Pu Duan

Beijing Institute of Technology, IR Dynamics (United States)

Papers

Total Citations

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About

Pu Duan is a leading researcher in the field of physical human-robot interaction, with a focus on exoskeletal robotics and variable impedance control. His work addresses critical challenges in creating safe, responsive, and adaptive robotic systems that can seamlessly collaborate with humans. Duan’s major contributions include the development of bio-inspired algorithms for real-time locomotion prediction, enabling exoskeletons to anticipate human movement and reduce control delays—a breakthrough with implications for rehabilitation and assistive technologies. His most cited paper, "Bio-Inspired Real-Time Prediction of Human Locomotion for Exoskeletal Robot Control" (2017, 9 citations), lays the foundation for this work. Duan has also advanced variable stiffness control under strict frequency-domain constraints (2020, 4 citations) and introduced a multi-objective admittance control method using linear matrix inequalities (2022, 2 citations), which balances accuracy, passivity, and robustness in human-robot systems. His research is instrumental in improving the safety and performance of collaborative robots, with applications in industrial automation, prosthetics, and wearable robotics. Duan’s innovative approaches continue to shape the future of human-robot interaction, making him a notable figure in the field.