🤖 Edge-to-Cloud AI TensorFlow in Robotic Pipelines
Deploying Machine Learning Models on Cloud Platforms for ROS2 Robots
Smart robots don’t just move—they think. And in today’s AI-powered world, deploying intelligence across both edge devices and the cloud is the key to building responsive, autonomous, and scalable robotic systems.
Edge-to-Cloud AI: TensorFlow in Robotic Pipelines is your end-to-end guide for integrating machine learning models into ROS2 robots, using TensorFlow, cloud platforms, and edge computing to achieve real-time performance with global reach.
This book teaches you how to:
Train and optimize TensorFlow models for perception, navigation, and control
Deploy AI models to edge devices using TensorFlow Lite and Coral/Jetson hardware
Build cloud-connected AI inference pipelines with ROS2, MQTT, and REST APIs
Leverage AWS, GCP, or Azure to manage, monitor, and scale robotic workloads
Streamline real-time communication between robots and cloud AI services
Apply federated learning and model updates across distributed fleets
Handle sensor fusion and decision logic between edge and cloud AI layers
From autonomous drones to AI-powered service bots, you’ll gain the skills to create robots that learn in the cloud, think at the edge, and act in real time.
🛠️ Perfect for robotics engineers, AI developers, and cloud-native automation teams
📦 Includes TensorFlow model deployment templates, ROS2 integration code, and edge-cloud data flow examples
⚙️ Covers multi-cloud strategies, hybrid inference, and edge accelerators
Build AI that scales. Power robots that think. From the edge to the cloud and beyond.
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