Cooperative active target tracking for heterogeneous robots with application to gait monitoring

This paper proposes a new cooperative active target-tracking strategy for a team of heterogeneous robots equipped with 3-D range-finding sensors. Our strategy is active, in the sense that the robots will track one or multiple moving targets while minimizing the combined uncertainty about the targets' position. We introduce a gradient-based control approach that encompasses the three major optimum experimental design criteria and relies only on robots' relative position measurements. The Kalman-Bucy filter is used for estimation fusion. Applications of the proposed strategy are shown to an experimental scenario featuring a team of double-integrator aerial vehicles and nonholonomic ground robots cooperatively tracking the motion of a human subject for a gait-monitoring task.