Cooperative Multi-robot Target Tracking

Target tracking performance can be improved by using multiple robot trackers, but this requires a coordinated motion strategy among the robots. We propose an algorithm based on treating the densities of robots and targets as properties of the environment in which they are embedded. By suitably manipulating these densities a control law for each robot is proposed. The proposed algorithm has been tested through intensive simulations and a realrobot experiment. First, two different versions of the approach were evaluated by studying the performance change as the communication range among robots varies. The results showed that our treatment of the coordination problem is effective and efficient. Second, the developed system was tested on two Segway RMP robots, and the behaviors of the robots in a cooperative tracking experiment provide evidence that the proposed method controls multiple robots appropriately according to the target distribution change.

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