Distributed cooperative control for joint optimization of sensor coverage and target tracking

This paper presents two approaches considering a distributed framework for joint optimization of sensor coverage for target detection and target tracking for maximizing estimation performance for multi-agent systems. The first algorithm is based on the Lloyd algorithm, which uses a centroid of Voronoi partitions, one of the workarounds of sensor coverage problems. The other algorithm is based on the Voronoi partition, which is the result of assigning the target to the agent considering the control input that maximizes the information matrix corresponding to the state estimate of the target. Two presented algorithms are compared and analyzed in terms of target state estimation errors through a series of simulations. The simulation results show that the Voronoi partition-based target tracking approach performs better than Lloyd's algorithm-based approach in terms of sensor coverages and estimation error of targets.