Simulo for Cloud Robotics Simulation and Training

Train robot policies in simulation on managed cloud GPUs.

Simulo is a cloud-native AI platform for robotics simulation and training. Its lightweight simulo Python SDK and CLI let you define robot-learning applications locally, submit them to the Simulo cloud, and inspect the results. The platform handles managed GPU execution, reproducible packaging, versioned assets, policies, checkpoints, recordings, ONNX bundles, and live 3D viewing.

The package installed on your computer is torch-free and requires no local GPU or simulator. The managed runtime executes reinforcement-learning training on managed GPUs in the cloud.

What you can do

• Write robotics applications in ordinary Python against a small, stable API.
• Build vectorized reinforcement-learning environments and train robot policies with PPO.
• Start with validated catalog robots or publish your own OpenUSD (USD) and URDF assets.
• Continue training from the best or latest checkpoint produced by an earlier job.
• Export an explicit policy checkpoint as a verified ONNX bundle.
• Stream logs, retrieve results and outputs, capture MCAP rollout recordings, and watch a live 3D view.

Install

python -m pip install simulo

Simulo requires Python 3.11 or newer. One installation provides both the import simulo Python API and the simulo command-line interface.

Train a first policy

simulo create mybot
simulo login
cd mybot
simulo run train.py --frozen --strict-assets

simulo create writes a complete starter application to your machine without requiring a login or network connection. It creates task.py, train.py, and .simuloignore; the default application trains a PPO policy on a validated cartpole asset. simulo run packages the source, resolves and pins its assets, submits the job, and follows its cloud logs.

Explore robotics samples

The public Simulo samples repository contains projects for cartpole, humanoid locomotion, JetBot navigation, Franka arm control, a bring-your-own URDF arm, and F1TENTH-compatible drift training. See the repository README for setup and usage.

Monitor jobs and retrieve artifacts

simulo jobs                       # list submitted jobs and status
simulo logs --follow              # stream the latest job's logs
simulo result                     # read the job's result
simulo policy list                # list training policies and checkpoints
simulo policy get policy_x:best   # download a verified checkpoint
simulo export policy_x:best       # export a verified ONNX bundle
simulo recordings                 # download MCAP rollout recordings
simulo outputs                    # retrieve other saved outputs
simulo view                       # view a running --viewstream job in 3D
simulo cancel                     # stop a queued or running job

Commands that accept a job ID default to the latest job and tell you which job they selected.

Use versioned robot assets

simulo asset list --global
simulo asset inspect simulo/robot/cartpole:v1
simulo asset publish ./my-robot --kind robot

Simulo catalogs keep robot, world, and prop assets versioned and traceable. You can use validated global assets immediately or publish your own USD or URDF package for reuse across training jobs.

Learn more

• Quickstart
• Documentation
• Python API reference
• CLI reference
• Examples
• Simulo website