Dynamic Visual Tracking for Manipulators Using an Uncalibrated Fixed Camera
Dynamic Visual Tracking for Manipulators Using an Uncalibrated Fixed Camera
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DOI：
10.1109/tro.2007.895091
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发表时间：
2007-06
影响因子：
7.8
通讯作者：
Hesheng Wang;Yunhui Liu;Dongxiang Zhou
中科院分区：
文献类型：
--
作者：
Hesheng Wang;Yunhui Liu;Dongxiang Zhou
本文提出了一种新的控制器，用于控制机器人操作器上的一些特征点跟踪指定的固定摄像机的图像平面上的期望轨迹。假设摄像机的内、外参数未标定。在三个创新思想的基础上，提出了一种新的自适应在线估计未知参数的算法。首先，我们使用深度无关的相互作用矩阵的伪逆映射到机械手的关节空间的图像误差。通过消除相互作用矩阵中的深度，我们可以线性地参数化机械手的闭环动力学。其次，为了保证伪逆的存在性，自适应算法引入了一个势力来驱动估计参数远离导致奇异雅可比矩阵的值。第三，为了确保估计的参数收敛到它们的真实值的规模，我们结合联合收割机的Slotine-Li方法与在线算法，以最大限度地减少估计的投影和真实的图像坐标的特征点之间的误差。我们已经证明了渐近收敛到零的图像误差的李雅普诺夫理论的基础上的非线性机器人动力学。实验已经进行了验证所提出的控制器的性能。
This paper presents a new controller for controlling a number of feature points on a robot manipulator to trace desired trajectories specified on the image plane of a fixed camera. It is assumed that the intrinsic and extrinsic parameters of the camera are not calibrated. A new adaptive algorithm is developed to estimate the unknown parameters online, based on three original ideas. First, we use the pseudoinverse of the depth-independent interaction matrix to map the image errors onto the joint space of the manipulator. By eliminating the depths in the interaction matrix, we can linearly parameterize the closed-loop dynamics of the manipulator. Second, to guarantee the existence of the pseudoinverse, the adaptive algorithm introduces a potential force to drive the estimated parameters away from the values that result in a singular Jacobian matrix. Third, to ensure that the estimated parameters are convergent to their true values up to a scale, we combine the Slotine-Li method with an online algorithm for minimizing the error between the estimated projections and real image coordinates of the feature points. We have proved asymptotic convergence of the image errors to zero by the Lyapunov theory based on the nonlinear robot dynamics. Experiments have been carried out to verify the performance of the proposed controller.