Hongde Qin
Papers
14
Total Citations
108
H-Index
6
About
Hongde Qin is a leading researcher in underwater robotics, specializing in intelligent control systems, bio-inspired design, and autonomous manipulation for marine environments. His major contributions lie in developing advanced adaptive control frameworks—particularly interval type-2 fuzzy logic systems—to address challenges like actuator faults, input saturation, and full-state constraints in multi-legged underwater robots. His work on fixed-time control with prescribed performance terminal sliding-mode surfaces (25 citations) and anti-windup compensators for trajectory tracking (24 citations) has significantly improved the robustness and precision of underwater locomotion. Qin has also pioneered bio-inspired robotic designs, including a novel robotic shark with enhanced maneuverability and a shape memory alloy-driven bionic jellyfish for jet propulsion. His recent innovations extend to formation control of autonomous underwater vehicles using potential field and fuzzy learning, as well as Koopman operator learning for real-time steering dynamics under ocean disturbances. Additionally, he has advanced underwater visual perception with efficient convolutional networks (G-Net) and binocular vision-based grasping for small targets. With over 100 citations across his top papers, Qin’s work is highly influential in marine robotics, offering practical solutions for aquaculture, seabed exploration, and autonomous underwater intervention.
Research Focus
Key Achievements
Top Papers
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- 3Mechatronic Design and Maneuverability Analysis of a Novel Robotic Shark10 citations · 2022
- 4A motion simulation of bionic jellyfish based on shape memory alloy8 citations · 2017
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- 8Learning strategies for underwater robot autonomous manipulation control5 citations · 2024
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