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LOTUS: Continual Imitation Learning for Robot Manipulation Through Unsupervised Skill Discovery
March 13, 2024, 4:44 a.m. | Weikang Wan, Yifeng Zhu, Rutav Shah, Yuke Zhu
cs.LG updates on arXiv.org arxiv.org
Abstract: We introduce LOTUS, a continual imitation learning algorithm that empowers a physical robot to continuously and efficiently learn to solve new manipulation tasks throughout its lifespan. The core idea behind LOTUS is constructing an ever-growing skill library from a sequence of new tasks with a small number of human demonstrations. LOTUS starts with a continual skill discovery process using an open-vocabulary vision model, which extracts skills as recurring patterns presented in unsegmented demonstrations. Continual skill …
arxiv continual cs.cv cs.lg cs.ro discovery imitation learning lotus manipulation robot robot manipulation through type unsupervised
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