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Robots learn new tasks while retaining old ones with Skill-Compositional Experts

Researchers have developed a new framework called SCE (Skill-Compositional Experts) to address catastrophic forgetting in embodied continual learning for robots. This framework decomposes task demonstrations into reusable skills, enabling robots to learn new manipulation tasks while retaining old ones. Experiments on LIBERO benchmarks and real-world tasks show that SCE significantly improves performance and retention. AI

RANK_REASON The cluster contains a research paper detailing a new framework for embodied continual learning. [lever_c_demoted from research: ic=1 ai=1.0]

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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Shuaike Zhang, Shaokun Wang, Haoyu Tang, Jianlong Wu, Liqiang Nie ·

    Learning New Tasks via Reusable Skills: Skill-Compositional Experts for Embodied Continual Learning

    arXiv:2606.15685v1 Announce Type: cross Abstract: Embodied Continual Learning (ECL) aims to enable robots to continually acquire new manipulation tasks while retaining previously learned behaviors under closed-loop control. Compared with conventional continual learning, ECL suffe…