Cyclo Lab
Cyclo Lab is the Isaac Lab-based environment for training AI Sapiens K1 policies in simulation. It provides the training and export workflow needed before deploying a policy with Sim2Real.
For robot-side deployment after training, use the Sim2Real guide.
Set Up the Docker Container
Run Cyclo Lab inside the provided Docker container. The container includes Isaac Sim, Isaac Lab, Cyclo Lab, and the Python dependencies used by the training scripts.
Install these on the host PC first:
- Docker and Docker Compose.
- NVIDIA Container Toolkit.
- NVIDIA GPU driver compatible with the Isaac Sim container image.
Clone Cyclo Lab with submodules:
git clone --recurse-submodules https://github.com/ROBOTIS-GIT/cyclo_lab.git
cd cyclo_lab
If the repository was cloned without submodules, initialize them before starting the container:
git submodule update --init --recursive
Start and enter the container:
./docker/container.sh start
./docker/container.sh enter
Inside the container, the repository is mounted at:
/workspace/cyclo_lab
Useful host-side commands:
| Command | Use |
|---|---|
./docker/container.sh start | Build if needed, initialize submodules, and start the container. |
./docker/container.sh enter | Open a shell inside the running container. |
./docker/container.sh stop | Stop the container. |
./docker/container.sh logs | Follow container logs. |
./docker/container.sh clean | Remove the container and image. |
The start script enables X11 forwarding when DISPLAY and xauth are available on the host.
Use --headless for training runs that do not need the Isaac Sim window.
Next Steps
- Train and export a velocity policy with the Locomotion guide.
- Train and export a motion-imitation policy with the Mimic guide.
- Deploy the exported asset with How to Deploy Your Own Cyclo Lab-Trained Policy.