MarcelTorneMIT
plate_toast_preferences
Real-robot trajectories for a Franka Panda performing "put the toast in the plate" with human pairwise preference labels across 43 judgment axes. Built for reward-model and preference-learning research with 271 episodes and 2,671 preference labels.
Downloads0
Episodes271
Hours~1.5
Why This Matters for Physical AI
This dataset enables training of reward models through pairwise preference learning on real robot manipulation trajectories, advancing RLHF and preference-learning methods for robotic control.
Technical Profile
- Modalities
- rgbproprioception
- Robot Embodiments
- Franka Panda
- Action Space
- joint_positions
- Environment
- lab
- Task Types
- manipulationpick_and_place
- Episodes
- 271
- Total Hours
- ~1.5
- Data Format
- LeRobot
- Annotation Types
- preference_labelspairwise_comparisonsreward_labels
- License
- MIT
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