Hieu Dang Van

Papers

2

Total Citations

11

H-Index

2

About

Hieu Dang Van is a rising researcher in autonomous robotics, specializing in exploration, 3D mapping, and sensor fusion for aerial and ground robots. His work addresses critical challenges in real-time navigation and environmental perception. In his highly cited 2023 paper, he introduced an enhanced sampling-based exploration method with a modified next-best view strategy, significantly improving the efficiency of autonomous exploration for Unmanned Aerial Vehicles (UAVs) and Micro Aerial Vehicles (MAVs) in 3D outdoor environments. This work, garnering 6 citations, optimizes both destination planning and path utility. Complementing this, his 2023 study on sensor fusion for indoor 3D mapping achieved 5 citations by accelerating the implementation speed and accuracy of the RTAB-Map algorithm, tackling real-time embedding issues and positioning errors. Together, these contributions demonstrate his impact on advancing autonomous navigation systems. Hieu’s research is pivotal for applications in robotics, from industrial inspection to search-and-rescue, marking him as a promising innovator in the field.

Research Focus

Key Achievements

2
H-Index
2
Papers
11
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
An Enhanced Sampling-Based Method with Modified Next-Best View Strategy For 2D Autonomous Robot Exploration
6 citations · 2023
📈 Most Prolific Year: 2023 (2 Papers)
🤝 Key Collaborators: 8

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago