Hoang-Anh Phan

Papers

3

Total Citations

15

H-Index

3

About

Hoang-Anh Phan is an emerging robotics and autonomous systems researcher whose work spans robot exploration, 3D environmental mapping, and industrial automation. With a growing body of citations across multiple publication years, Phan has established a focused research identity at the intersection of autonomous navigation and practical robotic applications. Among Phan's most recognized contributions is an enhanced sampling-based method for 2D autonomous robot exploration, which refines next-best view strategies to optimize path planning for UAVs and micro aerial vehicles operating in complex environments. This work, garnering 6 citations, reflects a meaningful advance in exploration utility functions for three-dimensional outdoor robotics. Complementing this, Phan's sensor fusion approach to RTAB-Map-based indoor 3D mapping — with 5 citations — addresses real-world challenges of positioning accuracy and computational efficiency, pushing the boundaries of reliable real-time mapping in complex indoor spaces. Phan also demonstrates a strong applied engineering sensibility, developing vision systems that improve pick-and-place robot reliability for precision smartphone camera module testing, earning 4 citations from the industrial robotics community. Collectively, these contributions signal a researcher bridging theoretical autonomy algorithms with high-stakes manufacturing and navigation applications, making Phan a notable voice in applied robotics research.

Research Focus

Key Achievements

3
H-Index
3
Papers
15
Total Citations
5
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: 13

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago