基于神经网络的RSRR轮毂逆运动学研究

J. Flores, H. Moreno, I. Carrera, M. A. Garcia, Roberto G. Adan
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引用次数: 0

摘要

RSRR HeIse wheel是一种可以将圆轮转变为多肢混合轮的二自由度机构。求解该机构的逆运动学需要求解具有多个解的非线性方程组。为了找到一种有效的在线计算逆运动学的算法,在这项工作中,我们探索使用人工神经网络。利用正运动学的解析解生成神经网络训练数据集。对不同结构的网络进行了测试,并讨论了它们在准确率方面的性能。利用所建立的模型进行了仿真,结果表明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Inverse Kinematics of a RSRR HeIse wheel using Neural Networks
The RSRR HeIse wheel is a 2 DOF mechanism that can transform a circular wheel into a hybrid wheel with multiple limbs. Solving the inverse kinematics of this mechanism requires solving a system of non-linear equations with multiple solutions. In order to find an efficient algorithm for on-line computation of the inverse kinematics, in this work we explore the use of artificial neural networks. The analytical solution of forward kinematics is used to generate the data set for the neural networks training. Different structures of networks are tested and their performance in terms of accuracy is discussed. The results of a simulation using the obtained model shows the efficacy of this method.
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