Nafiseh Osati Eraghi
Universidad Autónoma de Madrid, Islamic Azad University, Arak
Papers
4
Total Citations
59
H-Index
4
About
Nafiseh Osati Eraghi is a researcher specializing in autonomous robot navigation and intelligent optimization for wireless sensor networks. Her work focuses on developing efficient path planning algorithms for low-cost robots with limited computational resources and energy supply. Her major contributions include the creation of HCTNav, a path planning algorithm designed specifically for resource-constrained embedded systems, and NafisNav, a memory-efficient navigation algorithm for grid maps. These algorithms address critical challenges in indoor navigation, offering alternatives to traditional methods like A* and Dijkstra by prioritizing low memory usage and energy efficiency. Her research has garnered attention, with her most-cited paper, "HCTNav: A Path Planning Algorithm for Low-Cost Autonomous Robot Navigation in Indoor Environments," receiving 24 citations. In 2022, she expanded into multiobjective optimization for wireless sensor networks, using the Grey Wolf Optimization algorithm to enhance quality of service (QoS) in environmental monitoring applications. Her work bridges the gap between theoretical path planning and practical deployment in low-cost robotic systems, making her contributions valuable for students and researchers interested in embedded systems, robotics, and network optimization.
Research Focus
Key Achievements
Top Papers
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