Calibration of Stewart-Gough Parallel Robot with Minimum Sensor and Position Control in Joint Space

Hamed Navvabi, Behnam Hosseinkhani, Farbood Shokouhi, Amir Hossein Davaei Markazi
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Abstract

The Stewart-Gough Platform (SGP) is defined as a 6-DOF parallel robot. It consists of two rigid plates; moving platform (MP) in top and base platform (BP) in bottom and also six actuating links that connect them to each other and provide up to six DOF for the MP with respect to the BP. SGP's impressive features are high load carrying capacity, low inertia, high stiffness, better repetition and precise positioning. This paper focuses on the accuracy enhancement of a six DOF SGP robot through kinematic calibration. In this method minimum number of sensors have been used for SGP kinematic calibration. This method is presented with details and is implemented on an experimental robot. The assumption of the methodology is that the orientation of MP can be measured by two inclinometers. Calibration involves of a nonlinear function optimization with 36 unknown parameters. Nonlinear least square scheme is used for the optimization. Experimental studies reveal that the proposed method is effective in enhancing the SGP accuracy. The main contribution of this work is implementation of the proposed method on an experimental robot and achievement acceptable results by position control of SGP in joint space. The robot position is controlled in the joint space; results show that calibrated robot follows command signal more accurate than before the calibration.
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最小传感器与关节空间位置控制Stewart-Gough并联机器人标定
Stewart-Gough平台(SGP)是一种六自由度并联机器人。它由两块刚性板组成;移动平台(MP)在顶部,基础平台(BP)在底部,还有6个驱动链接将它们相互连接,并为MP相对于BP提供多达6个自由度。SGP令人印象深刻的特点是高承载能力,低惯性,高刚度,更好的重复和精确定位。本文研究了通过运动学标定提高六自由度SGP机器人精度的方法。该方法采用最小的传感器数量进行SGP的运动学标定。详细介绍了该方法,并在实验机器人上进行了实现。该方法的假设是MP的取向可以用两个测斜仪测量。校正涉及一个包含36个未知参数的非线性函数优化。采用非线性最小二乘格式进行优化。实验研究表明,该方法能有效提高SGP的精度。本工作的主要贡献是在实验机器人上实现了该方法,并通过关节空间的SGP位置控制获得了可接受的结果。在关节空间中控制机器人的位置;结果表明,标定后的机器人对指令信号的跟踪精度比标定前提高了。
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