Papers
36
Total Citations
549
H-Index
14
About
Keping Liu is a distinguished robotics and control systems researcher whose work bridges advanced theoretical frameworks with practical rehabilitation and robotic applications. His research spans three interconnected domains: intelligent control of modular robot manipulators, lower limb rehabilitation robotics, and neurodynamic computing algorithms. Liu has made significant contributions to decentralized neuro-optimal control strategies for modular and reconfigurable robots, developing critic-only and critic-identifier adaptive dynamic programming architectures that enable robots to operate robustly in uncertain, contact-rich environments — work reflected across several highly cited publications from 2017 to 2021 accumulating over 150 combined citations. His zero-sum game-theoretic approaches to disturbance rejection represent particularly innovative theoretical advances in this space. Equally impactful is his research in rehabilitation engineering, where he designed and evaluated wearable lower limb rehabilitation robots and pioneered human-in-the-loop adaptive iterative learning control strategies, earning nearly 100 citations across related works. His noise-tolerant zeroing neurodynamic algorithms further extend these capabilities to real-time human-robot interaction under non-ideal conditions. With a research portfolio exceeding 345 citations across his top works alone, Liu's scholarship meaningfully advances both the theoretical foundations and clinical applicability of intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
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- 2Development and Evaluation of a Wearable Lower Limb Rehabilitation Robot48 citations · 2022
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