基于随机Levenberg-Marquardt算法的平面三角机器人运动模型辨识

Jinbo Shi, Chun-jian Yu, Zexiang Li
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引用次数: 2

摘要

精确的运动学模型是高性能机械臂的基本要求之一。但由于公差和间隙的存在,必须首先进行标定,以确定运动模型的不准确性并进一步修改。本文详细介绍了平面并联机器人的标定工作。提出了一种新颖的求解非线性优化问题的算法,称为Random-Levenberg-Marquardt算法。通过具体的说明和实际的实验结果,与传统方法相比,该算法具有高效、准确和易于实现的特点。
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Kinematic model identification of planar delta manipulator using Random Levenberg-Marquardt algorithm
An accurate kinematic model is one of the fundamental requirements of high performance robotic manipulators. But due to the existence of tolerance and clearance, calibration should be always carried out first of all to identify the inaccuracy and further modification of the kinematic model. In this paper, the calibration work of a planar parallel manipulator was presented in details. And an innovative algorithm to solve the nonlinear optimization problem was proposed, which's named “Random-Levenberg-Marquardt” algorithm. With specific illustration and practical experiment result, this algorithm was proved to be efficient, accurate and easily implementable comparing to the traditional methods.
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