, a real-time particle filter system able to merge the information provided by the sensors (laser and 2D and 3D images) and calculate the position of the target is proposed, using probabilistic leg patterns, image features and optical flow to this end. The experiments carried out show promising results, allowing a real-time particle filtering based on two different information sources.