Papers

2

Total Citations

17

H-Index

1

About

Haining Lu is a researcher specializing in underwater robotics and autonomous navigation, with a particular focus on localization and odometry for deep-sea vehicles. His major contributions lie in developing robust sensor fusion algorithms that enable precise positioning in challenging underwater environments where GPS is unavailable. His most cited work, "Error-state Kalman filter-based localization algorithm with velocity estimation for deep-sea mining vehicle" (2022, 16 citations), presents an innovative approach that integrates inertial sensors with velocity estimation to improve localization accuracy for vehicles operating on the seafloor. More recently, Lu has advanced the field with "Direct Forward-Looking Sonar Odometry: A Two-Stage Odometry for Underwater Robot Localization" (2025), which addresses the critical need for fast, accurate localization during near-bottom operations by leveraging forward-looking sonar imagery. This work tackles the limitations of traditional methods like acoustic baseline localization and dead reckoning, offering a promising solution for real-time underwater navigation. Lu's research has direct applications in deep-sea mining, marine exploration, and autonomous underwater vehicle operations, making him a notable contributor to the advancement of underwater robotics technology.

Research Focus

Key Achievements

1
H-Index
2
Papers
17
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
Error-state Kalman filter-based localization algorithm with velocity estimation for deep-sea mining vehicle
16 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Shanghai Ocean University, Shanghai Jiao Tong University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago