LeWAM
LeWAM TwoRoom
Simulation training data for the LeWAM (Learning with Action Models) project, containing 10,000 episodes of navigation and manipulation tasks in a two-room environment.
Downloads16
Episodes10,000
Why This Matters for Physical AI
This dataset provides large-scale simulation training data for learning embodied navigation and action models in structured environments, enabling research into action prediction and model-based reinforcement learning for robotics.
Technical Profile
- Modalities
- rgb
- Action Space
- discrete
- Environment
- simulation
- Task Types
- navigation
- Episodes
- 10,000
- Data Format
- HDF5
Access
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