The paper proposes a Digital Twin-enabled Simultaneous Learning and Modeling (DT-SLAM) framework to enhance secure communications in UAV-assisted networks against intelligent eavesdropping attacks, ac…

A lightweight sensor-driven Lévy walk controller is presented for efficient autonomous exploration of minimal-sensing, resource-constrained nano-UAVs.

The paper proposes a Digital Twin-assisted Adaptive Multi-Agent Deep Reinforcement Learning framework to intelligently manage spectrum and resources in complex, dynamic Open-RAN 6G networks utilizing…

This paper proposes using an Unscented Kalman Filter (UKF) for accurate wind estimation in quadrotor UAVs, outperforming the Extended Kalman Filter (EKF) in highly nonlinear scenarios.

This paper presents TRUAV, a distributed multi-agent reinforcement learning framework for joint UAV trajectory planning and routing enhancement in UAV-aided VANETs, eliminating the need for global sta…

This paper proposes using cyber deception with honey drones (HDs) to defend UAV mission systems against Denial-of-Service (DoS) attacks, achieving superior performance using a novel Hypergame-Theoreti…

The paper proposes an uncertainty-aware, decentralized fusion layer for multi-UAV systems that significantly improves 3D localization robustness by incorporating neighbor constraints and handling faul…

This paper proposes a cloud-edge-end collaborative defense framework to secure UAV swarms against various threats like GPS spoofing and multi-hop intrusions, demonstrating its effectiveness through ex…

This paper identifies and discusses twelve technical challenges that need to be addressed to safely and effectively scale drone technology for commercial use.

This paper proposes CR-CMAB, a framework for jointly optimizing base station deployment and UAV flight corridors in urban environments to minimize infrastructure investment and flight distance while s…

The paper introduces SkyShield, the first front-view monocular semantic occupancy benchmark for low-altitude urban UAV flight, along with a novel metric and model to address the unique safety challeng…

This paper proposes a UAV trajectory optimization framework with continual transfer learning within the O-RAN architecture for 6G cellular systems.