| --- |
| license: other |
| license_name: nvidia-open-model-license |
| license_link: https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/ |
| base_model: nvidia/GR00T-N1.7-3B |
| tags: |
| - robotics |
| - humanoid |
| - vla |
| - gr00t |
| - asimov |
| - mujoco |
| pipeline_tag: robotics |
| --- |
| |
| # GR00T N1.7 for the Asimov 1 humanoid (simulation) |
|
|
| A fine-tune of [NVIDIA GR00T N1.7-3B](https://huggingface.co/nvidia/GR00T-N1.7-3B) for |
| [Menlo Research's Asimov 1](https://github.com/menloresearch/asimov-1), an open-source humanoid, in the |
| configuration that actually ships: 25 DOF, passive printed "dummy hands" (no grippers), one monocular head |
| camera. As far as we know this is the first GR00T policy for Asimov. |
|
|
| **Simulation only.** It has not been run on a real robot. |
|
|
| ## Tasks and results |
|
|
| Three language-conditioned tabletop tasks in MuJoCo. Evaluation is closed loop on 50 held-out layouts per |
| task, with seeds disjoint from every training seed. The policy runs at 20 Hz, predicts 16-step chunks and |
| executes 8 of them per call. Success must hold for 0.5 s. |
|
|
| | Task | Instruction example | ckpt 6000 | **ckpt 10000** | 95% CI (10000) | |
| |---|---|---|---|---| |
| | Push (one fist) | "push the purple block onto the orange pad" | 46% | **84%** | 0.71–0.92 | |
| | Button | "press the red button" | 36% | **64%** | 0.50–0.76 | |
| | Box (bimanual squeeze, carry, place) | "lift the box and put it on the shelf" | 2% | **56%** | 0.42–0.69 | |
|
|
| - **Main failures at step 10000:** |
| - push: block short of the pad (5), block never moved (3) |
| - button: no press (10), partial press (6), wrong button (2) |
| - box: dropped or not placed (16) |
| - **Not converged:** success was still rising steeply between steps 6000 and 10000, so longer training should help. |
| - **Open-loop** on training episodes: action MAE 0.027 rad. |
| - **Inference:** 95 ms per call on an L40 (PyTorch eager). |
|
|
| Example rollouts (one success and one failure per task) are in `results/closedloop_checkpoint-10000/videos/`. |
|
|
| ## Training |
|
|
| - **Data:** 900 scripted-expert demonstrations, 300 per task. That is 155k frames at 20 Hz, 43 instructions, |
| randomized object poses, colors, distractors, lighting and camera jitter. |
| - **Observation:** |
| - head camera, 256×256 |
| - joint positions: left and right arm (5 each), waist yaw, neck yaw and pitch |
| - the instruction |
| - **Action:** absolute joint targets for the same 13 DOF, learned as RELATIVE (delta from current state), |
| 16-step horizon. |
| - **Fine-tune:** `NEW_EMBODIMENT`, default GR00T recipe (projector and action head trained, backbone frozen). |
| 10,000 steps at batch 64, learning rate 1e-4, color jitter. One L40 for 2 h 43 m. Loss went from 0.095 to 0.010. |
| - **Checkpoints:** `checkpoints/checkpoint-{2000..10000}`, with weights and processor but no optimizer state. |
|
|
| ## Simplifications and assumptions |
|
|
| These are deliberate scope cuts for v1: |
|
|
| - **Pelvis welded:** legs held at the standing pose. Balance is the locomotion controller's job on hardware. |
| - **Hand collision shapes:** convex hulls of Menlo's printed dummy-hand files. Mass (0.18 kg) and mounting are |
| assumptions. |
| - **Head camera:** mounted pitched 45° down inside the head with a 75° vertical FOV. The neck's 19.5° downward |
| limit cannot see the table on its own. This needs checking against the real camera mount. |
| - **Box task:** the carton is held by friction only (μ 0.5, no welds). It uses a 0.30–0.34 m carton because |
| Asimov's fists only face each other in a narrow band, set by one-sided shoulder roll and a 5-DOF arm. |
|
|
| ## Code |
|
|
| Simulation tasks, scripted experts, dataset export, GR00T modality config, closed-loop evaluation and the |
| one-shot training script: `asimov-groot` (to be published). |
|
|
| ## License |
|
|
| Licensed by NVIDIA Corporation under the |
| [NVIDIA Open Model License](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/). |
| This is a derivative of nvidia/GR00T-N1.7-3B, which uses nvidia/Cosmos-Reason2-2B, under the same license. |
| The Asimov robot model is from menloresearch/asimov-1 (GPL-2.0 software / CERN-OHL-S-2.0 hardware). |
|
|
