Mohamad Shukor Talib

Papers

Total Citations

157

H-Index

About

Mohamad Shukor Talib is a researcher whose work lies at the intersection of artificial intelligence, mobile robotics, and autonomous navigation. His primary research focus is on Simultaneous Localization and Mapping (SLAM), a critical technique that enables robots to explore and map unknown environments while keeping track of their own position. Talib’s most cited work, the 2015 review "Review on simultaneous localization and mapping (SLAM)," has garnered 150 citations, establishing itself as a foundational resource for researchers entering this rapidly evolving field. Beyond this comprehensive survey, Talib has made notable contributions to improving SLAM performance through hybrid optimization. His 2017 paper, "GA-PSO-FASTSLAM: A Hybrid Optimization Approach in Improving FastSLAM Performance," introduces a novel fusion of Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) to enhance the accuracy and efficiency of the FastSLAM algorithm. This work demonstrates Talib’s commitment to pushing the boundaries of autonomous navigation, offering practical solutions for real-world robotic applications. Through his research, Talib continues to shape the development of intelligent, self-exploring systems.