SMoDP routes action chunks in a diffusion policy to semantically specialized experts via a VLM-supervised skill predictor and dual contrastive alignment, achieving better efficiency and compositional transfer than baselines.
3d diffusion policy: Generalizable visuomotor policy learning via simple 3d representations
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A task-conditioned two-stage system decouples grasp localization from interaction trajectory planning using specialized foundation models to improve generalization across heterogeneous object types.
WARPED synthesizes realistic wrist-view observations from monocular egocentric human videos via foundation models, hand-object tracking, retargeting, and Gaussian Splatting to train visuomotor policies that match teleoperation success rates on five tabletop tasks with 5-8x less collection effort.
citing papers explorer
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Semantically Structured Mixture-of-Experts for Compositional Robotic Manipulation
SMoDP routes action chunks in a diffusion policy to semantically specialized experts via a VLM-supervised skill predictor and dual contrastive alignment, achieving better efficiency and compositional transfer than baselines.
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HeteroGenManip: Generalizable Manipulation For Heterogeneous Object Interactions
A task-conditioned two-stage system decouples grasp localization from interaction trajectory planning using specialized foundation models to improve generalization across heterogeneous object types.
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WARPED: Wrist-Aligned Rendering for Robot Policy Learning from Egocentric Human Demonstrations
WARPED synthesizes realistic wrist-view observations from monocular egocentric human videos via foundation models, hand-object tracking, retargeting, and Gaussian Splatting to train visuomotor policies that match teleoperation success rates on five tabletop tasks with 5-8x less collection effort.