MarcelTornemit
setup_table_preferences
Real-robot trajectories for table setup on a Franka Panda with human pairwise preference labels across multiple judgment axes, designed for reward modeling and preference learning research.
Downloads0
Episodes467
Hours3.7
Why This Matters for Physical AI
This dataset enables preference learning and reward modeling research by providing structured human feedback on robot manipulation trajectories across multiple quality dimensions, advancing methods for learning from human preferences rather than scalar rewards.
Technical Profile
- Modalities
- rgbproprioception
- Robot Embodiments
- Franka Panda
- Action Space
- joint_positions
- Environment
- lab
- Task Types
- manipulationtable_setup
- Episodes
- 467
- Total Hours
- 3.7
- Data Format
- LeRobot
- Annotation Types
- pairwise_preferenceslanguage_instructionsreward_labels
- License
- mit
Access
Need custom rgb data?
Claru builds purpose-built datasets for lab applications with dense human annotations and quality assurance.
Request a Sample Pack