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.