Weilun Situ
Papers
1
Total Citations
7
H-Index
1
About
Weilun Situ is a researcher advancing autonomous systems in challenging marine environments, with a primary focus on visual-based tracking and control for autonomous underwater vehicles (AUVs). His most-cited work, "A Method for Long-Term Target Anti-Interference Tracking Combining Deep Learning and CKF for LARS Tracking and Capturing" (2023), addresses a critical bottleneck in AUV recycling—maintaining robust visual lock under harsh sea conditions. By fusing deep learning with a Cubature Kalman Filter (CKF), Situ’s method significantly improves long-term anti-interference tracking, enabling reliable AUV docking and capture even in turbulent, low-visibility waters. This contribution directly supports the sustainable exploitation of marine resources by enhancing the autonomy and safety of underwater recovery operations. With 7 citations in a short time, his work is gaining traction among researchers in marine robotics and computer vision. Situ’s research sits at the intersection of deep learning, sensor fusion, and practical ocean engineering, offering tangible solutions for real-world underwater missions.
Research Focus
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Top Papers
- 1