Announcements

We are delighted to invite the winner of the Drones 2024 Best Paper Award, Dr. Seonah Lee, to discuss her article, “FANET Routing Protocol Analysis for Multi-UAV-Based Reconnaissance Mobility Models”. The paper was published in Drones (ISSN: 2504-446X) and has received a significant amount of positive feedback from our readers. We hope you enjoy the interview:

1. Congratulations on your published paper and the award it has received! Could you briefly introduce the key research focus and main findings of your paper?
Thank you very much. Our award-winning paper analyzed FANET (Flying Ad Hoc Network) routing protocols in multi-UAV reconnaissance missions. We evaluated how mobility models and routing protocols interact in scenarios needing wide coverage and unpredictable movement. AODV combined with SRWP showed the best packet delivery ratio. This offers useful guidance for real-world UAV networks.

2. Could you share a bit about your academic background and what first inspired your interest in this field of research?
I have a background in software engineering. I was employed as a Professor in the Department of Aerospace and Software Engineering in 2016. Since then, I have been seeking a contribution to aerospace engineering as a software engineer. Now, I focus on this field to make unmanned aerial systems more adaptive, reliable, and mission-capable.

3. During the course of this study, did you encounter any significant challenges? If so, how did you address and overcome them?
FANETs inherently suffer from low node density and a highly dynamic topology. This made it difficult to ensure consistent network connectivity and reliable packet delivery in simulations. To address this, we implemented a trace-based simulation approach using a custom mobility model simulator, allowing us to repeat experiments under consistent movement patterns and rigorously assess routing performance.

4. What was your specific role within the research team, and how did collaboration with your colleagues contribute to the paper’s success?
As the corresponding author, I guided the overall direction of the research and supported the first author, Taehwan Kim, in conducting experiments and data analysis. I helped structure the research scenario and ensured the experimental design aligned with the study’s objectives. Together with the other co-authors, I reviewed and revised the manuscript to improve its clarity and completeness.

5. Looking ahead, what impact do you hope your research will have on the field, and what do you consider the paper’s most important innovation?
Looking ahead, I hope this research will provide a meaningful foundation for developing routing protocols tailored to real-world multi-UAV reconnaissance missions. By clearly analyzing the performance of different routing protocols under diverse mobility models, the study offers practical insights for optimizing communication in rapidly changing aerial networks.

6. In your view, how does open access publishing contribute to the dissemination of knowledge and the advancement of research in your area?
Open access is essential in fast-moving, interdisciplinary fields like UAV or AI systems. It ensures that researchers, developers, and industry practitioners around the world can access the latest findings. I prefer to publish our papers in open access publishing, thanks to the easy and speedy sharing of our research results.

7. Finally, what are your current short-term and long-term research goals?
In the short term, we're focusing on our reinforcement learning framework. Our latest paper, published in Drones, presents a data-efficient reinforcement learning framework for autonomous flight. In this work, we present a model-based reinforcement learning setup to overcome the data scarcity issue that is typical in real-world autonomous flight systems.
In the long term, I envision this research supporting scalable, safe autonomous flight systems—including multiple drone systems—that can collaboratively adapt to uncertain and dynamic environments.