PolicyServer in the foreground, so run-policy can offload inference to a more powerful machine (e.g. a desktop with a discrete GPU) on the same network as the robot. The robot streams joint positions + camera frames to it over gRPC and receives action chunks back.
The policy itself (--policy_path / --policy_type / --device) is selected by the client (run-policy), not the server — so one server can serve different policies across sessions without restarting. The server downloads the policy itself, so the path must be reachable from it (e.g. a HuggingFace Hub repo ID, or a local path that exists on the server machine).
Requires the
lerobot extra and, for GPU inference, a CUDA-capable PyTorch install on the server machine. Without --server_host, run-policy spawns its own local PolicyServer child process — this command is only needed when inference runs on a different machine.