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About this paper
Keyhan Rayati, AliReza Beigy, Anoosheh Saadati, Pourya Shahverdi, Mehdi Tale Masouleh, Ahmad Kalhor, Wing-Yue Geoffrey Louie
The authors present a framework for teaching a NAO humanoid manipulation from demonstrations. It extracts object locations, human arm configuration, and task progress, then uses a temporal model to predict robot arm movements. In simulation it placed a red ball in a green box, achieving success rates of 78% with 16 demonstrations and 86% with 100, limited to this task.
Summary by alphaXiv.
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