Industrial robots play a vital role in automatic production, which have been widely utilized in industrial production activities, like handling and welding. However, due to an uncalibrated robot with machining tolerance and assembly tolerance, it suffers from low absolute positioning accuracy, which cannot satisfy the requirements of high-precision manufacture. To address this hot issue, we propose a novel calibration method based on an unscented Kalman filter and variable step-size Levenberg-Marquardt algorithm. This work has three ideas: a) proposing a novel variable step-size Levenberg-Marquardt algorithm to addresses the issue of local optimum in a Levenberg-Marquardt algorithm; b) employing an unscented Kalman filter to reduce the influence of the measurement noises; and c) developing a novel calibration method incorporating an unscented Kalman filter with a variable step-size Levenberg-Marquardt algorithm. Furthermore, we conduct enough experiments on an ABB IRB 120 industrial robot. From the experimental results, the proposed method achieves much higher calibration accuracy than some state-of-the-art calibration methods. Hence, this work is an important milestone in the field of robot calibration.

中文翻译：

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基于步长Levenberg-Marquardt算法的工业机器人标定新方法

工业机器人在自动化生产中发挥着至关重要的作用，已广泛应用于工业生产活动，如搬运和焊接。但由于机械手未经标定，存在加工公差和装配公差，存在绝对定位精度低的问题，无法满足高精度制造的要求。为了解决这个热点问题，我们提出了一种基于无迹卡尔曼滤波器和可变步长 Levenberg-Marquardt 算法的新型校准方法。这项工作有三个想法： a) 提出一种新颖的可变步长 Levenberg-Marquardt 算法来解决 Levenberg-Marquardt 算法中的局部最优问题；b) 采用无迹卡尔曼滤波器来减少测量噪声的影响；c) 开发一种新的校准方法，将无迹卡尔曼滤波器与可变步长 Levenberg-Marquardt 算法结合起来。此外，我们在 ABB IRB 120 工业机器人上进行了足够的实验。从实验结果来看，所提出的方法比一些最先进的校准方法实现了更高的校准精度。因此，这项工作是机器人校准领域的一个重要里程碑。