Abstract
This paper describes the sensor configuration and dynamic robust tracking algorithm for a mobile robot capable of following a walking human in 2D space. Since the back shape of a walking human is not constant as that of a vehicle would be, it is difficult to identify the human solely by vision sensor and image signal processing. Here, we employ a sensor fusion technique and combine an omni-directional camera and a laser rangefinder to solve this problem and achieve stable tracking and following ability.An omni-directional camera is used for robust image acquisition and processing, and a 2D laser rangefinder is used for environmental recognition by detecting obstacles. We present the advanced sensor fusion technique of the omni-directional camera and laser rangefinder, which yields dynamic range-adjusting tracking, avoidance of collision and stable human tracking. The Kalman filter based on multi-rate sensor fusion theory is employed to make the system functional. Human tracking necessarily involves the problem of short-cut passing of human following trajectory. In order to avoid the short-cut problem, we adopted a path-tracking algorithm to generate a trajectory as similar as possible to that of a walking human. The path-tracking algorithm calculates the trajectory to be passed from the target position and the direction, and a control signal is generated based on the calculated trajectory.
