Everloom2025MIT
Active Perception AAWR Dataset in GRASP Lab Mock Kitchen
A real-world reinforcement learning dataset of active perception behaviors collected in a mock kitchen environment with 4 scenes. The dataset contains 13.5GB of robot demonstrations in DROID format with cleaned, idle-frame-filtered episodes.
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Why This Matters for Physical AI
This dataset demonstrates real-world active perception learning through reinforcement learning, showing how robots can learn to effectively control their viewpoints and sensing strategies to accomplish manipulation tasks in realistic kitchen environments.
Technical Profile
- Modalities
- rgbproprioception
- Robot Embodiments
- xarm
- Action Space
- joint_positions
- Environment
- kitchenlab
- Task Types
- manipulationactive_perceptionlifting
- Data Format
- DROID
- License
- MIT
Community Signals
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