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cs.RO2024
Bi-Level Motion Imitation for Humanoid Robots
Wenshuai Zhao, Yi Zhao, Joni Pajarinen +1
Imitation learning from human motion capture (MoCap) data provides a promising way to train humanoid robots. However, due to differences in morphology, such as varying degrees of j…
cs.RO2024
RP1M: A Large-Scale Motion Dataset for Piano Playing with Bi-Manual Dexterous Robot Hands
Yi Zhao, Le Chen, Jan Schneider +5
It has been a long-standing research goal to endow robot hands with human-level dexterity. Bi-manual robot piano playing constitutes a task that combines challenges from dynamic ta…
cs.LG2024
iQRL -- Implicitly Quantized Representations for Sample-efficient Reinforcement Learning
Aidan Scannell, Kalle Kujanpää, Yi Zhao +3
Learning representations for reinforcement learning (RL) has shown much promise for continuous control. We propose an efficient representation learning method using only a self-sup…