CLARU
mulligan2026MIT

sim-square-broad-c01-dagger-sobol-no-cf

Part of the Mulligan project, this dataset contains 100 episodes of simulated square manipulation tasks using DAGGER training with Sobol sampling and no counterfactual augmentation. Data is provided in parquet format with state-only observations.

Downloads75
Episodes100

Why This Matters for Physical AI

This dataset contributes to physical AI research by providing simulated manipulation trajectories generated through DAGGER imitation learning with controlled sampling strategies, enabling study of policy learning methodologies and data augmentation effects.

Technical Profile

Modalities
proprioception
Environment
simulation
Task Types
manipulation
Episodes
100
Data Format
parquet
License
MIT
Part of the Mulligan family

Access

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