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About

Yongzhuo Gao is a versatile robotics researcher whose work spans industrial automation, wearable assistive technologies, and medical robotics. His research has made significant contributions across multiple interconnected domains, establishing him as a productive and broad-minded engineer-scientist. In industrial robotics, Gao has advanced precision manufacturing through innovations in hand-eye calibration using 3D reconstruction (103 citations), robotic milling based on point cloud data, and force-controlled belt grinding for free-form surfaces. His early work on trajectory optimization using an improved teaching-learning-based algorithm further demonstrated his commitment to intelligent robotic motion planning. Perhaps most notably, Gao has emerged as a leading voice in wearable and assistive robotics. His GA-CNN-based locomotion mode recognition system for lower limb exoskeletons (72 citations) addressed the critical challenge of subject-specific training, while his widely read review of soft wearable robots (51 citations) synthesized the field's development status and technical hurdles. His work on mechanomyography-driven joint torque estimation and systematic exoskeleton reviews further cements this expertise. Gao has also contributed to surgical robotics, developing a hand-held prostate biopsy robot with remote center of motion and a fiber Bragg grating-based force sensing system for laryngeal surgery. With over 390 cumulative citations, his interdisciplinary contributions continue to shape next-generation human-robot interaction systems.