Syed Muhammad Mamduh Syed Zakaria
Papers
14
Total Citations
160
H-Index
8
About
Syed Muhammad Mamduh Syed Zakaria is a leading researcher in mobile robotics and olfaction, whose work bridges the critical gap between robot perception and environmental sensing. His primary research areas include Simultaneous Localization and Mapping (SLAM), gas distribution mapping, and gas source localization—fields where he has made foundational contributions. His most cited work, a 2014 performance analysis of the Microsoft Kinect sensor for 2D SLAM (41 citations), demonstrated how low-cost sensors could effectively replace laser scanners for mapping, significantly lowering the barrier to entry in robotics research. He further advanced the field by integrating SLAM with gas distribution mapping (SLAM-GDM, 31 citations), enabling real-time gas source localization—a breakthrough for environmental monitoring and disaster response. His innovative use of reinforcement learning for multi-target path planning in unknown environments (2023, 14 citations) and application of the Grey Wolf Optimizer for gas source localization (2018, 9 citations) showcase his ability to blend AI with practical robotics. Additionally, his development of a scalable testbed for mobile olfaction verification (2015, 9 citations) and flexible gas sensor characterization system (2014, 9 citations) have provided essential tools for the research community. With over 140 total citations across his publications, Zakaria’s work continues to inspire new approaches in autonomous navigation and environmental sensing.
Research Focus
Key Achievements
Top Papers
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- 4Gas Source Localization using Grey Wolf Optimizer9 citations · 2018
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- 6Development of a Scalable Testbed for Mobile Olfaction Verification9 citations · 2015
- 7Braitenberg swarm vehicles for odour plume tracking in laminar airflow8 citations · 2013
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