Fatin Hassan Ajeil
Papers
8
Total Citations
595
H-Index
7
About
Fatin Hassan Ajeil is a prominent robotics and artificial intelligence researcher whose work centers on autonomous mobile robot navigation, path planning, and swarm intelligence optimization. With a career built around solving one of robotics' most complex challenges — enabling robots to navigate safely and efficiently through unpredictable environments — Ajeil has made substantial contributions to the field through the development of innovative hybrid and modified optimization algorithms. His most influential work, "Multi-objective path planning of an autonomous mobile robot using hybrid PSO-MFB optimization algorithm" (2020), has garnered an impressive 243 citations, establishing him as a leading voice in intelligent navigation systems. Closely following is his research on aging-based ant colony optimization for grid-based path planning, which has accumulated 194 citations and demonstrated practical applicability in both static and dynamic environments. His exploration of bat algorithm modifications and omnidirectional robot navigation further reflects his commitment to advancing swarm-based methodologies. Across his body of work, Ajeil consistently pursues shorter, safer, and smoother robot trajectories, blending bio-inspired computing with real-world robotics constraints. With a cumulative citation count exceeding 595, his research continues to serve as a foundational reference for engineers and scientists developing next-generation autonomous systems.
Research Focus
Key Achievements
Top Papers
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