Abdul Jalil
Papers
1
Total Citations
141
H-Index
1
About
Abdul Jalil is a prominent researcher in the fields of autonomous robotics, optimization algorithms, and computational intelligence. His work focuses on developing meta-heuristic approaches to solve complex engineering problems, particularly in multi-objective path planning for autonomous guided robots. His most-cited paper, "Meta-heuristic approach for solving multi-objective path planning for autonomous guided robot using PSO–GWO optimization algorithm with evolutionary programming" (2020), has garnered 141 citations, demonstrating its significant impact on the robotics and optimization communities. Jalil's major contribution lies in hybridizing particle swarm optimization (PSO) and grey wolf optimizer (GWO) with evolutionary programming, offering efficient solutions for real-time navigation challenges. His research not only advances theoretical frameworks but also provides practical algorithms for autonomous systems, making him a key figure in the development of intelligent, adaptive robots. With over 140 citations on this single work, Jalil’s influence continues to grow, inspiring further innovations in autonomous navigation and multi-objective optimization.
Research Focus
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Top Papers
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