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Comparison of trajectory parametrization methods with statistical analysis for dynamic parameter identification of serial robot

机译:轨迹参数化方法对串行机器人动态参数识别的统计分析

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This paper introduces an approach for designing exciting trajectories for parameter identification of serial robots based on a combination of Fourier Series (FS) and Schroeder Phased Harmonic Sequence (SPHS). An initial estimation of the trajectory is designed for each link using SPHS. Afterwards, the initial trajectory enable to find the initial parameters of the FS which are fed to an optimization process that finds the optimal parameters of the FS used for identification purpose. Like this, we can take the advantages of both FS and SPHS and eliminate the disadvantages of each of them. Moreover, a comparison of results between; the proposed method, original FS, and SPHS is taking place to demonstrate the effectiveness of the new approach. In this vein, a one-way analysis of variance is conducted to compare whether there are significant improvement or not. An PA10 7DoF arm robot serves as test bed for conducting experiments. Findings shows that the optimal trajectory found through the proposed approach requires less computation time compared to original FS which can be an advantage for fast and robust identification.
机译:本文介绍了一种基于傅里叶系列(FS)和施罗德分阶段谐波序列(SPHS)的组合来设计串行机器人参数识别令人兴奋轨迹的方法。轨迹的初始估计是针对使用SPHS的每个链路设计的。之后,初始轨迹使能找到FS的初始参数,该参数被馈送到找到用于识别目的的FS的最佳参数的优化过程。像这样,我们可以采取FS和SPH的优势并消除每个人的缺点。而且,结果比较;提出的方法,原始FS和SPHS正在展示新方法的有效性。在该静脉中,进行单向分析,以比较是否存在显着改善。 PA10 7DOF ARM机器人用作用于进行实验的试验台。调查结果表明,通过所提出的方法发现的最佳轨迹需要与原始FS相比的计算时间较少,这对于用于快速和鲁棒识别的优势。

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