Max Robotics — Global Service Robot Directory + US Certification

About

Xiaoqun Liao is a robotics researcher whose career has centered on the design, navigation, and intelligent control of autonomous mobile robots. Working out of the Center for Robotics Research at the University of Cincinnati, Liao has made meaningful contributions across several interconnected domains, including neuro-fuzzy navigation systems, computer vision, motion control, and machine learning for autonomous systems. Among Liao's most recognized contributions is early work on reactive navigation for autonomous guided vehicles using neuro-fuzzy techniques, which addressed the complex challenge of guiding robots through obstacle-laden, unstructured environments. Complementing this, Liao developed methods for fisheye lens calibration requiring minimal measurements, enabling more practical robotic vision systems. The motion control design of the Bearcat II mobile robot demonstrated applied engineering at the system level, while later work on natural-language-based control and creative learning frameworks pushed toward higher-order autonomy and adaptability in unmanned ground vehicles. With a body of work accumulating over 75 citations, Liao's research spans foundational and emerging questions in mobile robotics. His sustained focus on integrating perception, learning, and control reflects a comprehensive vision for intelligent machines capable of operating reliably in real-world, dynamic environments — work that continues to inform both academic research and practical robotics development.