运动学习中阻抗知识与内部模型的可靠性

2021 10th International Congress on Advanced Applied Informatics (IIAI-AAI) Pub Date : 2021-07-01 DOI:10.1109/iiai-aai53430.2021.00106

António Oliveira Nzinga René, K. Okuhara, E. Domoto, Ryo Haruna

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引用次数: 0

摘要

本研究的重点是一种称为追踪运动的感知运动学习，这是一种追踪图形轮廓并创建追踪运动实验的学习形式。首先，利用卡尔曼滤波计算内部模型的置信水平。为了实现最佳运动，可以通过设置适当的参数来控制阻抗。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Impedance Knowledge and Reliability of Internal Model in Motor Learning

This study focuses on a type of perceptual-motor learning called tracing motion, a form of learning to trace a figure's contour and create a tracing motion experiment. First, the Kalman filter is applied to calculate the confidence level of the internal model. To achieve optimal motion, one can control the impedance, which is possible by setting appropriate parameters.

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2021 10th International Congress on Advanced Applied Informatics (IIAI-AAI)

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