Ali Yeon Md Shakaff
Papers
13
Total Citations
180
H-Index
8
About
Ali Yeon Md Shakaff is a leading researcher in mobile robotics, sensor fusion, and gas sensing, whose work bridges the gap between autonomous navigation and environmental monitoring. His major contributions lie in integrating Simultaneous Localization and Mapping (SLAM) with gas distribution mapping, enabling robots to localize gas sources in real time—a critical capability for search-and-rescue and industrial safety. His highly cited paper on mapping mobile robots using RP Lidar scanners (35 citations) and his work on converting Kinect 3D depth data to 2D maps for indoor SLAM (31 citations) have advanced low-cost, accessible robotic mapping. Shakaff’s research on metal oxide gas sensor cross-sensitivity to temperature and humidity (13 citations) has improved the reliability of gas distribution models, while his exploration of Grey Wolf Optimizer for gas source localization (9 citations) showcases innovative bio-inspired algorithms. With a portfolio spanning multi-sensor data fusion, swarm robotics for odor plume tracking, and autonomous sensor characterization systems, Shakaff has earned over 170 citations, demonstrating his impact on practical, real-world robotic applications. His work continues to inspire students and researchers aiming to create smarter, more responsive autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1A mapping mobile robot using RP Lidar scanner35 citations · 2015
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- 3Method to convert Kinect's 3D depth data to a 2D map for indoor SLAM31 citations · 2013
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- 6Mobile robot localization system using multiple ceiling mounted cameras12 citations · 2015
- 7Gas Source Localization using Grey Wolf Optimizer9 citations · 2018
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- 9Braitenberg swarm vehicles for odour plume tracking in laminar airflow8 citations · 2013
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