Multiscale observation of multiple moving targets using Micro Aerial Vehicles

Abstract

This paper presents a centralized algorithm for multi-scale observation of multiple moving targets using a team of Micro Aerial Vehicles (MAVs). The proposed algorithm is appropriate when MAVs can observe targets at different elevations with the objective of jointly maximizing duration and resolution of observation for each target. The MAVs share the workload using a greedy assignment of locations and targets to MAVs. The proposed algorithm uses a quad-tree data structure to model the movement decisions of MAVs as well as the variable qualities (resolutions) of observations. We consider cases where there is uncertainty in the target observations (i.e., measurement noise), the number of targets is larger than that of the MAVs and the combined field of views (FOVs) of the sensors cannot cover the whole search region. Simulation results confirm the effectiveness of the proposed algorithm.