UAV Applications and Optimization

Latest papers

• DroneShield-AI: A Multi-Modal Sensor Fusion Framework for Real-Time Autonomous Drone Threat Detection, Behavioral Intent Classification, and Swarm Intelligence in Contested Airspace

  Marius Bayizere · 11 June 2026

  Unmanned Aerial Vehicle (UAV) threats have emerged as a defining security challenge of the 21st century. This paper presents DroneShield-AI, a unified open framework integrating six processing layers: RF signal classification, acoustic motor-signature detection, YOLOv8-based visual detection, eviden…

• LLM-Aided Joint Secrecy Precoding and Trajectory for RSMA-Based Heterogeneous UAV Networks

  Lijie Zheng, Ji He, Shih Yu Chang, Yulong Shen · 10 June 2026

  This paper investigates secure communications in rate-splitting multiple access (RSMA) enabled heterogeneous UAV networks, where multiple UAVs collaboratively serve ground terminals in the presence of eavesdroppers. By jointly considering secrecy rate maximization and propulsion energy consumption m…

• Disturbance-Aware Aerial Robotics for Ethical Wildlife Monitoring

  Mahmut Osmanovic, Isac Paulsson, Teddy Lazebnik · 9 June 2026

  Reliable wildlife monitoring is essential for ecology and conservation, yet many existing methods, such as tagging, capture, and close-range observation, can alter the very behaviors they aim to measure. Aerial robots offer a scalable alternative, which has shown promising performance in multiple st…

• Efficient Onboard Vision-Language Inference in UAV-Enabled Low-Altitude Economy Networks via LLM-Enhanced Optimization

  Yang Li, Ruichen Zhang, Yinqiu Liu, Guangyuan Liu, Abbas Jamalipour, Xianbin Wang, Dong In Kim · 9 June 2026

  The rapid advancement of Low-Altitude Economy Networks (LAENets) has enabled a variety of applications, including aerial surveillance, environmental sensing, and semantic data collection. To support these scenarios, unmanned aerial vehicles (UAVs) equipped with onboard vision-language models (VLMs) …

• X-Band UAV-enabled Integrated Sensing and Communications for Vehicular Networks

  Remon Polus, Soumaya Cherkaoui · 5 June 2026

  Uncrewed aerial vehicles (UAVs) are increasingly considered as aerial platforms capable of providing both sensing and communication services, representing a promising paradigm for intelligent transportation systems. This paper investigates the optimal time allocation for a UAV-enabled integrated sen…

• Digital Twin-Assisted Adaptive Multi-Agent DRL for Intelligent Spectrum and Resource Management in Open-RAN UAV-Enabled 6G Networks

  Marwan Dhuheir, Thang X. Vu, Symeon Chatzinotas · 2 June 2026

  The evolution toward 6G wireless networks envisions a seamlessly intelligent, Open-RAN-enabled architecture where unmanned aerial vehicles (UAVs) play a pivotal role in extending coverage, enhancing resilience, and ensuring reliable connectivity for ground users deployment. However, efficiently mana…

• Crazyflow: An Accurate, GPU-Accelerated, Differentiable Drone Simulator in JAX

  Martin Schuck, Marcel P. Rath, Yufei Hua, AbhisheK Goudar, SiQi Zhou, Angela P. Schoellig · 2 June 2026

  High-quality, large-scale synthetic data from simulations is becoming a cornerstone for pushing the capabilities of robot algorithms. While aerial robotics simulators have evolved to support specialized needs such as fidelity, differentiability, and swarms independently, a unified platform that can …

• Classification and detection of multiple UAVs using rational Gaussian wavelet neural networks

  Ungv\'ari Gerg\H{o}, Ferenc Braun, Attila \'Amon, P\'eter Kackst\"adter, J\'anos Volk, P\'eter Kov\'acs, Tam\'as D\'ozsa · 27 May 2026

  The detection of unmanned aerial vehicles (UAVs) is important for the protection of civilian and military infrastructure. In this paper we propose a cost effective UAV detection system using sound signals obtained from microphones. The recorded signals are passed through a signal processing pipeline…

• Scaling up Energy-Aware Multi-Agent Reinforcement Learning for Mission-Oriented Drone Networks with Individual Reward

