Adaptive visual servoing of autonomous helicopters

This paper presents a novel adaptive controller for image-based dynamic control of autonomous helicopter using an on-board camera. We assume that the intrinsic and extrinsic parameters of the camera and the geometric information of the features are unknown. The controller is developed based on two key ideas. First, we employ the depth-independent interaction matrices for autonomous helicopters to map the image error so that the close-loop dynamics can be linearly parameterized by the unknown camera parameters and 3-D coordinates of the point features. Second, we define an error vector that is linear to the unknown parameters and propose an adaptive algorithm for on-line estimation of the unknown parameters using an idea similar to the structure from motion method in Computer Vision. Then, a simple controller is proposed for regulating the image of the features to desired values. The Lyapunov method is used to prove the asymptotic convergence of the image error based on the nonlinear dynamics of the helicopter. Finally, simulations have been conducted to demonstrate the performance of the proposed method.