ReKep encodes robotic tasks as optimizable Python functions over 3D keypoints that are generated automatically from language and RGB-D input, enabling real-time hierarchical planning on single- and dual-arm platforms without task-specific data.
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Decompose and Recompose decomposes seen robotic demonstrations into skill-action alignments and recomposes them via visual-semantic retrieval and planning to enable zero-shot cross-task generalization.
A two-level hierarchical vector quantization tokenizer that clusters actions spatially and temporally achieves new state-of-the-art results in in-context imitation learning for robotics.
citing papers explorer
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ReKep: Spatio-Temporal Reasoning of Relational Keypoint Constraints for Robotic Manipulation
ReKep encodes robotic tasks as optimizable Python functions over 3D keypoints that are generated automatically from language and RGB-D input, enabling real-time hierarchical planning on single- and dual-arm platforms without task-specific data.
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Decompose and Recompose: Reasoning New Skills from Existing Abilities for Cross-Task Robotic Manipulation
Decompose and Recompose decomposes seen robotic demonstrations into skill-action alignments and recomposes them via visual-semantic retrieval and planning to enable zero-shot cross-task generalization.
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A Hierarchical Spatiotemporal Action Tokenizer for In-Context Imitation Learning in Robotics
A two-level hierarchical vector quantization tokenizer that clusters actions spatially and temporally achieves new state-of-the-art results in in-context imitation learning for robotics.