A distributed motion planning and distributed filtering approach for target tracking in mobile sensor networks

Abstract

AbstractThe paper studies the problem of tracking of a target by a multi-robot system assuming that the target's state vector is not directly measurable and has to be estimated by distributed filtering based on the target's cartesian coordinates and bearing measurements obtained by the individual mobile robots. The objective is to make the robots converge in a synchronized manner towards the target, while avoiding collisions between them and avoiding collisions with obstacles in the motion plane. To solve the overall problem, the following steps are followed: (i) distributed filtering, so as to obtain an accurate estimation of the target's state vector. This estimate provides the desirable state vector to be tracked by each one of the mobile robots, (ii) motion planning and control that enables convergence of the vehicles to the goal position and also maintains the cohesion of the vehicles swarm. The efficiency of the proposed distributed filtering and distributed motion planning scheme is tested through simulation experiments.