Shahrizal Saat

Technical University of Malaysia Malacca

Papers

Total Citations

H-Index

About

Shahrizal Saat is a robotics researcher whose work centers on autonomous navigation, simultaneous localization and mapping (SLAM), and intelligent inspection systems. His most cited paper, "HECTORSLAM 2D Mapping for Simultaneous Localization and Mapping (SLAM)" (2020, 22 citations), demonstrates a practical application of LiDAR sensors for constructing 2D maps in unknown environments while enabling a robot to localize itself using detected landmarks—a foundational contribution to mobile robotics. In a second notable study (2018, 6 citations), Saat addresses a real-world infrastructure challenge by developing an autonomous robot for highway inspection, specifically targeting hazardous puddles that compromise driver safety during rain. This work bridges robotics and civil infrastructure, showcasing how autonomous systems can improve road maintenance and public safety. With a growing citation footprint, Saat’s research is valuable for students and engineers interested in SLAM algorithms, sensor fusion, and field robotics. His ability to translate complex mapping techniques into tangible inspection solutions highlights his impact on both academic robotics and practical engineering applications.