English

Principles of Robot Autonomy

Robotics 2026-08-04 v1 Artificial Intelligence Computer Vision and Pattern Recognition Systems and Control

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.

Cite

@article{arxiv.2608.03496,
  title  = {Principles of Robot Autonomy},
  author = {Daniele Gammelli and Joseph Lorenzetti and Katie Luo and Gioele Zardini and Marco Pavone},
  journal= {arXiv preprint arXiv:2608.03496},
  year   = {2026}
}

Comments

531 pages. Pre-publication version of a book forthcoming from Cambridge University Press, posted with the permission of the publisher