Coverage-Aware Distributed Target Tracking for Mobile Sensor Networks

In this paper, we deal with the problem of distributed target tracking with heterogeneous mobile robots. We extend the static sensor network framework, presented by some of the authors in [1], introducing a cooperative motion control algorithm. In particular, each mobile node has limited sensing range and can estimate (either by measuring or by predicting) the target position. Then, a totally distributed algorithm exploits a suitable max-consensus protocol to reach a global agreement on the best estimate available in the network at a given time instant. The algorithm is based on the spread of a perception confidence value, locally computed by every single node and related to the Fisher Information, and requires a connected network to converge. Finally, a control law based on artificial potential fields allows the agents to move in order to improve the algorithm performance. In particular, the distributed motion control algorithm is capable to trade off between different requirements: to reduce the distance between the agent and the target to improve the accuracy of the measurement, to maintain the network connectivity, to perform collision avoidance, and to maintain a desidered coverage of the sensed area. Extensive simulation results are provided to confirm the suitability of the approach.