AIBullisharXiv – CS AI · 10h ago7/10
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KITE: Decoupling Kinematics and Interaction for Zero-Shot Cross-Embodiment Manipulation
Researchers introduce KITE, a machine learning framework that decouples task reasoning from embodiment-specific motor control to enable robot manipulation policies trained on one robot type to transfer zero-shot to structurally different robots. The approach uses learned latent representations of interaction intent based on contact patterns, requiring only kinematic model training for new embodiments without collecting new demonstration data.