Train robot policies for simulation or real arms.
Guides users through training, evaluating, and serving robot action policies with OpenVLA-OFT and OpenVLA-OFT+.
When to use it
Use for visually and language-conditioned robot action generation, particularly official LIBERO or ALOHA workflows with continuous action heads.
Give it a robot-policy training or evaluation request; it sets up the official codebase and runs the corresponding workflow.
Requires conda to create and activate the training environment.
Requires GPU compute: evaluation lists one A100/A40 with about 16–18 GB VRAM; paper-default training lists eight A100s.
This skill
VLA server
Starts a robot inference server
Requests actions from the server
ALOHA
Controls your ALOHA robot