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Motion Segmentation and Recognition for Imitation Learning and Influence of Bias for Learning Walking Motion of Humanoid Robot Based on Human Demonstrated Motion

机译:基于人体运动的仿人学习运动分割与识别及仿人机器人学习行走运动偏差的影响

摘要

Two main issues arise in practical imitation learningby humanoid robots observing human behavior –the first is segmenting and recognizing motion demonstratednaturally by a human beings and the second isutilizing the demonstrated motion for imitation learning.Specifically, the first involves motion segmentationand recognition based on the humanoid robotmotion repertoire for imitation learning and the secondintroduces learning bias based on demonstratedmotion in the humanoid robot’s imitation learning towalk. We show the validity of our motion segmentationand recognition in a practical way and report theresults of our investigation in the influence of learningbias in humanoid robot simulations.
机译:在仿人机器人观察人类行为的实际模仿学习中,出现了两个主要问题:第一个是对人类自然演示的运动进行分段和识别,第二个是将演示的运动用于模仿学习。具体来说,第一个涉及基于仿人机器人的运动库来进行运动分割和识别,以进行模仿学习;第二个则是基于仿人机器人的模仿行走学习中所演示的运动来引入学习偏差。我们以一种实用的方式展示了运动分割和识别的有效性,并报告了研究结果对人形机器人仿真中学习偏差的影响。

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