Awantha Jayasiri
Papers
3
Total Citations
19
H-Index
2
About
Awantha Jayasiri is an emerging robotics and autonomous systems researcher whose work sits at the intersection of aerial navigation, sensor fusion, and simultaneous localization and mapping (SLAM). His most significant contribution to date is the MUN-FRL dataset — a comprehensive visual-inertial-LiDAR collection captured via a DJI-M600 hexacopter across flight distances of 300 meters to 5 kilometers — which has quickly gained traction in the GNSS-denied navigation community, accumulating 16 citations since its 2024 release. This dataset addresses a critical gap in aerial autonomy research by providing richly annotated multi-sensor data for environments where satellite positioning is unavailable or unreliable. Complementing this, Jayasiri developed an aeronautical-grade, interchangeable payload unit capable of executing visual-inertial-LiDAR odometry and mapping algorithms in real time across platforms ranging from full-scale Bell 412 helicopters to compact drones, demonstrating a practical commitment to scalable hardware solutions. His work also extends to ground robotics, where he has explored CNN-based visual place recognition paired with Google Indoor Street View for robust indoor localization using factor graph frameworks. Collectively, Jayasiri's research reflects a coherent and impactful vision for resilient, sensor-rich autonomous navigation across diverse aerial and ground platforms.
Research Focus
Key Achievements
Top Papers
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