CLARU
e-cagan2026apache-2.0

DiffPick: Fetch Pick-and-Place Demonstrations

A dataset of 200 successful pick-and-place demonstrations collected from a scripted expert policy in the FetchPickAndPlace-v4 MuJoCo environment, designed for training vision-based imitation learning policies.

Downloads14
Episodes200

Why This Matters for Physical AI

This dataset demonstrates vision-based imitation learning for manipulation by forcing policies to develop visual grounding rather than relying on ground-truth object pose, bridging the gap between simulation and real-world deployment scenarios.

Technical Profile

Modalities
rgbproprioception
Robot Embodiments
Fetch
Action Space
end_effector_delta
Environment
simulation
Task Types
pick_and_placemanipulationgrasping
Episodes
200
Data Format
LeRobot
Annotation Types
language_instructions
License
apache-2.0
Part of the DiffPick family

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