  Changling Li, Ying Li · 26 May 2026

  Multi-agent reinforcement learning (MARL) has shown wide applicability in collaborative systems such as autonomous driving and smart cities for its ability of learning through interaction. With the recent development of drone networks, researchers have also applied MARL to address the trajectory pla…

• Personalized Federated Learning by Energy-Efficient UAV Communications

  Shiqian Guo, Jianqing Liu, Beatriz Lorenzo · 26 May 2026

  Federated learning (FL) is an effective paradigm for enhancing the learning capability of edge devices while preserving data privacy. In geographically dispersed FL systems, such as sensor networks in remote areas, unmanned aerial vehicles (UAVs) can flexibly establish high-quality communication lin…

• Comparative Analysis of Military Detection Using Drone Imagery Across Multiple Visual Spectrums

  Sourov Roy Shuvo, Prajwal Panth, Rajesh Chowdhury, Sorup Chakraborty, Sudip Chakrabarty, Prasant Kumar Pattnaik · 21 May 2026

  In modern warfare, drones are becoming an essential part of intelligence gathering and carrying out precise attacks in different kinds of hostile environments. Their ability to operate in real-time and hostile environments from a safe distance makes them invaluable for surveillance and military oper…

• World Model-Enabled Causal Digital Twins for Semantic Communications in Physical AI Systems

  Lingyi Wang, Tingyu Shui, Walid Saad, Pascal Adjakple · 19 May 2026

  Semantic communication has emerged as a promising paradigm for enabling goal-oriented networking. However, most existing semantic communication solutions are tailored to one-shot tasks and optimize instantaneous performance. Hence, they cannot be used to support closed-loop dynamic systems with phys…

• An Agentic AI Framework with Large Language Models and Chain-of-Thought for UAV-Assisted Logistics Scheduling with Mobile Edge Computing

  Hanwen Zhang, Dusit Niyato, Wei Zhang, Xin Lou, Malcolm Yoke Hean Low · 14 May 2026

  In cloud manufacturing, unmanned aerial vehicles (UAVs) can support both product collection and mobile edge computing (MEC). This joint operation forms a hybrid scheduling problem, where physical logistics decisions are coupled with computational task scheduling. In this paper, UAVs collect finished…

• On Privacy-Preserving Image Transmission in Low-Altitude Networks: A Swin Transformer-Based Framework with Federated Learning

  Kexin Zhang, Lixin Li, Yuna Yan, Xin Zhang, Wensheng Lin, Rui Li, Dongwei Zhao, Zhu Han · 14 May 2026

  The rapid development of low-altitude economy has driven the proliferation of Unmanned Aerial Vehicle (UAV) applications, including logistics, inspection, and emergency response. However, transmitting high-volume image data from UAVs to ground stations faces significant challenges due to limited ban…

• Hierarchical LLM-Driven Control for HAPS-Assisted UAV Networks: Joint Optimization of Flight and Connectivity

  Zijiang Yan, Hao Zhou, Wael Jaafar, Jianhua Pei, Ping Wang, Halim Yanikomeroglu, Hina Tabassum · 13 May 2026

  Uncrewed aerial vehicles (UAVs) are increasingly deployed in complex networked environments, yet the joint optimization of multi-UAV motion control and connectivity remains a fundamental challenge. In this paper, we study a multi-UAV system operating in an integrated terrestrial and non-terrestrial …

• Joint Optimization of Trajectory Control, Resource Allocation, and Task Offloading for Multi-UAV-Assisted IoV

  Maoxin Ji, Qiong Wu, Pingyi Fan, Cui Zhang, Nan Cheng, Wen Chen, Khaled B. Letaief · 7 May 2026

  This paper investigates a multi-Unmanned Aerial Vehicle (UAV) joint base station-assisted Internet of Vehicles (IoV) task offloading system in dense urban environments. To minimize system delay and energy consumption under strict coupling constraints, the complex non-convex optimization problem is d…

• Efficient Transceiver Design for Aerial Image Transmission and Large-scale Scene Reconstruction

  Zeyi Ren, Jialin Dong, Wei Zuo, Yikun Wang, Bingyang Cheng, Sheng Zhou, Zhisheng Niu · 14 April 2026

