Autonomous search and tracking of objects using model predictive control of unmanned aerial vehicle and gimbal: Hardware-in-the-loop simulation of payload and avionics

This paper describes the design of model predictive control (MPC) for an unmanned aerial vehicle (UAV) used to track objects of interest identified by a real-time camera vision (CV) module in a search and track (SAT) autonomous system. A fully functional UAV payload is introduced, which includes an infra-red (IR) camera installed in a two-axis gimbal system. Hardware-in-loop (HIL) simulations are performed to test the MPC's performance in the SAT system, where the gimbal attitude and the UAV's flight trajectory are optimized to place the object to be tracked in the center of the IR camera's image.(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works