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About

Zhiyong Tang is a prominent robotics and control systems researcher whose work spans wearable exoskeleton technology, quadruped robotics, and intelligent control algorithms. His scholarship sits at the intersection of human-robot interaction, autonomous locomotion, and advanced perception systems, addressing both rehabilitation medicine and frontier robotics engineering. Tang's most influential contributions include a widely cited systematic review of lower extremity robotic exoskeletons (93 citations), which comprehensively mapped the landscape of assistive locomotion technology across medical, military, and industrial domains, and a highly regarded review of quadruped robots (88 citations) examining structural design, motion planning, and terrain adaptability. These works have become key reference points for researchers entering these fields. Beyond reviews, Tang has developed practical innovations including novel control strategies — such as Fuzzy PID-Variable Structure Adaptive Control for motor positioning and RBF neural network-based adaptive control for hydraulic parallel robots — alongside deep learning approaches for stair detection and depth-aware gait analysis in exoskeleton rehabilitation contexts. His prototype lower-limb exoskeleton, PTEXO, exemplifies his commitment to translating theory into functional assistive devices. With cumulative citations exceeding 290 across his top works, Tang represents a vital voice in the rapidly evolving field of assistive and autonomous robotics.