Real-Time Combinatorial Tracking of a Target Moving Unpredictably among Obstacles

Many applications require continuous monitoring of a moving target by a controllable vision system. Although the goal of tracking objects is not new, traditional techniques usually ignore the presence of obstacles and focus on imaging and target recognition issues. For a target moving among obstacles, the goal of tracking involves a complex motion problem: a controllable observer (e.g., a robot) must anticipate that the target may become occluded by an obstacle and move to prevent such an event from occurring. This paper describes a strategy for computing the motions of a mobile robot operating in a 2-D workspace without prior knowledge of the target’s intention or the distribution of obstacles in the scene. The proposed algorithm governs the motion of the observer based on current measurements of the target’s position and the location of the local obstacles. The approach is combinatorial in the sense that the algorithm explicitly computes a description of the geometric arrangement between the target and the observer’s visibility region produced by the local obstacles. The algorithm computes a continuous control law based on this description. The new tracking strategy has been implemented in a real-time