Max Robotics — Global Service Robot Directory + US Certification

About

Ted Xiao is a prominent robotics and machine learning researcher whose work sits at the intersection of large language models, computer vision, and robotic control. His research focuses on enabling robots to understand and execute complex, natural-language instructions by grounding semantic knowledge in real-world physical affordances — a challenge at the frontier of embodied AI. Xiao has been a key contributor to Google's landmark Robotics Transformer series, with RT-1 and RT-2 together accumulating nearly 800 citations, demonstrating how transformer architectures and internet-scale vision-language models can be transferred directly into robotic control systems. His co-authorship on "Do As I Can, Not As I Say" (516 citations) helped establish a foundational framework for combining language model reasoning with practical robot capabilities. His work on "Inner Monologue" (206 citations) further advanced embodied reasoning through closed-loop language-based planning. Beyond individual models, Xiao has contributed to large-scale data infrastructure through the DROID dataset and open-source generalist policies like Octo, reflecting a commitment to democratizing robot learning research. Collectively, his papers have gathered well over 1,900 citations, underscoring his significant and growing influence in shaping the future of intelligent, language-guided robotics.