Cloud Robotics Architecture: How Robots Offload AI Workloads to the Cloud

This chapter from the STATERA Library's AMR AI and Embodied Intelligence series explains cloud robotics, which combines robotics, cloud computing, AI, and edge computing. Instead of treating robots as isolated machines, it describes networked agents that continuously share data, models, and operational state with cloud infrastructure. The architecture is layered, with real-time tasks like obstacle avoidance kept on local edge hardware while heavy AI inference, learning, simulation, and fleet management move to the cloud. The text highlights benefits such as scalable compute, fleet-level learning, and continuous model updates over the air, while noting latency and network reliability as key constraints. It concludes that most practical systems rely on local autonomy supported by cloud-based intelligence.
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