Cooperative Target Tracking Control of Multiple Robots

This paper focuses on the problem of moving target tracking with a group of mobile robots. Each robot in the group has a pan/tilt camera to detect the target and has limited communication capability to communicate with neighbor robots. The problem is solved by separating it into two parts. One part is the estimation of target position and another is the flocking control of multiple robots moving toward the estimated position. In the target estimation part, we propose to use a novel distributed Kalman filter to estimate the target position. The distributed Kalman filter is deduced based on a standard Kalman filter by modeling the neighbor's information as one of measurements. In the motion control part, a distributed flocking algorithm is developed. It is used to track the estimated target and avoid collision. In both parts, only local communication between neighbor robots is required. Finally, the tracking algorithms are simulated with 2-D and 3-D robots to verify their performance. The simulation results provide a firm conclusion that the proposed algorithms are able to track a moving target. A group of real ground mobile robots is used to test the proposed algorithm. The experiment results show that multiple robots are able to cooperate to track the target under the proposed algorithms and the tracking result outperforms the result produced by individual robots without cooperation.