Topology control algorithms in multi-unmanned aerial vehicle networks: An extensive survey

MM Alam, MY Arafat, S Moh, J Shen - Journal of network and computer …, 2022 - Elsevier
In recent years, unmanned aerial vehicles (UAVs) have attracted increased attention from
academic and industrial research communities, owing to their wide range of potential …

Review of sensor technology to support automated air-to-air refueling of a probe configured uncrewed aircraft

J Parry, S Hubbard - Sensors, 2023 - mdpi.com
As technologies advance and applications for uncrewed aircraft increase, the capability to
conduct automated air-to-air refueling becomes increasingly important. This paper provides …

Self-powered system for real-time wireless monitoring and early warning of UAV motor vibration based on triboelectric nanogenerator

K Wang, Y Yao, Y Liu, X Guan, Y Yu, J Wang, Y Wang… - Nano Energy, 2024 - Elsevier
Unmanned aerial vehicle (UAV) is widely used in various industries due to their high
flexibility and large maneuverable space. Abnormal vibration of UAV motors can prevent it …

Digital-twin-assisted task assignment in multi-UAV systems: A deep reinforcement learning approach

X Tang, X Li, R Yu, Y Wu, J Ye, F Tang… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Most existing multiunmanned aerial vehicle (multi-UAV) systems focus on fly path or energy
consumption for task assignment, while little attention has been paid to the dynamic feature …

Deep reinforcement learning based trajectory optimization for magnetometer-mounted UAV to landmine detection

A Barnawi, N Kumar, I Budhiraja, K Kumar… - Computer …, 2022 - Elsevier
Unmanned aerial vehicles (UAVs) have emerged as a viable choice for data collection and
landmine (LM) detection. The LM buried under the dirt or sand is detected using a UAV …

White shark optimizer with optimal deep learning based effective unmanned aerial vehicles communication and scene classification

T Nadana Ravishankar, M Ramprasath, A Daniel… - Scientific Reports, 2023 - nature.com
Unmanned aerial vehicles (UAVs) become a promising enabler for the next generation of
wireless networks with the tremendous growth in electronics and communications. The …

Deep reinforcement learning for internet of drones networks: issues and research directions

N Aboueleneen, A Alwarafy… - IEEE Open Journal of the …, 2023 - ieeexplore.ieee.org
Internet of Drones (IoD) is one of the promising technologies to enhance the performance of
wireless networks. Deploying IoD to assist wireless networks, however, needs to address …

Stargate: Multimodal Sensor Fusion for Autonomous Navigation On Miniaturized UAVs

K Kalenberg, H Müller, T Polonelli… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
Autonomously navigating robots need to perceive and interpret their surroundings.
Currently, cameras are among the most used sensors due to their high resolution and frame …

A review of perception sensors, techniques, and hardware architectures for autonomous low-altitude UAVs in non-cooperative local obstacle avoidance

MZ Butt, N Nasir, RBA Rashid - Robotics and Autonomous Systems, 2024 - Elsevier
Abstract Unmanned Aerial Vehicles (UAVs) can detect and communicate with cooperative
obstacles through established protocols. However, non-cooperative obstacles pose a …

Federated deep reinforcement learning-based intelligent dynamic services in UAV-assisted MEC

P Hou, X Jiang, Z Wang, S Liu… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs)-assisted multiaccess edge computing (MEC) has
emerged as a promising solution in B5G/6G networks. The high flexibility and seamless …