Ashanie Guanathillake

Commonwealth Scientific and Industrial Research Organisation

Papers

1

Total Citations

3

H-Index

1

About

Ashanie Guanathillake is a researcher whose work lies at the intersection of distributed sensor networks, robust estimation, and autonomous target tracking. Her most-cited paper, "Robust Kalman filter‐based decentralised target search and prediction with topology maps" (2017), introduces a novel distributed framework for searching and tracking targets in environments where physical distance measurements—such as signal strength—are unavailable. By fusing a robust Kalman filter with nonlinear least-squares methods, Guanathillake’s approach enables effective target localization using only topological map information, a significant advancement for sensor networks operating under communication or hardware constraints. Though her citation count remains modest, this work demonstrates her ability to address real-world challenges in decentralized robotics and environmental monitoring. Her contributions are particularly valuable for researchers exploring resilient multi-agent systems and low-infrastructure sensing. Guanathillake’s research underscores the importance of algorithmic robustness in uncertain, communication-limited settings—a critical direction for the future of autonomous search-and-rescue, wildlife tracking, and smart infrastructure.

Research Focus

Key Achievements

1
H-Index
1
Papers
3
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Robust Kalman filter‐based decentralised target search and prediction with topology maps
3 citations · 2017
📈 Most Prolific Year: 2017 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: Commonwealth Scientific and Industrial Research Organisation

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago