机器人自主性原理
Principles of Robot Autonomy
Daniele Gammelli · Joseph Lorenzetti · Katie Luo · Gioele Zardini · Marco Pavone
中文摘要
自主机器人正迅速走出研究实验室，进入道路、空中、仓库和太空等现实环境。机器人自主性已不再是纯学术课题，而成为从业者在实际部署中依赖的一套成熟且经过现场验证的方法与工具。本书在统一概念框架下清晰介绍实现自主性的方法，源于 Stanford 数十年的教学经验，涵盖现代自主技术栈的核心要素，并连接经典机器人学与现代物理 AI。每个主要主题均配有实践型 Jupyter notebooks 和以实现为导向的练习，帮助读者在掌握理论的同时建立实践直觉，为设计、分析或参与下一代自主系统提供有原则、易理解且面向部署的基础知识。
关键要点
- 01自主机器人已从实验室研究走向道路、空中、仓库和太空部署
- 02机器人自主性已形成经现场验证、可供实践者采用的成熟方法与工具
- 03统一框架连接经典机器人学、现代物理 AI 与自主技术栈核心要素
- 04各主要主题均配有 Jupyter notebooks 和实现导向练习
- 05内容面向学生、工程师及进入自主系统领域的研究人员
解读
尚无解读。
原始英文摘要
arXiv:2608.03496v2 Announce Type: replace Abstract: 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.