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

机译:串行机器人动态参数辨识的轨迹参数化与统计分析方法比较

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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立叶级数(FS)和施罗德相谐波序列(SPHS)的组合设计用于设计串行机器人参数的励磁轨迹的方法。使用SPHS为每个链接设计了轨迹的初始估计。之后,初始轨迹能够找到FS的初始参数,然后将其输入到优化过程中,该优化过程将找到用于识别目的的FS的最佳参数。这样,我们可以同时利用FS和SPHS的优势,并消除它们各自的劣势。而且,结果之间的比较;建议的方法,原始FS和SPHS正在进行中,以证明新方法的有效性。在这种情况下,进行单向方差分析以比较是否有显着改善。 PA10 7DoF手臂机器人用作进行实验的测试台。研究结果表明,与原始的FS相比,通过所提出的方法找到的最佳轨迹需要更少的计算时间,这对于快速而可靠的识别是一个优势。

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