Adaptive Jacobian vision based control for robots with uncertain depth information
Adaptive Jacobian vision based control for robots with uncertain depth information
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DOI：
10.1016/j.automatica.2010.04.009
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发表时间：
2010-07
期刊：
影响因子：
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通讯作者：
C. Cheah;Chao Liu;J. Slotine
中科院分区：
文献类型：
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作者：
C. Cheah;Chao Liu;J. Slotine
本文提出了一种简单的基于视觉的设定点控制器，适应深度信息的不确定性。深度不确定性在基于视觉的控制中起着特殊的作用，因为它在整个雅可比矩阵中呈现非线性，因此不能与其他不确定的运动参数一起适应。我们提出了一种新的参数更新法来更新深度的不确定参数。证明了在深度信息、机器人运动学和动力学存在不确定性的情况下，系统的稳定性是可以保证的。仿真结果说明了所提出的控制器的性能。
This paper presents a simple vision based setpoint controller with adaptation to uncertainty in depth information. Depth uncertainty plays a special role in vision based control as it appears nonlinearly in the overall Jacobian matrix and hence cannot be adapted together with other uncertain kinematic parameters. We propose a novel parameter update law to update the uncertain parameters of the depth. It is proved that system stability can be guaranteed for the vision regulation task in presence of uncertainties in depth information, robot kinematics and dynamics. Simulation results are presented to illustrate the performance of the proposed controller.