Phillip Quin

University of Technology Sydney

Papers

10

Total Citations

154

H-Index

7

About

Phillip Quin’s research lies at the intersection of autonomous robotics, 3D exploration, and inspection of complex, hazardous environments. His major contributions center on developing efficient exploration algorithms for robots operating in challenging settings, particularly steel bridges and truss structures. His pioneering work on frontier-based exploration—including the Expanding Wavefront Frontier Detection (EWFD) algorithm—has advanced how robots detect unknown space, enabling faster and more autonomous map building. Quin’s research has practical impact in bridge inspection, where his climbing robot designs reduce the need for dangerous human work at heights. His most cited paper, “Efficient neighbourhood-based information gain approach for exploration of complex 3D environments” (37 citations), demonstrates his influence in the field. Other notable works include approaches for nearest neighbor exploration with backtracking and sliding window viewpoint selection, all aimed at improving exploration efficiency. With over 150 total citations across his publications, Quin’s work has shaped how robots autonomously inspect and map hard-to-reach infrastructure, making him a key figure in field robotics and autonomous exploration.

Research Focus

Key Achievements

7
H-Index
10
Papers
154
Total Citations
15
Avg Citations/Paper
🏆 Most Cited Paper
Efficient neighbourhood-based information gain approach for exploration of complex 3D environments
37 citations · 2013
📈 Most Prolific Year: 2013 (2 Papers)
🤝 Key Collaborators: 18
🏛 Institutions: University of Technology Sydney

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8
  9. 9
  10. 10

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago