Intan Mastura Saadon
Papers
1
Total Citations
3
H-Index
1
About
Intan Mastura Saadon is a researcher whose work lies at the intersection of robotics, swarm intelligence, and sensor-based navigation. Her key research areas include odor sensing localization, autonomous robot movement, and the application of metaheuristic algorithms like Particle Swarm Optimization (PSO) to solve complex spatial problems. In her most cited work, "Particle Swarm Optimization (PSO) for Simulating Robot Movement on Two-Dimensional Space Based on Odor Sensing" (2017), she pioneered a simulation framework that enables robots to navigate toward odor sources using PSO, a nature-inspired algorithm. This contribution is significant for advancing autonomous search-and-rescue operations, environmental monitoring, and industrial safety, where robots must locate chemical leaks or hazardous materials without human intervention. While her citation count is currently modest at 3, her work represents an early and foundational step in integrating swarm intelligence with olfactory sensing—a niche but rapidly growing field. Saadon’s research demonstrates a forward-looking approach to robotics, bridging theoretical optimization with practical sensor-driven navigation, and lays groundwork for future innovations in autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1