Diluka Moratuwage
Nanyang Technological University, University of Chile, Central Queensland University
Papers
9
Total Citations
140
H-Index
6
About
Diluka Moratuwage is a robotics researcher whose work bridges multi-vehicle autonomous navigation, simultaneous localization and mapping (SLAM), and human–machine interfacing. His early contributions advanced collaborative SLAM in dynamic, high-clutter environments, notably developing a hierarchical, random finite set (RFS)-based framework for multi-vehicle SLAM that enables robust map fusion without requiring constant data sharing between robots. His most cited work, “Collaborative Multi-vehicle SLAM with moving object tracking” (34 citations), addresses the practical challenge of operating in environments with moving obstacles. Moratuwage also introduced the δ-Generalized Labeled Multi-Bernoulli SLAM approach (26 citations), which uses optimal kernel-based particle filtering to overcome heuristic-based data association failures. Beyond navigation, he has made significant contributions to 3D occupancy grid map fusion (24 citations) and, more recently, to electromyography (EMG) signal processing for exoskeleton control, with two 2025–2026 publications already accumulating 22 citations. His work on MarineSIM (12 citations) provided a critical simulation platform for marine robotics. Moratuwage’s research consistently addresses real-world deployment challenges—from underwater exploration to wearable robotics—demonstrating a rare ability to span theoretical SLAM foundations and applied human–robot interaction.
Research Focus
Key Achievements
Top Papers
- 1Collaborative Multi-vehicle SLAM with moving object tracking34 citations · 2013
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- 5A hierarchical approach to the Multi-Vehicle SLAM problem15 citations · 2012
- 6MarineSIM: Robot simulation for marine environments12 citations · 2010
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