Unmanned aerial vehicles (UAVs) are increasingly used to survey remote or difficult-to-access areas, including mountains, forests, and disaster-stricken regions. Rather than relying on a single drone, researchers can deploy fleets of UAVs that work together to cover a wider area. These fleets form what is known as a flying ad hoc network (FANET), in which UAVs act as mobile communication nodes and exchange images, environmental data, and status information with one another and with a ground station.
Reliable communication is therefore essential for multi-UAV surveying. However, flight-path planning and communication-network management have often been treated as separate problems. A route that enables efficient area coverage may take some UAVs too far from their communication partners, while a network designed primarily to preserve connectivity may produce inefficient flight paths. In addition, maintaining too many communication links can increase interference and reduce the efficient reuse of the wireless spectrum.
To address these challenges, a research team led by Associate Professor Haihua Chen of Nankai University, China, has developed a framework that jointly optimizes UAV trajectories and FANET topology while maximizing the amount of data transmitted through the network. Their findings were published in Volume 13, Issue 6 of the IEEE/CAA Journal of Automatica Sinica on July 3, 2026.
The proposed method solves the problem in stages. First, a reinforcement-learning-based trajectory-planning algorithm determines how the UAVs should visit their assigned waypoints while satisfying communication constraints. In particular, the method requires each UAV to maintain communication with at least a specified number of neighboring UAVs. The framework then optimizes the network topology and establishes suitable transmit-power ranges. Finally, a convex optimization procedure adjusts the transmit powers to maximize the total data throughput while preserving the required network structure.
The researchers evaluated the approach using computer simulations of a mountainous region in Wanglang, Sichuan, China. The UAVs were tasked with visually covering a 2 km × 2 km area while maintaining communication links during the mission. The team also conducted field experiments at Wanghai Mountain in Tianjin, China, using three octocopter UAVs equipped with the NexFi MFS series ad hoc data communication module.
In the field experiment, the proposed method achieved a reported throughput of 91.39 Kb/s, outperforming the three comparison methods tested under the same hardware conditions. The researchers also evaluated the network’s ability to remain connected when UAVs were sequentially disconnected. The proposed approach maintained stronger connectivity than the comparison methods because it explicitly required each UAV to retain multiple neighboring links.
“ Simulation and field-experiment results show that the proposed optimization strategy can effectively plan UAV trajectories and significantly improve FANET data throughput compared with other well-established optimization methods, ” remarks Dr. Chen.
The findings demonstrate the advantages of treating flight planning and network communication as a combined optimization problem rather than as two independent tasks. Such an approach could support more efficient and reliable multi-UAV missions for environmental monitoring, disaster response, mapping, and other wide-area surveying applications.
The researchers describe the study as a foundation for further work on UAV fleet coordination. “ Our future work will focus on developing online multi-UAV task-scheduling and topology self-healing strategies to improve adaptability and robustness in dynamic environments ,” concludes Dr. Chen.
Reference
Title of original paper: Optimization of Flying Ad Hoc Network Topology and Collaborative Path Planning for Multiple UAVs
Journal: IEEE/CAA Journal of Automatica Sinica
DOI: https://doi.org/10.1109/JAS.2025.125846
About Nankai University
Nankai University is a public research university located in Tianjin, China. It is a Chinese Ministry of Education Class A Double First-Class University, founded in 1919 by educators Yan Xiu and Zhang Boling. The university blends Chinese and Western teaching methods to produce future leaders, top specialists, and successful entrepreneurs. Ranked among the top 10 public universities in China, Nankai University has developed cooperative relations with 300 colleges and research institutes in over 40 countries.
About Associate Professor Haihua Chen from Nankai University
Haihua Chen received a Ph.D. degree in electrical and electronic engineering from the University of Hong Kong, China, in 2006. She joined the College of Electronic Information and Optical Engineering at Nankai University in September 2010, where she currently serves as Associate Professor. Her research interests include wireless networking and task allocation for unmanned intelligent systems, distributed beamforming, resource allocation in wireless networks, massive multiple-input multiple-output systems, broadband sensor arrays, and statistical array signal processing.
Funding information
This work was supported by the National Natural Science Foundation of China (62373201, 61973173), and the Technology Research and Development Program of Tianjin (20YFZCSY00830, 18ZXZNGX00340).
IEEE/CAA Journal of Automatica Sinica
Experimental study
Not applicable
Optimization of Flying Ad Hoc Network Topology and Collaborative Path Planning for Multiple UAVs
3-Jul-2026
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