Tongsheng Shen

National University of Defense Technology

Papers

2

Total Citations

13

H-Index

2

About

Dr. Tongsheng Shen is a leading researcher in underwater robotics and geomagnetic navigation, whose work bridges bio-inspired sensing and advanced localization technologies. His primary research areas include underwater geomagnetic localization, particle filter optimization, and artificial lateral line (ALL) systems for flow estimation. Dr. Shen’s most cited work, “Underwater Geomagnetic Localization Based on Adaptive Fission Particle-Matching Technology” (2023, 10 citations), introduces an innovative adaptive fission approach to overcome particle degradation and impoverishment in particle filters—a critical challenge for robot navigation in GPS-denied environments. This contribution has significant implications for autonomous underwater vehicle (AUV) positioning. Additionally, his study “MrDMD-Based Sensor Placement in Distributed Flow Estimation for the Design of the Artificial Lateral Line of an Underwater Robot” (2023, 3 citations) tackles the open problem of optimal sensor placement in bio-inspired ALL systems, enhancing flow estimation capabilities for underwater robots. By integrating dynamic mode decomposition with sensor placement strategies, Dr. Shen advances the design of distributed sensing systems that mimic fish lateral lines. His work is foundational for improving the autonomy and environmental perception of underwater robots, with applications in ocean exploration, environmental monitoring, and defense. Dr. Shen’s research continues to shape the future of intelligent underwater systems.

Research Focus

Key Achievements

2
H-Index
2
Papers
13
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Underwater Geomagnetic Localization Based on Adaptive Fission Particle-Matching Technology
10 citations · 2023
📈 Most Prolific Year: 2023 (2 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: National University of Defense Technology

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago