Lifelong Language-Conditioned Robotic Manipulation Learning
Traditional language-conditioned manipulation agent sequential adaptation to new manipulation skills leads to catastrophic forgetting of old skills, limiting dynamic scene practical deployment. In this paper, we propose SkillsCrafter, a novel robotic manipulation framework designed to continually learn multiple skills while reducing catastrophic forgetting of old skills. Specifically, we propose a Manipulation Skills Adaptation to retain the old skills knowledge while inheriting the shared knowledge between new and old skills to facilitate learning of new skills. Meanwhile, we perform the singular value decomposition on the diverse skill instructions to obtain common skill semantic subspa...
| Authors | Xudong Wang, Zebin Han, Zhiyu Liu et al. |
|---|---|
| Primary category | cs.RO |
| Published | 5 March 2026 |
| Last updated at source | 5 March 2026 |
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