Software & Middleware

Cloud Robotics

Cloud robotics is an architecture in which robots offload computation, storage, and learning to remote data centers while retaining time-critical control onboard, a term popularized by James Kuffner around 2010. Typical patterns include cloud-hosted fleet management, shared maps and skill libraries, remote teleoperation gateways, and centralized training on fleet-collected data with periodic policy redeployment. Latency, bandwidth, and connectivity loss define the boundary between cloud and edge responsibilities.

Why it matters for physical AI

Fleet learning loops, in which robots stream experience to central training clusters and receive improved policies, are the operational backbone of scaling robot foundation models with real-world data.