R2RGen introduces a simulator-free three-stage pipeline that parses, augments, and post-processes real pointcloud observation-action pairs to improve spatial generalization in robotic manipulation policies.
//arxiv.org/abs/2409.18121
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RIGVid shows that filtered AI-generated videos can serve as effective supervision for complex robotic manipulation tasks without any real demonstrations.
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R2RGEN: Real-to-Real 3D Data Generation for Spatially Generalized Manipulation
R2RGen introduces a simulator-free three-stage pipeline that parses, augments, and post-processes real pointcloud observation-action pairs to improve spatial generalization in robotic manipulation policies.
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Robotic Manipulation by Imitating Generated Videos Without Physical Demonstrations
RIGVid shows that filtered AI-generated videos can serve as effective supervision for complex robotic manipulation tasks without any real demonstrations.
- From Video to Control: A Survey of Learning Manipulation Interfaces from Temporal Visual Data