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Currently, robot learning of human activities is mainly studied in two largely disconnected domains: high level semantics understanding in human activity recognition, and low level motion trajectory reproduction in robot imitation learning. The critical problem of human activity unified learning (HAUL) was not well studied in previous work. One important challenge is the lack of a representation that...
Adaptation is an essential capability for intelligent robots to work in new environments. In the learning framework of Programming by Demonstration (PbD) and Reinforcement Learning (RL), a robot usually learns skills from a latent feature space obtained by dimension reduction techniques. Because the latent space is optimized for a specific environment during the training phase, it typically contains...
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