Adaptive IBVS Based Planar Non-Holonomic Target Tracking for Quadrotors

This paper presents an adaptive image-based visual servoing (IBVS) technique for a quadrotor to track a moving planar non-holonomic target with unknown constant body fixed linear velocity and arbitrary angular motion. We propose a novel target velocity estimator augmented kinematic controller based on appropriately derived feature dynamics in a virtual image plane. Through a comprehensive theoretical analysis based on the Lyapunov direct method, we prove the convergence of feature tracking errors to zero for translational kinematics and to an ultimate bound for rotational kinematics despite the unknown target motion and parameter uncertainty in desired feature depth. The theoretical claims are validated using model-in-the-loop and software-in-the-loop (SITL) simulations.