MimicGen UR5e pi0.5 with 6-D end-effector state

This repository contains two pi0.5 checkpoints trained on the same balanced UR5e MimicGen four-task subset. The policy state contains only end-effector position and axis-angle rotation:

[ee_x, ee_y, ee_z, ee_rx, ee_ry, ee_rz]

The original gripper joint state is removed before normalization and prompt tokenization. The OSC_POSE action remains 7-D:

[delta_x, delta_y, delta_z, delta_rx, delta_ry, delta_rz, gripper_command]

Checkpoints

Hub path OpenPI config Normalization
ownnorm/14999 pi05_mimicgen_ur5e4_ee6_state_ownnorm_2850_15k UR5e-only state and action quantiles
sharednorm/14999 pi05_mimicgen_ur5e4_ee6_state_sharednorm_2850_15k Shared Panda+UR5e state and action quantiles

Each checkpoint includes inference parameters, normalization assets, and Orbax checkpoint metadata. Optimizer/train state is intentionally omitted.

Training setup

  • Tasks: Square 950, Threading 950, Stack 475, Stack Three 475
  • Total demonstrations: 2,850
  • State dimensions used by the policy: 6
  • Action dimensions before OpenPI padding: 7
  • Action horizon: 10
  • Optimizer updates: 15,000; checkpoint step: 14,999
  • Micro-batch size: 8
  • Gradient accumulation: 8 (effective batch size 64)
  • Initialization: pi0.5 base checkpoint

OpenPI loading

Use the matching config from the DART/OpenPI codebase. For example, after downloading ownnorm/14999:

python scripts/serve_policy.py \
  --env LIBERO \
  --port 8000 \
  policy:checkpoint \
  --policy.config pi05_mimicgen_ur5e4_ee6_state_ownnorm_2850_15k \
  --policy.dir /path/to/ownnorm/14999

The environment may provide the original padded 12-D MimicGen state. The matching policy config applies TruncateState(state_dim=6) before normalization and pi0.5 discrete-state tokenization, so only the six end-effector pose values affect the state tokens.

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