Asimov 1 locomotion policy
- AI model
- Humanoids and robot learning
- Runs on hardware you can build
Training and evaluation code for Asimov 1 humanoid locomotion policies, built as an Isaac Lab extension using PPO and adversarial motion priors, for sim-to-real deployment.
- Closed core
Made by Menlo Research, Singapore (checked on github.com/menloresearch (opens in a new tab)).
Source on GitHub: github.com/menloresearch/cyclotron (opens in a new tab). Facts read at commit 870c161 (opens in a new tab).
Licenses
- Code
- BSD-3-Clause (opens in a new tab)
Read by Robotheca from LICENSE (opens in a new tab) (BSD-3-Clause) at commit 870c161 (opens in a new tab), on 16 Oct 2026.
- Weights
- BSD-3-Clause (opens in a new tab)
Read on huggingface.co/Menlo/asimov1-locomotion-0818 (opens in a new tab).
- Commercial use
- Unknown
It needs closed parts under their own terms: read them before any commercial use.
One part it needs is closed
- Needs NVIDIA Isaac Sim components (training): Training goes through Isaac Lab, which needs Isaac Sim's closed components; the policy itself runs without them.
Labels
- Closed coreIt needs closed parts: NVIDIA Isaac Sim components (training).
What it does
- Trains Asimov 1 walking policies in Isaac Lab with PPO, with an optional adversarial motion prior (AMP) variant.
- Plays back checkpoints in Isaac Sim to watch and evaluate trained policies.
- Exports checkpoints to ONNX with a deployment contract in the metadata for robot runtimes.
- Uploads trained runs with a generated model card to the Hugging Face Hub.
- Views exported or shared policies in the browser with MuJoCo, without Isaac Sim or a GPU.
- Includes a quick install script that sets up uv, Isaac Lab and the Asimov 1 robot model.
Written by Robotheca from the project's README (opens in a new tab) at commit 870c161.
Getting started
- Difficulty
- Advanced
- Hardware it needs, as the project states it
- Ubuntu 22.04+ on x86_64 with a compatible NVIDIA driver and a GPU; tested on RTX A6000, RTX PRO 6000, RTX 4090 and RTX 3090. Training at 4096 environments is said to suit A6000 or PRO 6000, with lower num_envs suggested for out-of-memory errors. The browser viewer needs only Node.js 20 or newer, wit
- How to start
- The project's README (opens in a new tab)
Maintenance
- Status
- Active: a commit in the last 90 days
- Newest commit
- 16 Oct 2026 on main
- Latest release
- None published on GitHub
Checked on GitHub on 16 Oct 2026.
Links
Robots on Robotheca that use it
No robot on Robotheca is linked to it yet. Links come from a robot's robot.yaml, from its dependency files read as text, or from Robotheca's editors.
Robotheca lists AI models as a reference: nothing is hosted or run here, and every fact links to where it was read.