Alif Ridzuan Khairuddin

Papers

Total Citations

157

H-Index

About

Alif Ridzuan Khairuddin is a leading researcher in autonomous robotics, specializing in simultaneous localization and mapping (SLAM) and intelligent optimization algorithms. His seminal 2015 review, “Review on simultaneous localization and mapping (SLAM),” with 150 citations, remains a foundational resource for students and engineers exploring SLAM’s role in enabling mobile robots to autonomously navigate unknown environments. This work systematically clarifies SLAM’s core challenges—such as sensor fusion and loop closure—and has shaped subsequent research in self-driving vehicles and exploration robotics. Building on this foundation, Khairuddin introduced the GA-PSO-FASTSLAM hybrid optimization approach in 2017, which combines genetic algorithms and particle swarm optimization to significantly improve FastSLAM’s accuracy and computational efficiency. This innovative method addresses persistent issues in landmark estimation and particle depletion, offering a practical solution for real-time deployment. With his contributions bridging theoretical frameworks and applied optimization, Khairuddin’s work continues to influence the development of robust, scalable SLAM systems for field robotics and intelligent automation.