Max Robotics — Global Service Robot Directory + US Certification

About

Yutao Men is a researcher advancing the frontiers of robotics and computer-assisted intervention, with key contributions spanning lower limb exoskeletons, rescue robotics, and surgical gesture recognition. His work is unified by a focus on interactive information fusion and intelligent control for human-robot systems. Men’s most cited paper, "Gait Recognition for Lower Limb Exoskeletons Based on Interactive Information Fusion" (2022, 26 citations), addresses critical limitations in rehabilitation training by integrating multi-modal sensor data to improve gait phase detection. In rescue robotics, he has developed novel dynamics models for flexible manipulators and applied PSO-CPG algorithms to achieve invariably horizontal control for parallel mobile robots, enhancing stability in disaster response. Notably, Men has pioneered surgical gesture recognition in open surgery—a field traditionally focused on robotic procedures—using 3DCNN, SlowFast, and multi-head attention mechanisms to enable automated skills assessment and intraoperative guidance. With recent publications in 2024, his work is gaining traction, demonstrating impact in both clinical and emergency applications. Men’s interdisciplinary approach, combining mechanical design, control theory, and deep learning, positions him as an emerging leader in intelligent robotic systems for healthcare and disaster relief.