NMPC-based UAV 3D Target Tracking In The Presence Of Obstacles and Visibility Constraints

Persistent target tracking using fixed-wing unmanned aerial vehicles (UAVs) in urban areas is an important application. However, due to the kinematic constraints of the UAV coupled with the visibility obstruction due to terrain impose hard constraints on the UAV motion for persistent tracking. In this paper, we propose a nonlinear model predictive control (NMPC) based controller with a gimballed camera to persistently track a target on the ground. The controller determines the control commands for the UAV and the gimbal azimuth and elevation angles. Simulations results show that the proposed approach can efficiently track the target compared to the NMPC framework without gimbal.