CASTER: Formalizing Zero-Shot Manipulation from Synthetic Videos as Constrained Optimization
cs.RO, cs.CV
Submitted: 2026-10-08
Updated: 2026-10-08
Code: https://github.com/isaac-sim/IsaacSim
Project page: https://collab.me.vt.edu/CASTER
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset
- OPEN TEACH: A Versatile Teleoperation System for Robotic Manipulation
- Robotic Manipulation by Imitating Generated Videos Without Physical Demonstrations
- Robot Learning from a Physical World Model
- Learning to Act from Actionless Videos through Dense Correspondences
- Morphology-Consistent Humanoid Interaction through Robot-Centric Video Synthesis
- Learning Universal Policies via Text-Guided Video Generation
- Video Generators are Robot Policies
- VAG: Dual-Stream Video-Action Generation for Embodied Data Synthesis
- RoboVIP: Multi-View Video Generation with Visual Identity Prompting Augments Robot Manipulation
- CRAFT: Video Diffusion for Bimanual Robot Data Generation
- DreamGen: Unlocking Generalization in Robot Learning through Video World Models
- Ctrl-World: A Controllable Generative World Model for Robot Manipulation
- GE-Sim 2.0: A Roadmap Towards Comprehensive Closed-loop Video World Simulators for Robotic Manipulation
- GenHOI: Contact-Aware Humanoid-Object Interaction by Imitating Generated Videos without Task-Specific Training
- Gen2Act: Human Video Generation in Novel Scenarios enables Generalizable Robot Manipulation
- Grounding Generated Videos in Feasible Plans via World Models
- Do as I Do: Dexterous Manipulation Data from Everyday Human Videos
- EmboAlign: Aligning Video Generation with Compositional Constraints for Zero-Shot Manipulation
- V2-STRep: VLM-Grounded Structured Task Representations for Reusable Robot Skills Acquired from Generated Videos
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