Papers
8
Total Citations
160
H-Index
6
About
Junzheng Zheng is a robotics researcher specializing in biomimetic underwater robotics, with particular expertise in bio-inspired sensing, dynamic modeling, and intelligent control systems for robotic fish. His work sits at a compelling intersection of biology and engineering, drawing inspiration from natural fish sensory systems to solve fundamental challenges in underwater robot navigation and control. Zheng's most influential contribution applies reinforcement learning and sim-to-real transfer techniques to the attitude control of robotic fish in real-world flow conditions, garnering 53 citations and demonstrating a practical end-to-end approach to handling complex fluid dynamics. Complementing this, his research on artificial lateral line systems — biologically inspired flow-sensing arrays modeled after fish sensory organs — has advanced leader-follower formation control and attitude stabilization in underwater robots, collectively attracting nearly 40 citations across multiple studies. His work on electric sense-based localization offers innovative solutions for small underwater robots operating in GPS-denied, visually limited environments, providing alternatives where cameras and sonar fall short. Additionally, his three-dimensional dynamic modeling research provides rigorous theoretical foundations for multi-mode underwater locomotion analysis. Across his career, Zheng has accumulated over 160 citations, establishing himself as a rising contributor to intelligent underwater robotics and bio-inspired sensing technologies.
Research Focus
Key Achievements
Top Papers
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- 4Dual-sensor fusion based attitude holding of a fin-actuated robotic fish20 citations · 2020
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- 7Azimuth Estimation of Swimming Fish by Artificial Lateral Line System4 citations · 2023
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