AINeutralarXiv – CS AI · Jun 96/10
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Continual Quadruped Robots Coordination via Semantic Skill Discovery
Researchers present Conquer, a semantic skill-library framework enabling multi-quadruped robots to learn new coordination tasks sequentially without forgetting previously acquired skills. The system uses a variable-cardinality architecture and semantic descriptors to retrieve and adapt existing skills for new tasks, achieving 95.6% success rates in simulation and real-world validation on Unitree Go2 robots.
