微小无人直升机自适应视觉伺服

针对摄像机未标定和特征点坐标未知的情况, 本文提出一种新颖的基于图像的无人直升机自适应视觉伺服方法. 控制器是基于反推法设计的, 但是和已有的基于反推法的视觉伺服不同的是, 它利用与深度无关矩阵将图像误差映射到执行器空间, 从而可以避免估计特征点的深度. 这种设计方法可以线性化未知的摄像机参数和特征点坐标, 所以能方便地设计自适应算法来在线估计这些未知参数, 同时为了保证图像误差收敛和避免估计参数收敛至零解而引入了两个势函数. 利用Lyapunov方法证明了基于非线性动力学的控制器的稳定性, 并给出了仿真验证.

Adaptive Visual Servoing of a Small Scale Autonomous Helicopter

This paper presents a novel adaptive controller for image-based visual servoing of a small autonomous helicopter to cope with uncalibrated camera parameters and unknown 3-D geometry of the feature points. The controller is based on the backstepping technique, but its design differs from the existing backstepping-based methods because the controller maps the image errors onto the actuator space via a depth-independent interaction matrix to avoid estimation the depths of the feature points. The new design method makes it possible to linearly parameterize the closed-loop dynamics by the unknown camera parameters and coordinates of the feature points in the three dimensional space so that an adaptive algorithm can be developed to estimate the unknown parameters and coordinates on-line. Two potential functions are introduced in the controller to guarantee convergence of image errors and to avoid trivial solutions of the estimated parameters. The Lyapunov method is used to prove the asymptotic stability of the proposed controller based on the nonlinear dynamics of the helicopter. Simulations have been also conducted to demonstrate the performances of the proposed method.