Bayesian optimization enhanced deep reinforcement learning for trajectory planning and network formation in multi-UAV networks
In this paper, we employ multiple UAVs coordinated by a base station (BS) to help the
ground users (GUs) to offload their sensing data. Different UAVs can adapt their trajectories …
ground users (GUs) to offload their sensing data. Different UAVs can adapt their trajectories …
Deep reinforcement learning for joint trajectory planning, transmission scheduling, and access control in UAV-assisted wireless sensor networks
Unmanned aerial vehicles (UAVs) can be used to relay sensing information and
computational workloads from ground users (GUs) to a remote base station (RBS) for further …
computational workloads from ground users (GUs) to a remote base station (RBS) for further …
QoE-driven adaptive deployment strategy of multi-UAV networks based on hybrid deep reinforcement learning
Y Zhou, X Ma, S Hu, D Zhou… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) serve as aerial base stations to provide controlled
wireless connections for ground users. Due to their constraints on both mobility and energy …
wireless connections for ground users. Due to their constraints on both mobility and energy …
Trajectory design and resource allocation for multi-UAV networks: Deep reinforcement learning approaches
The future mobile communication system is expected to provide ubiquitous connectivity and
unprecedented services over billions of devices. The unmanned aerial vehicle (UAV), which …
unprecedented services over billions of devices. The unmanned aerial vehicle (UAV), which …
Learning-based UAV trajectory optimization with collision avoidance and connectivity constraints
Unmanned aerial vehicles (UAVs) are expected to be an integral part of wireless networks,
and determining collision-free trajectories for multiple UAVs while satisfying requirements of …
and determining collision-free trajectories for multiple UAVs while satisfying requirements of …
Resource allocation in UAV-assisted networks: A clustering-aided reinforcement learning approach
S Zhou, Y Cheng, X Lei, Q Peng… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
As an aerial base station, unmanned aerial vehicle (UAV) has been considered as a
promising technology to assist future wireless communications due to its flexible, swift and …
promising technology to assist future wireless communications due to its flexible, swift and …
Energy-efficient multi-uavs cooperative trajectory optimization for communication coverage: An madrl approach
T Ao, K Zhang, H Shi, Z Jin, Y Zhou, F Liu - Remote Sensing, 2023 - mdpi.com
Unmanned Aerial Vehicles (UAVs) can be deployed as aerial wireless base stations which
dynamically cover the wireless communication networks for Ground Users (GUs). The most …
dynamically cover the wireless communication networks for Ground Users (GUs). The most …
Deep reinforcement learning for trajectory path planning and distributed inference in resource-constrained UAV swarms
The deployment flexibility and maneuverability of unmanned aerial vehicles (UAVs)
increased their adoption in various applications, such as wildfire tracking, border monitoring …
increased their adoption in various applications, such as wildfire tracking, border monitoring …
Multi-uav adaptive path planning using deep reinforcement learning
J Westheider, J Rückin… - 2023 IEEE/RSJ …, 2023 - ieeexplore.ieee.org
Efficient aerial data collection is important in many remote sensing applications. In large-
scale monitoring scenarios, deploying a team of unmanned aerial vehicles (UAVs) offers …
scale monitoring scenarios, deploying a team of unmanned aerial vehicles (UAVs) offers …
Cooperative trajectory design of multiple UAV base stations with heterogeneous graph neural networks
Unmanned aerial vehicles as base stations (UAV-BSs) are recognized as effective means
for tackling eruptive communication service requirements especially when terrestrial …
for tackling eruptive communication service requirements especially when terrestrial …
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- deep reinforcement trajectory planning
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