Jiarong Han
Papers
4
Total Citations
15
H-Index
3
About
Jiarong Han is a rising leader in the field of bio-inspired underwater robotics, with a research focus on the dynamic modeling, precise control, and autonomous perception of bionic robotic fish. Han’s major contributions bridge the gap between theoretical hydrodynamics and practical robotic autonomy. Their work on orientation control and target tracking, published in 2023, introduced an Active Disturbance Rejection Control (ADRC) strategy for robotic fish, leveraging computational fluid dynamics to achieve stable swimming and turning. To address the challenges of underwater vision, Han developed a lightweight object detection algorithm based on YOLOv8, featuring an adaptive image enhancement module that improves real-time performance without heavy computational cost. Further advancing the field, Han pioneered a data-assisted dynamic modeling method that combines Lagrangian mechanics with machine learning to achieve precise speed control. Most recently, their 2025 work on vision-based obstacle avoidance and formation control integrates hyperparameter neural networks into the YOLOv8 framework, enabling multi-robot coordination in complex underwater environments. With over 15 citations across these key papers, Han’s contributions are shaping the next generation of autonomous underwater vehicles, making them a researcher to watch in marine robotics.
Research Focus
Key Achievements
Top Papers
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