Liangwei Deng

Shandong Institute of Automation, Beijing Academy of Artificial Intelligence, University of Chinese Academy of Sciences

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About

Liangwei Deng is a researcher at the forefront of bioinspired robotics, specializing in the design, modeling, and control of robotic fish. His work centers on replicating the exceptional swimming abilities of real fish by focusing on variable stiffness mechanisms and compliant structures. Deng’s major contributions include the development of a fishlike propeller with a compressible flexible bionic spine, which mimics the dynamic stiffness changes in fish muscles to enhance propulsion efficiency. He has also advanced the field through dynamic modeling of tuna-inspired robots using elastic-damping mechanisms, addressing the challenge of achieving consistent performance across a wide frequency range. With his most-cited papers accumulating over 19 citations, Deng’s research has laid critical groundwork for more agile and efficient underwater robots. Notably, his recent survey on reinforcement learning methods in robotic fish highlights his forward-looking approach, exploring how AI-driven control can enable autonomous adaptation without requiring complex dynamic models. Deng’s work is essential reading for students and researchers interested in the intersection of biomechanics, soft robotics, and intelligent control systems.