Building Serverless Robotics with Aws, Ai, and Ros 2: Designing Drone Detection and Defense Systems Under Fire
暫譯: 使用 AWS、AI 和 ROS 2 建立無伺服器機器人：設計在火力下的無人機偵測與防禦系統
Kozhevin, Dmytro
相關主題
商品描述
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 workflows--allowing you to move swiftly from prototype to production.
In this book, you'll 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 devices--all 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, you'll have a repeatable framework for using AWS services and AI agents to control and manage ROS2 devices--without the need for complex IoT setups. Whether you're a robotics enthusiast or a cloud developer, you'll 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
商品描述(中文翻譯)
這本書採用實作導向的簡化方法，使用 Terraform 來構建可擴展的機器人系統，並使用 Python 來處理邏輯。這本書消除了不必要的複雜性，提供實用的技術，例如將二進位數據儲存在 Amazon S3 中以觸發基於 AI 的工作流程，讓您能夠迅速從原型轉向生產環境。
在這本書中，您將學習如何設置基於 ROS2 的相機與伺服馬達，使用托管在 AWS 上的 AI 模型處理圖像，並通過 Lambda 函數和 DynamoDB 觸發自動化操作。每一章都會帶您走過真實世界的實作，提供用於部署無伺服器組件的 Terraform 代碼。您將發現如何管理數據流，運行基於 AI 的物體檢測，並向 ROS2 設備發送運動指令，同時保持完全整合的雲端機器人工作流程。這本書並不將雲端和機器人概念孤立，而是提供一種實用的端到端方法，包含代碼片段和最佳實踐，以實現無縫部署。
在這本書結束時，您將擁有一個可重複的框架，利用 AWS 服務和 AI 代理來控制和管理 ROS2 設備，而無需複雜的物聯網設置。無論您是機器人愛好者還是雲端開發者，您都將獲得信心，構建可擴展、具成本效益的即時機器人應用程序，輕鬆應對現實世界的事件。
您將學習到的內容：
- 如何使用 AWS、Terraform 和 Python 設置簡化的無伺服器管道
- 探索將 ROS2 設備與 AI 代理整合以進行即時事件處理
- 如何部署基於 AI 的物體檢測和伺服控制邏輯
- 如何以最小的開銷有效管理數據流
本書適合對象：
DevOps 工程師、機器人愛好者和 AI/ML 實踐者。希望將 ROS2 設備與雲端服務整合的開發者。尋求實用無伺服器解決方案的軟體架構師。
作者簡介
Dmytro Kozhevin is an accomplished DevOps Engineer and Educator with over 18 years of experience, specializing in AI, serverless robotics, and cloud infrastructure. Currently, he focuses on AWS EKS, CI/CD, and Kubernetes, helping professionals implement scalable, automated solutions. His expertise extends to integrating AI-driven workflows with AWS services and ROS2, enabling real-time decision-making in robotics. Passionate about innovation, Dmytro is dedicated to simplifying complex DevOps and AI challenges, making advanced cloud and automation technologies accessible through education, hands-on training, and real-world applications.
作者簡介(中文翻譯)
Dmytro Kozhevin 是一位成就卓越的 DevOps 工程師和教育者，擁有超過 18 年的經驗，專注於人工智慧、無伺服器機器人技術和雲端基礎設施。目前，他專注於 AWS EKS、CI/CD 和 Kubernetes，幫助專業人士實施可擴展的自動化解決方案。他的專業知識還包括將 AI 驅動的工作流程與 AWS 服務和 ROS2 整合，使機器人能夠進行即時決策。Dmytro 對創新充滿熱情，致力於簡化複雜的 DevOps 和 AI 挑戰，通過教育、實作訓練和實際應用，使先進的雲端和自動化技術變得更易於接觸。
