Seamless multi-skill learning: learning and transitioning non-similar skills in quadruped robots with limited data
In multi-skill imitation learning for robots, expert datasets with complete motion features are crucial for enabling robots to learn and transition between different skills. However, such datasets are often difficult to obtain. As an alternative, datasets constructed using only joint positions are m...
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| Principais autores: | , , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Frontiers Media S.A.
2025-04-01
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| coleção: | Frontiers in Robotics and AI |
| Assuntos: | |
| Acesso em linha: | https://www.frontiersin.org/articles/10.3389/frobt.2025.1542692/full |
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