Deep reinforcement learning for real-time trajectory planning in UAV networks
In Unmanned Aerial Vehicle (UAV)-enabled wireless powered sensor networks, a UAV can
be employed to charge the ground sensors remotely via Wireless Power Transfer (WPT) and …
be employed to charge the ground sensors remotely via Wireless Power Transfer (WPT) and …
Trajectory design and generalization for UAV enabled networks: A deep reinforcement learning approach
X Li, Q Wang, J Liu, W Zhang - 2020 IEEE Wireless …, 2020 - ieeexplore.ieee.org
In this paper, an unmanned aerial vehicle (UAV) flies as a base station (BS) to provide
wireless communication service. We propose two algorithms for designing the trajectory of …
wireless communication service. We propose two algorithms for designing the trajectory of …
Deep reinforcement learning based path planning for UAV-assisted edge computing networks
Y Peng, Y Liu, H Zhang - 2021 IEEE Wireless Communications …, 2021 - ieeexplore.ieee.org
Mobile edge computing (MEC) harvests the computation capability at the network edge to
perform the computation intensive tasks for diverse IoT applications. Meanwhile, the …
perform the computation intensive tasks for diverse IoT applications. Meanwhile, the …
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 …
AoI optimal UAV trajectory planning: A deep recurrent reinforcement learning approach
M Wu, H Chi, S Gan, X Wang… - 2021 IEEE 32nd Annual …, 2021 - ieeexplore.ieee.org
In this paper, we consider an unmanned aerial vehicles (UAV)-assisted IoT network and
study the trajectory planning problem to optimize the information freshness, in terms of age …
study the trajectory planning problem to optimize the information freshness, in terms of age …
Decentralized planning-assisted deep reinforcement learning for collision and obstacle avoidance in UAV networks
JS Lin, HT Chiu, RH Gau - 2021 IEEE 93rd Vehicular …, 2021 - ieeexplore.ieee.org
In this paper, we propose using a decentralized planning-assisted approach of deep
reinforcement learning for collision and obstacle avoidance in UAV networks. We focus on a …
reinforcement learning for collision and obstacle avoidance in UAV networks. We focus on a …
FED-UP: Federated deep reinforcement learning-based UAV path planning against hostile defense system
In military operations, unmanned aerial vehicles (UAVs) have been heavily utilized in recent
years. However, due to the antenna installment regulation, UAVs cannot be controlled by …
years. However, due to the antenna installment regulation, UAVs cannot be controlled by …
Adaptive deployment of UAV-aided networks based on hybrid deep reinforcement learning
X Ma, S Hu, D Zhou, Y Zhou… - 2020 IEEE 92nd Vehicular …, 2020 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) can be used as air base stations to provide fast wireless
connections for ground users. Due to their constraints on both mobility and energy …
connections for ground users. Due to their constraints on both mobility and energy …
Data-driven deep reinforcement learning for online flight resource allocation in uav-aided wireless powered sensor networks
In wireless powered sensor networks (WPSN), data of ground sensors can be collected or
relayed by an unmanned aerial vehicle (UAV) while the battery of the ground sensor can be …
relayed by an unmanned aerial vehicle (UAV) while the battery of the ground sensor can be …
Deep Reinforcement Learning Assisted UAV Path Planning Relying on Cumulative Reward mode and Region Segmentation
Z Wang, SX Ng, EIH Mohammed - IEEE Open Journal of …, 2024 - ieeexplore.ieee.org
In recent years, unmanned aerial vehicles (UAVs) have been considered for many
applications, such as disaster prevention and control, logistics and transportation, and …
applications, such as disaster prevention and control, logistics and transportation, and …
相关搜索
- uav networks deep reinforcement
- trajectory planning deep reinforcement
- uav networks trajectory planning
- computing networks reinforcement learning
- trajectory planning bayesian optimization
- bayesian optimization deep reinforcement
- uav networks obstacle avoidance
- region segmentation deep reinforcement
- obstacle avoidance deep reinforcement
- communication network trajectory design
- sensor networks deep reinforcement
- uav path deep reinforcement
- trajectory planning network formation
- network formation deep reinforcement