R+X: Retrieval and Execution from Everyday Human Videos
<|reference_start|>R+X: Retrieval and Execution from Everyday Human Videos: We present R+X, a framework which enables robots to learn skills from long, unlabelled, first-person videos of humans performing everyday tasks. Given a language command from a human, R+X first retrieves short video clips containing relevant behaviour, and then executes the skill by conditioning an in-context imitation learning method on this behaviour. By leveraging a Vision Language Model (VLM) for retrieval, R+X does not require any manual annotation of the videos, and by leveraging in-context learning for execution, robots can perform commanded skills immediately, without requiring a period of training on the retrieved videos. Experiments studying a range of everyday household tasks show that R+X succeeds at translating unlabelled human videos into robust robot skills, and that R+X outperforms several recent alternative methods. Videos are available at https://www.robot-learning.uk/r-plus-x.<|reference_end|>
@article{papagiannis2024r+x:,
    title={R+X: Retrieval and Execution from Everyday Human Videos},
    author={Georgios Papagiannis, Norman Di Palo, Pietro Vitiello, Edward Johns},
    journal={arXiv preprint arXiv:2407.12957},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.12957},
    primaryClass={cs.RO cs.LG}
}