Robots that learn from a few demonstrations often require two forms of generalization. Compositional generalization recombines skills to solve new tasks, and skill generalization lets the learned policy behind each skill work in new situations. The two depend on each other, yet information is lost between composition a...
Pu-Ming Jiang, Tian-Run Hu, Hao-Zhe Du et al.· 0 citations
Vision-language-action (VLA) models struggle on history-dependent manipulation tasks, where the current observation alone does not determine the action, and the policy needs a memory of the history. Existing memory methods decide what to remember by design, for example, keeping frames with large pixel changes, and show...
Xue-Hui Yu, Eason Yu, Mei-Yi Wang et al.· 0 citations
Physically grounded robot intelligence requires robots to perceive, reason about, and regulate their interactions with the physical world. This capability is particularly critical in contact-sensitive manipulation, where successful task execution depends not only on visual perception and motion generation, but also on...
Shilin Shan, Chu-Hao Zhou, Rui-Ze Wang et al.· 0 citations
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