During the past decades, industrial robot arms have been widely adopted in various fields, like aerospace and medical care. However, an uncalibrated industrial robot arm suffers from its high absolute positioning error, which tremendously restricts its application in high-precision intelligent manufacture. Related robot arm calibration methods present a potential solution to this issue, while recent algorithms frequently encounter some issues, such as long-tail convergence and low calibration accuracy. To address this thorny issue, this study proposes a novel robot arm calibration method incorporating the extended Kalman filter with Quadratic Interpolated Beetle Antennae Search algorithm. It adopts three-fold ideas: a) developing a new Quadratic Interpolated Beetle Antennae Search algorithm that greatly addresses the issue of local optimum and low convergence rate in a Beetle Antennae Search algorithm; b) adopting an extended Kalman filter algorithm to decrease the influence of measurement noises and c) proposing a robot arm calibration method incorporating an extended Kalman filter with Quadratic Interpolated Beetle Antennae Search algorithm to searching the optimal kinematic parameters of a robot arm. Extensive experiments on an ABB IRB120 industrial robot arm demonstrate that the calibration accuracy of the proposed method is 5.17% higher than that of the state-of-the-art method. Therefore, it is appropriate for practical application occasions with high-precision requirements.

中文翻译：

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使用二次插值甲虫天线搜索来提高机器人手臂校准精度


在过去的几十年里，工业机器人手臂已广泛应用于航空航天、医疗保健等各个领域。然而，未经标定的工业机器人手臂绝对定位误差较大，极大地限制了其在高精度智能制造中的应用。相关的机械臂标定方法为这一问题提供了潜在的解决方案，而最近的算法经常遇到一些问题，例如长尾收敛和标定精度低。为了解决这个棘手的问题，本研究提出了一种新颖的机器人臂校准方法，结合了扩展卡尔曼滤波器和二次插值甲虫天线搜索算法。它采用了三重思想：a）开发了一种新的二次插值甲虫天线搜索算法，极大地解决了甲虫天线搜索算法中的局部最优和收敛速度低的问题； b）采用扩展卡尔曼滤波器算法来减少测量噪声的影响；c）提出一种结合扩展卡尔曼滤波器和二次插值甲虫天线搜索算法的机器人臂标定方法，以搜索机器人臂的最佳运动学参数。在 ABB IRB120 工业机器人手臂上进行的大量实验表明，该方法的标定精度比现有方法高 5.17%。因此，适合于精度要求较高的实际应用场合。