论文标题
一种基于步进大小的Levenberg-Marquardt算法的工业机器人的新校准方法
A New Calibration Method for Industrial Robot Based on Step-Size Levenberg-Marquardt Algorithm
论文作者
论文摘要
工业机器人在自动生产中起着至关重要的作用，该生产已在工业生产活动中广泛使用，例如处理和焊接。但是，由于未校准的机器人具有加工耐受性和组装耐受性，因此它的绝对定位精度较低，无法满足高精度制造的要求。为了解决这个热门问题，我们提出了一种基于无味的卡尔曼过滤器和变量尺寸的levenberg-marquardt算法的新型校准方法。这项工作有三个想法：a）提出一种新颖的变量尺寸的levenberg-marquardt算法，以解决Levenberg-Marquardt算法中本地最佳的问题； b）使用无气味的卡尔曼过滤器来减少测量噪声的影响； c）开发一种新型的校准方法，该方法结合了带有变量尺寸的levenberg-marquardt算法的无气体滤波器。此外，我们对ABB IRB 120工业机器人进行了足够的实验。从实验结果中，提出的方法比某些最新的校准方法获得了更高的校准精度。因此，这项工作是机器人校准领域的重要里程碑。
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.
