基于卡尔曼滤波器的图像雅克比在线估计

Online Estimation of the Image Jacobian Matrix Based on the Kalman Filter

提出一种估计图像雅克比的方法,即构建辅助动态系统,其状态变量由图像雅克比矩阵元素构成。用卡尔曼滤波器在线观察辅助系统状态,因此获得的图像雅克比具有很强的鲁棒性。以一个无标定视觉反馈机械手的二维跟踪任务为例,介绍辅助系统的构成,图像雅克比的估计和伺服控制器的设计。仿真实验表明了所提方法的有效性和跟踪过程的满意度。

The linear image Jacobian matrix is used to describe the differential movement relation between the image space and the robotic workspace. This paper proposes a method to estimate the image Jacobian matrix,that is to construct an instrumental dynamic system with the state variables formed from elements of the image Jacobian matrix.The Kalman filter is used to observe the system states online. Thus the obtained image Jacobian matrix is robustly. A 2D tracking task by a robot manipulator with visual feedback from uncalibrated cameras is exemplified to show the formation of the instrumental system,the estimation process of the image Jacobian matrix and the design of the servo controller. The effectiveness of the proposed method and satisfactory tracking process can be found from the simulation experiment.