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Physical-Intelligence/openpi

Embedl's build embedl/pi05-droid of the original model Physical-Intelligence/openpi

embedl/pi05-droid architecture graph
embedl/pi05-droid architecture graph
  • embedl/pi05-droid
  • FP8
  • H200
Labels
  • Text
  • VLA
  • Robot Policy
Build
Embedl-optimized
Precision
FP8
Runtime
TensorRT 10.16.1.11 with Embedl optimizations
Action chunk
15 joint-position actions per call, 10 denoising steps
Checkpoint
pi05_droid_jointpos (OpenPI, RoboLab's config)
Run π0.5 DROID on H200

π0.5 is Physical Intelligence's vision-language-action policy: it takes camera images, the arm's joint and gripper positions and a task instruction, and outputs robot actions. This is the DROID checkpoint on joint positions (pi05_droid_jointpos), driving a Franka arm in the RoboLab simulator.

Simulator: RoboLab

ad45d4f · Isaac Sim 5.0, Isaac Lab 2.2.0 · Franka Emika Panda (DROID) · 15 steps per second

7 scenes

  • Banana in the bowl banana_bowl

    RoboLab-120 · at most 750 steps

    • Pick up the banana and place it in the bowl
    • Put the fruit in the bowl
    • Grasp the yellow banana and place it inside the red bowl on the table
  • An orange into the white bowl orange_bowl

    RoboLab-120 · at most 900 steps

    • Move an orange to the white bowl
    • Move orange to white bowl
    • Pick up one orange citrus fruit and place it inside the white bowl
  • Yellow block on red yellow_on_red

    RoboLab-120 · at most 900 steps

    • Stack the yellow block on the red block
    • Stack blocks: yellow on red
    • Pick up the yellow block on the left and place it precisely on top of the red block in front of the birdhouse
  • Red things into the bin red_items_bin

    RoboLab-120 · at most 900 steps

    • Put all the red things in the grey bin
    • Sort items by color
    • Identify every red-colored object on the table and place each one into the grey bin
  • Blocks into the bin blocks_in_bin

    RoboLab-120 · at most 2250 steps

    • Sort all colored blocks into the bin
    • Put away the colored blocks
    • Put away the solidly-colored wooden blocks from the table and place them all into the bin
  • Block tower block_tower

    RoboLab-120 · at most 1350 steps

    • Stack the blocks into a tower
    • Build a tower
    • Pick up the colored blocks and stack them vertically on top of each other, forming one tower
  • Blocks in color order colored_blocks

    RoboLab-120 · at most 1350 steps

    • Stack the blocks in the order from bottom to top: red, blue, green, yellow
    • Stack in the order of red, blue, green, yellow
    • Build a tower by placing the red block first, then the blue block on top, then the green, and finally the yellow block on top as a single tower

OpenPI code is Apache-2.0; the weights and tokenizer are Gemma Model Derivatives under the Gemma Terms of Use (ai.google.dev/gemma/terms). Not an official Physical Intelligence product.

Methodology

  • Latency: Policy end to end (served transforms and engine), median of 20 runs; the engine alone, median, on the device.
  • Accuracy: task success is RoboLab-120's as published (Yang et al., NVIDIA, 2026), not measured on this build. The build checks its served actions against OpenPI's PyTorch policy on DROID samples (actions cosine).
  • Simulator: RoboLab (NVIDIA Isaac Sim) runs on its own device; the policy's runner drives it one episode at a time, so a run may wait for another.

Files

Image Size

Model

docker.io/embedl/models:gh.physical-intelligence.openpi.pi05-droid-jointpos-fp8.h200.202610172106e563

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Runtime

docker.io/embedl/models:pi0_5-openpi.h200.runtime.amd64.20261021073351ba

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