基于神经网络补偿的稳定视觉伺服

Proceeding of the 2001 IEEE International Symposium on Intelligent Control (ISIC '01) (Cat. No.01CH37206) Pub Date : 2001-09-05 DOI:10.1109/ISIC.2001.971505

G. Loreto, Wen Yu, R. Garrido

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引用次数: 9

摘要

提出了一种稳定的平面机器人视觉伺服算法。我们假设重力和摩擦力是未知的，并且在视觉系统中存在建模误差。利用径向基函数神经网络，证明了这些不确定性是可以补偿的。证明了在没有或没有建模动力学的情况下，具有神经网络补偿的二维视觉伺服系统是李雅普诺夫稳定的。

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Stable visual servoing with neural network compensation

We propose a stable 2D visual servoing algorithm for planar robot manipulators. We assume that gravity and friction are unknown and that there exists modeling errors in the vision system. By using a radial basis function neural network, it is shown that these uncertainties can be compensated. We prove that without or with unmodeled dynamics, the 2D visual servoing with neural networks compensation is Lyapunov stable.

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Proceeding of the 2001 IEEE International Symposium on Intelligent Control (ISIC '01) (Cat. No.01CH37206)

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