Simultaneous Tracking of Multiple Ground Targets from a Multirotor Unmanned Aerial Vehicle

Abstract

An algorithm for simultaneous tracking of multiple ground targets by an unmanned aerial vehicle is presented. The algorithm is specifically tailored toward multirotor vehicles, and it consists of a particle filter to predict target motion, a reference trajectory generator, and a finite-horizon model predictive controller for trajectory tracking. Two versions of the algorithm are proposed: for a vehicle equipped with a gimbaled camera, and for a vehicle equipped with a fixed camera. Furthermore, a target rejection algorithm is included to prune targets that inhibit accurate tracking of the majority of the target set. The tracking algorithm and multirotor vehicle dynamic model are first described, followed by example simulations for both the gimbaled and fixed-camera cases. Trade studies are presented, analyzing the effects of controller tuning parameters and camera field of view, as well as performance of the target rejection algorithm. In simulation experiments, real-world target data are used to improve simulation fidelity. Overall, results show that the algorithm is effective in capturing a set of ground targets within the field of view simultaneously when using either gimbaled or fixed-camera configurations, but performance is somewhat degraded in the fixed-camera case when target dynamics occur on timescales similar to tracking vehicle dynamics.