Izzati Saleh
Papers
6
Total Citations
34
H-Index
3
About
Izzati Saleh is a rising researcher in robotics, specializing in bio-inspired optimization and autonomous navigation for mobile robots. Her work focuses on developing intelligent path planning algorithms that enable robots to navigate complex, GNSS-denied environments with greater efficiency and smoothness. She has made key contributions by integrating bio-inspired population-based optimization (BPO) methods—such as the Modified Whale Optimization Algorithm—with classical planners like Rapidly Exploring Random Trees (RRT) to overcome issues like jagged paths and local minima. Her most cited papers, including a comprehensive technical review on BPO algorithms for path planning and a study on reducing UWB indoor localization error using Kalman and moving average filters, each have garnered 12 citations, reflecting growing interest in her practical, hybrid approaches. Saleh has also advanced indoor localization and pure-pursuit control for nonholonomic robots in confined spaces. Her 2025 work on RRT-MWOAII demonstrates her ongoing commitment to balancing computational efficiency with path quality. With publications spanning 2022 to 2025, Saleh is establishing herself as a thoughtful contributor to the next generation of autonomous robotic navigation.
Research Focus
Key Achievements
Top Papers
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