Max Robotics — Global Service Robot Directory + US Certification

About

Min Tan is a prominent robotics and control systems researcher whose work spans adaptive control theory, biomimetic robotics, and underwater autonomous systems. Based at the Institute of Automation, Chinese Academy of Sciences, Tan has made significant contributions across several interconnected domains that together advance the frontier of intelligent robotic systems. His most influential contribution — a 2009 paper on adaptive control of electrically driven nonholonomic mobile robots (242 citations) — demonstrated a sophisticated fusion of backstepping methodology and fuzzy logic to handle model uncertainties across kinematic, dynamic, and actuator levels, establishing him as a leading voice in robust adaptive control. This work remains a cornerstone reference for researchers tackling real-world robot motion control challenges. Equally notable is Tan's sustained investment in biomimetic robot fish, where he pioneered multi-link free-swimming designs governed by biologically inspired Central Pattern Generator (CPG) controllers and kinematic propulsive models. This body of work, spanning from 2005 through 2019, reflects a long-term vision for underwater robotic locomotion that mirrors nature's elegance. His broader interests further extend to underwater wireless sensor networks, nano-scale displacement measurement for micro-manipulation, and vision-based pan-tilt tracking systems — painting the portrait of a versatile researcher whose work bridges theory and application across some of robotics' most challenging environments.