Papers

5

Total Citations

58

H-Index

4

About

Basma Gh. Elkilany is a leading researcher in swarm robotics and multi-agent systems, with a primary focus on formation control and adaptive navigation. Her work addresses the critical challenge of enabling robot swarms to move cohesively, avoid obstacles, and track targets in dynamic, unstructured environments. Elkilany’s major contributions center on optimizing the Potential Field Method (PFM) through fuzzy inference systems and adaptive algorithms, significantly improving the flexibility and robustness of decentralized formation control. Her most-cited paper, “Potential Field Method Parameters Tuning Using Fuzzy Inference System for Adaptive Formation Control of Multi-Mobile Robots” (2020), has garnered 20 citations, underscoring its influence in the field. She has also published key studies on optimized potential field methods for robot swarms (2017, 15 citations) and decentralized formation control (2020, 15 citations), collectively advancing the state of the art in swarm coordination. Additionally, her work on flexible capacitive-based tactile sensors (2015) demonstrates a broader interest in robotic sensing for unstructured environments. Elkilany’s research is foundational for applications such as search and rescue, forest fire detection, and autonomous exploration, making her a pivotal figure in modern robotics.

Research Focus

Key Achievements

4
H-Index
5
Papers
58
Total Citations
12
Avg Citations/Paper
🏆 Most Cited Paper
Potential Field Method Parameters Tuning Using Fuzzy Inference System for Adaptive Formation Control of Multi-Mobile Robots
20 citations · 2020
📈 Most Prolific Year: 2020 (2 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Tanta University, Egypt-Japan University of Science and Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago