Tracking a Planar Target Using Image-Based Visual Servoing Technique

In this paper, we design and validate a kinematic controller for a quadrotor tracking a planar moving target using image-based visual servoing (IBVS). Most of the current literature on IBVS for moving targets often consider restrictive assumptions on the target dynamics that limits its generalizability for any arbitrary motion. We propose a model-free target velocity estimator augmented kinematic controller based on appropriately derived feature dynamics in a virtual image plane. We show how the inner-loop mismatch affects the kinematic controller performance through a comprehensive theoretical analysis based on the Lyapunov direct method. We prove that the system errors converge exponentially to an ultimate bound in general and asymptotically to zero for the purely translational and constant target motions and vanishing inner-loop mismatch. Extensive simulations, including model-in-the-loop and software-in-the-loop settings, along with experimental validation in an outdoor environment, confirm the utility of the proposed visual servoing technique.