P.G.C.N. Senarathne
Papers
13
Total Citations
250
H-Index
9
About
P.G.C.N. Senarathne is a robotics researcher whose work centers on autonomous robot exploration, multi-robot systems, and 3D mapping — areas that address some of the most demanding challenges in deploying intelligent robots in complex, unstructured environments. His most influential contributions lie in developing sophisticated map fusion frameworks that enable multiple robots to collaboratively build coherent representations of their surroundings. His hierarchical probabilistic fusion framework (2018, 44 citations) and multilevel fusion system for heterogeneous sensors (2019, 42 citations) stand as landmark works, tackling the formidable problem of merging 3D occupancy maps in real-time distributed systems where robots may carry different sensor types. Senarathne has also made foundational contributions to frontier-based exploration, with multiple papers on efficient and safe frontier detection accumulating nearly 60 citations combined, shaping how autonomous robots identify and prioritize unexplored regions. His early development of MarineSIM demonstrated a breadth extending into marine robotics simulation. Across his career, his research has collectively amassed over 230 citations, reflecting meaningful influence on the robotics community and offering valuable guidance to researchers designing the next generation of collaborative autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 4Efficient frontier detection and management for robot exploration29 citations · 2013
- 5Towards autonomous 3D exploration using surface frontiers28 citations · 2016
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- 8MarineSIM: Robot simulation for marine environments12 citations · 2010
- 9Probabilistic Fusion Framework for Collaborative Robots 3D Mapping10 citations · 2018
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