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位置/力的自學習混合控制及其應用

Learning Hybrid Position/Force Control and Its Application

  • 摘要: 綜合了Raibert和Craig提出的機器人位置/力的Hybrid Control及Yoshikawa提出的機器人動態混合控制算法的基本思想,針對作業環境及其力學擾動難以辨識及機構振動等問題,提出了基于機器人裝配作業的PI自學習混合控制方法,并根據此方法實現了三自由度機器人的圓柱二維插入作業。實驗結果表明,該方法可以有效地實現機器人的銷孔裝配作業并抑制或緩沖機構的振動現象。

     

    Abstract: This paper combines the robot position/force hybrid control algorithm proposed by Raibert and Craig and the robot dynamic hybrid control algorithm proposed by Yoshikawa. Taking account of the difficulty to identify the environment, especially the effect of mechanical disturbance, and the vibrations of mechanism, a PI learning hybrid control algorithm for using robot to do assembly task was presented. This algorithm was realized in a peg insertion by a three DOF robot. The experiment results showed that this algorithm could effectly realize the peg-and-hole task, and restrain and weaken the vibrations of mechanism.

     

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