Motion Planning for 3-D Target Tracking among Obstacles

Summary

The goal of target tracking is to compute motion strategies for a robot equipped with visual sensors, so that it can effectively track a moving target despite obstruction by obstacles. It is an important problem with many applications in robotics. Existing work focuses mostly on the 2-D version of the problem, partly due to the complexity of dealing with 3-D visibility relationships. This paper proposes an online algorithm for 3-D target tracking among obstacles, using only local geometric information available to a robot’s visual sensors. Key to this new algorithm is the definition and efficient computation of a risk function, which tries to capture a target’s ability in escaping from the robot sensors’ visibility region in both short and long terms. The robot then moves to minimize this risk function locally in a greedy fashion. In the absence of occlusion by obstacles, the standard tracking algorithm based on visual servo control can be considered a special case of our algorithm. Experiments show that the new algorithm generated interesting tracking behaviors in three dimensions and performed substantially better than visual servo control in simulation.