Ahmad Sufril Azlan Mohamed
Papers
6
Total Citations
157
H-Index
5
About
Ahmad Sufril Azlan Mohamed is a leading researcher in mobile robotics and human-robot interaction, whose work has garnered over 150 citations. His primary research areas include path planning optimization, educational robotics, and speech recognition systems. Mohamed's most impactful contribution is his "Improved genetic algorithm for mobile robot path planning in static environments" (2024, 107 citations), which significantly enhanced autonomous navigation efficiency. He has also advanced the field with his "Optimised path planning using Enhanced Firefly Algorithm for a mobile robot" (2024, 6 citations) and "Efficient Pathfinding on Grid Maps" (2025, 4 citations), demonstrating his sustained focus on algorithmic innovation. During the COVID-19 pandemic, Mohamed provided critical insights through his survey on robotics in education (2021, 20 citations), examining how platforms like NAO robots could support remote learning. His work on "A New Speech Recognition Model in a Human-Robot Interaction Scenario Using NAO Robot" (2021, 8 citations) further showcases his expertise in creating intuitive robotic interfaces. Mohamed's research bridges theoretical optimization with practical applications, making significant contributions to autonomous systems and educational technology.
Research Focus
Key Achievements
Top Papers
- 1Improved genetic algorithm for mobile robot path planning in static environments107 citations · 2024
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