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Choosing Measurement Configurations for Kinematic Calibration of Cable-Driven Parallel Robots

机译:选择测量配置以进行电缆驱动并联机器人的运动学校准

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For kinematic calibration of cable-driven parallel robots (CDPRs), many kinematic calibration methods have been proposed in the last decade. However, the established methods are mainly based on calibration with different models, whose robustness of observability index with respect to (w.r.t) sensor noise is not investigated. The observability index of the robot configurations can be maximized and the calibration accuracy will be improved by adequately choosing the measurement configurations. This paper proposes to calibrate the kinematic calibration of CDPRs by choosing measurement configurations, which can optimize the observability index and increase the calibration accuracy. The kinematic calibration model is formulated, and then a calibration method is designed to calculate the transformation matrix between the measuring-coordinate frame and the global coordinate frame. With these models, an efficient configuration choosing algorithm is proposed by using the DETMAX algorithm and the Tabu search algorithm. The proposed algorithm was validated by simulation experiments under several observability indices, and the results indicate that the robustness of the calibration method can be improved significantly by choosing configurations. With the theoretical geometric parameters and the selected measurement configurations, calibration experiments were performed on a redundant CDPR.
机译:对于电缆驱动并联机器人(CDPR)的运动学标定,最近十年提出了许多运动学标定方法。但是,已建立的方法主要基于不同模型的校准,因此未研究其可观察性指标相对于(w.r.t)传感器噪声的鲁棒性。机器人配置的可观测性指数可以被最大化并且校准精度将通过适当地选择测量配置被改善。本文建议通过选择测量配置来校准CDPR的运动学标定,这可以优化可观察性指标并提高标定精度。建立运动学标定模型,然后设计一种标定方法,计算出测量坐标系与全局坐标系之间的转换矩阵。利用这些模型,提出了一种有效的配置选择算法,该算法采用DETMAX算法和禁忌搜索算法。仿真实验在几种可观察性指标下对该算法进行了验证,结果表明,通过选择配置可以显着提高校准方法的鲁棒性。利用理论几何参数和选定的测量配置,对冗余CDPR进行了校准实验。

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