Vision-based UAV adaptive tracking control for moving targets with velocity observation

Abstract

An adaptive image-based visual servoing (IBVS) controller is designed for a quadrotor unmanned aerial vehicle (UAV) to achieve robust tracking for moving targets, under underactuation and tight coupling constraints of UAV kinematics. Specifically, image features are selected from perspective image moments of a planar target to obtain virtual feature dynamics regarding UAV kinematics and dynamics. By constructing an auxiliary variable, a translational velocity observer for moving target is constructed by using virtual image features. An IBVS tracking controller is designed without target geometric information by combining UAV and visual feature dynamics. Designed controller and observer make the UAV robustly reach desired height and track the moving target, despite uncertainty of target movement. The controller has asymptotical convergence performance, and the target velocity is observed according to Lyapunov stability analysis. Simulation and experimental results show that the proposed method has smoother and more accurate performance in motion tracking and target velocity prediction under system uncertainty.