This book takes a hands-on, simplified approach to building scalable robotic systems using Terraform for infrastructure and Python for logic. This book eliminates unnecessary complexity, offering practical techniques such as storing binary data in Amazon S3 to trigger AI-based workflowsallowing you to move swiftly from prototype to production.
In this book, youll learn how to set up a ROS2-based camera with servo motors, process images using AI models hosted on AWS, and trigger automated actions with Lambda functions and DynamoDB. Each chapter walks you through real-world implementations, providing Terraform code for deploying serverless components. You'll discover how to manage data streams, run AI-powered object detection, and send movement commands to ROS2 devicesall while maintaining a fully integrated cloud-robotics workflow. Rather than isolating cloud and robotics concepts, this book presents a practical, end-to-end approach with code snippets and best practices for seamless deployment.
By the end of this book, youll have a repeatable framework for using AWS services and AI agents to control and manage ROS2 deviceswithout the need for complex IoT setups. Whether youre a robotics enthusiast or a cloud developer, youll gain the confidence to build scalable, cost-effective, real-time robotics applications that respond to real-world events effortlessly.
What you will learn:
How to set up a simplified serverless pipeline using AWS, Terraform, and Python Explore integrating ROS2 devices with AI agents for real-time event handling How to deploy AI-driven object detection and servo control logic How to manage data flows efficiently with minimal overhead
Who this book is for:
DevOps engineers, robotics enthusiasts, and AI/ML practitioners . Developers looking to integrate ROS2 devices with cloud services. Software architects seeking practical serverless solutions
