Papers
5
Total Citations
527
H-Index
4
About
Zhicong Huang is a leading researcher in the field of rehabilitation robotics and human-robot interaction, with a primary focus on adaptive control systems for robotic exoskeletons. His most influential work, "Adaptive Impedance Control for an Upper Limb Robotic Exoskeleton Using Biological Signals" (2016), has garnered 319 citations and introduces a novel approach that integrates a calibrated musculoskeletal model with biological signals to enable intuitive, assistive motion. Building on this, his 2017 paper on "Adaptive Impedance Control of Human–Robot Cooperation Using Reinforcement Learning" (171 citations) pioneers the use of machine learning to allow robots to dynamically adapt their behavior during cooperative tasks, significantly enhancing performance and user experience. Huang’s contributions are foundational to creating exoskeletons that can learn and adjust in real-time, bridging the gap between human intent and robotic assistance. Beyond rehabilitation, his work extends to medical robotics, including a 2023 review on miniaturized percutaneous nephrolithotomy and early studies on CyberKnife stereotactic radiosurgery for lung tumors, demonstrating a versatile impact across surgical and assistive technologies. His research continues to shape the future of adaptive, human-centered robotics.
Research Focus
Key Achievements
Top Papers
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- 3Miniaturization in percutaneous nephrolithotomy: What is new?17 citations · 2023
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