系统梳理机器人自主核心技术，理论实践结合。
Principles of Robot Autonomy
- 基于统一框架整合经典与现代自主方法
- 配套交互式代码实验强化实战理解
- 适合想深入机器人系统的研习者
自主机器人正快速从实验室走向日常应用——在道路、空中、仓库和太空中。机器人自主已不再只是学术探索，而是由一系列成熟、经实地验证的方法与工具构成，成为从业者在真实部署中的可靠支撑。本书提供清晰、统一的入门指南，系统阐述实现这一目标的核心技术。内容基于斯坦福大学数十年教学经验，将现代自主系统架构中的关键要素纳入单一概念框架，连接经典机器人学与现代物理人工智能。每个主要主题均配有动手的 Jupyter 笔记本与以实现为导向的练习，使读者在掌握理论的同时建立实际直觉。最终形成一套有原则、可访问、面向部署的基础，为设计、分析或贡献下一代自主系统的人士提供坚实支撑。本书是学生、工程师与研究人员进入当今增长最快领域之一的全面资源。
原文摘要 · Abstract (English)
Autonomous robots are moving rapidly from research labs into everyday life - on roads, in the air, in warehouses, and in space. Robot autonomy is no longer solely an academic pursuit, but a collection of mature, field-tested methods and tools that practitioners rely on in real-world deployments. This book offers a clear, unified introduction to the methods that make this possible. Built on decades of teaching at Stanford, the text develops the core elements of modern autonomy stacks within a single conceptual framework, bridging classical robotics and modern physical AI. Every major topic is paired with hands-on Jupyter notebooks and implementation-driven exercises, so readers build practical intuition alongside theoretical understanding. The result is a principled, accessible, and deployment-aware foundation for anyone seeking to design, analyze, or contribute to the next generation of autonomous systems. This is a comprehensive resource for students, engineers, and researchers entering one of today's fastest-growing fields.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。