Humanoid Robots and Physical AI

This book analyzes the convergence of humanoid robotics and agentic AI, providing the first comprehensive, interdisciplinary examination of how physical embodiment and autonomous intelligence are transforming robotics from research prototypes into practical systems reshaping industries worldwide. It addresses the critical gap in understanding how hardware innovations, AI breakthroughs, economic forces, and societal considerations intersect in the development and deployment of humanoid robots. The scope spans ten engaging chapters covering: hardware and embodiment technologies (actuators, power systems, locomotion); perception and interaction systems (computer vision, sensor fusion, multimodal processing); agentic AI architectures (foundation models, reinforcement learning, planning systems); integration and control (real-time systems, simulation, sim-to-real transfer); safety, security, and reliability (physical safety standards, cybersecurity, adversarial robustness); economic transformation and labor markets (cost analysis, productivity gains, business models); governance, ethics, and philosophy (regulatory frameworks, liability, consciousness debates); psychology and human-robot coexistence (trust, emotional bonding, societal adaptation); and decentralized systems and future convergence (blockchain integration, robot economies, 2030-2050 scenarios). Among the compelling themes addressed are the USA-China technology race in humanoid development, with detailed case studies of Boston Dynamics, Tesla Optimus, Figure AI, Agility Robotics, Apptronik, Unitree, UBTECH, Xiaomi, Fourier Intelligence, and EX Robots. The book examines how different design philosophies, cost structures, and regulatory environments shape humanoid development trajectories.

The book raises critical questions about the future of work, human dignity in automation, robot rights and consciousness, geopolitical competition in robotics, and the convergence of physical and digital intelligence. It provides frameworks for understanding these questions through technical depth, ethical analysis, and practical deployment considerations. As such, the book is intended for robotics and AI researchers, engineers, and graduate students in related fields who seek advanced insights into humanoid development and applications.

Ken Huang is a prolific book author and researcher in AI applications and Agentic AI Security, serving as CEO and Chief AI Officer at DistributedApps.ai. He is Co-Chair of AI Safety groups at the Cloud Security Alliance and the OWASP AIVSS project, and Co-Chair of the AI STR Working Group at the World Digital Technology Academy. He is an EC Council instructor and Adjunct Professor at the University of San Francisco, teaching GenAI Security and Agentic AI security for data scientists respectively. He coauthored OWASP's Top 10 for LLM Applications and contributes to the NIST Generative AI Public Working Group. His books are published by Springer, Cambridge, Wiley, Packt, and China Machine Press, including Securing AI Agents, LLM Design Patterns, Generative AI Security, Agentic AI Theories and Practices, Beyond AI and The Handbook for Chief AI Officers,  A frequent global speaker, he engages at major technology and policy forums.

Professor Chunxiao Xing is a Foreign Academician of the Russian Academy of Engineering. He is the Dean of the Tsinghua-Kelan Advanced Intelligent Database Research Institute, and Vice Dean of the Institute for Medical-Robotic Engineering Interdisciplinary Research at Tsinghua University, China. His research focuses on artificial intelligence, blockchain technology, big data,smart cities, and e-government. He has published over 380 academic papers, holds 43 invention patents and 33 software copyrights, and has led more than 40 major national research projects including National 973 Program, 863 Program, and National Key R&D projects. Professor Xing has received numerous honors including the National Science and Technology Progress Award (Second Class) and recognition as one of the "Metaverse 30" and "Blockchain 60" innovation leaders in China. He holds leadership positions in several professional organizations including the China Computer Federation, the Zhongguancun Blockchain Industry Alliance, and the Chinese Institute of Electronics Blockchain Branch.

Yuyan "Lynn" Duan is a product leader and angel investor at the forefront of AI and robotics innovation. As an early-stage investor, she has backed a robotics startup supported by Salesforce CEO Marc Benioff, Skild's founder, and Nat Friedman, as well as a healthcare LLM venture backed by Anthropic's co-founder. Known for writing first checks, Lynn has already seen one portfolio company advance to Series B funding. Since 2019, Lynn has served as Product Leader at Treasure Data, a pre-IPO customer data platform company, where she has architected roughly one-third of the company's product suite. She pioneered the company's AI transformation by creating its first AI Agent Framework, which has generated 30+ enterprise-grade agents and driven 30+ new customer engagements. Her work spans enterprise big data, data security, and AI-driven marketing solutions. In 2023, Lynn founded AI+, a thriving AI startup community with 50+ contributing members that has hosted 150+ events over two years, connecting 2,000+ founders annually with 200+ investors and corporate partners. She holds degrees from the University of Michigan (Psychology & Statistics, International Relations) and Georgia Tech (M.S. in Human-Computer Interaction with a Certificate in Management of Technology).