  Large-scale three-dimensional (3D) scene reconstruction in low-altitude intelligent networks (LAIN) demands highly efficient wireless image transmission. However, existing schemes struggle to balance severe pilot overhead with the transmission accuracy required to maintain reconstruction fidelity. T…

• Plasticity-Enhanced Multi-Agent Mixture of Experts for Dynamic Objective Adaptation in UAVs-Assisted Emergency Communication Networks

  Wen Qiu, Zhiqiang He, Wei Zhao, Hiroshi Masui · 13 April 2026

  Unmanned aerial vehicles serving as aerial base stations can rapidly restore connectivity after disasters, yet abrupt changes in user mobility and traffic demands shift the quality of service trade-offs and induce strong non-stationarity. Deep reinforcement learning policies suffer from plasticity l…

• Lightweight Multimodal Adaptation of Vision Language Models for Species Recognition and Habitat Context Interpretation in Drone Thermal Imagery

  Hao Chen, Fang Qiu, Fangchao Dong, Defei Yang, Eve Bohnett, Li An · 8 April 2026

  This study proposes a lightweight multimodal adaptation framework to bridge the representation gap between RGB-pretrained VLMs and thermal infrared imagery, and demonstrates its practical utility using a real drone-collected dataset. A thermal dataset was developed from drone-collected imagery and w…

• Governance-Constrained Agentic AI: Blockchain-Enforced Human Oversight for Safety-Critical Wildfire Monitoring

  Ali Akarma, Toqeer Ali Syed, Salman Jan, Hammad Muneer, Abdul Khadar Jilani · 7 April 2026

  The AI-based sensing and autonomous monitoring have become the main components of wildfire early detection, but current systems do not provide adaptive inter-agent coordination, structurally defined human control, and cryptographically verifiable responsibility. Purely autonomous alert dissemination…

• Dynamic Mask Enhanced Intelligent Multi-UAV Deployment for Urban Vehicular Networks

  Gaoxiang Cao, Wenke Yuan, Yunpeng Hou, Huasen He, Quan Zheng, Jian Yang · 6 April 2026

  Vehicular Ad Hoc Networks (VANETs) play a crucial role in realizing vehicle-road collaboration and intelligent transportation. However, urban VANETs often face challenges such as frequent link disconnections and subnet fragmentation, which hinder reliable connectivity. To address these issues, we dy…

• Robust Multi-Agent Reinforcement Learning for Small UAS Separation Assurance under GPS Degradation and Spoofing

  Alex Zongo, Filippos Fotiadis, Ufuk Topcu, Peng Wei · 1 April 2026

  We address robust separation assurance for small Unmanned Aircraft Systems (sUAS) under GPS degradation and spoofing via Multi-Agent Reinforcement Learning (MARL). In cooperative surveillance, each aircraft (or agent) broadcasts its GPS-derived position; when such position broadcasts are corrupted, …

• CSI-tuples-based 3D Channel Fingerprints Construction Assisted by MultiModal Learning

  Chenjie Xie, Li You, Ruirong Chen, Gaoning He, Xiqi Gao · 27 March 2026

  Low-altitude communications can promote the integration of aerial and terrestrial wireless resources, expand network coverage, and enhance transmission quality, thereby empowering the development of sixth-generation (6G) mobile communications. As an enabler for low-altitude transmission, 3D channel …

• UAV-DETR: DETR for Anti-Drone Target Detection

  Jun Yang, Dong Wang, Hongxu Yin, Hongpeng Li, Jianxiong Yu · 25 March 2026

  Drone detection is pivotal in numerous security and counter-UAV applications. However, existing deep learning-based methods typically struggle to balance robust feature representation with computational efficiency. This challenge is particularly acute when detecting miniature drones against complex …

• A Bayesian Learning Approach for Drone Coverage Network: A Case Study on Cardiac Arrest in Scotland

  Tathagata Basu, Edoardo Patelli, Gianluca Filippi, Ben Parsonage, Christy Maddock, Massimiliano Vasile, Marco Fossati, Adam Loyd, Shaun Marshall, Paul Gowens · 25 March 2026

  Drones are becoming popular as a complementary system for \ac{ems}. Although several pilot studies and flight trials have shown the feasibility of drone-assisted \ac{aed} delivery, running a full-scale operational network remains challenging due to high capital expenditure and environmental uncertai…