Principles of Robot Autonomy
Daniele Gammelli, Joseph Lorenzetti, Katie Luo, Gioele Zardini, Marco Pavone
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.
Create a lesson
Related papers
rMuscle: Robotic Muscle Memory for Efficient Vision-Language-Action Model Inference
Kaijun Zhou, Zhiyang Li, Le Chen et al.
ElastiQP: An Always-Feasible QP Solver for Constrained Robot Control
Daniel Morton, Jon Arrizabalaga, Zachary Manchester et al.
"What's going to happen after I'm gone?": Parent Perspectives on Technology in Supporting Independent Living for Adults with Intellectual Disabilities
Alexander Tyshka, Andrea Macklem-Zabel, Absalat Getachew et al.
Learning Holistic Whole-Body Loco-Manipulation with a Bipedal Mobile Manipulator
Zhongyu Chen, Yuxuan Nai, Qian Chen et al.
CaSCo: Cascade-Aware Soft-Collision Motion Planning
Shivaram Kumar, Gaoyuan Liu, Yoonchang Sung
Examining the Difference in Human Behavior Between Virtual and Real-World Human-Robot Teaming
Sean Dallas, Absalat Getachew, Motaz AbuHijleh et al.