Topology control algorithms in multi-unmanned aerial vehicle networks: An extensive survey
In recent years, unmanned aerial vehicles (UAVs) have attracted increased attention from
academic and industrial research communities, owing to their wide range of potential …
academic and industrial research communities, owing to their wide range of potential …
[HTML][HTML] Multi-agent deep reinforcement learning for multi-robot applications: A survey
J Orr, A Dutta - Sensors, 2023 - mdpi.com
Deep reinforcement learning has produced many success stories in recent years. Some
example fields in which these successes have taken place include mathematics, games …
example fields in which these successes have taken place include mathematics, games …
Deep reinforcement learning multi-UAV trajectory control for target tracking
J Moon, S Papaioannou, C Laoudias… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
In this article, we propose a novel deep reinforcement learning (DRL) approach for
controlling multiple unmanned aerial vehicles (UAVs) with the ultimate purpose of tracking …
controlling multiple unmanned aerial vehicles (UAVs) with the ultimate purpose of tracking …
[HTML][HTML] Joint topology control and routing in a UAV swarm for crowd surveillance
Aerial surveillance using unmanned aerial vehicles (UAVs) provides an on-demand and
cost-effective solution to smart-city monitoring needs, owing to their three-dimensional …
cost-effective solution to smart-city monitoring needs, owing to their three-dimensional …
Deep reinforcement learning based three-dimensional area coverage with UAV swarm
Unmanned aerial vehicle (UAV) technology is recognized as a promising solution to area
coverage problems (ACPs) and has been extensively studied recently. In this paper, we …
coverage problems (ACPs) and has been extensively studied recently. In this paper, we …
[HTML][HTML] Scalable and cooperative deep reinforcement learning approaches for multi-UAV systems: A systematic review
In recent years, the use of multiple unmanned aerial vehicles (UAVs) in various applications
has progressively increased thanks to advancements in multi-agent system technology …
has progressively increased thanks to advancements in multi-agent system technology …
LSTM-characterized deep reinforcement learning for continuous flight control and resource allocation in UAV-assisted sensor network
Unmanned aerial vehicles (UAVs) can be employed to collect sensory data in remote
wireless sensor networks (WSNs). Due to UAV's maneuvering, scheduling a sensor device …
wireless sensor networks (WSNs). Due to UAV's maneuvering, scheduling a sensor device …
[HTML][HTML] Survey on Q-learning-based position-aware routing protocols in flying ad hoc networks
A flying ad hoc network (FANETs), also known as a swarm of unmanned aerial vehicles
(UAVs), can be deployed in a wide range of applications including surveillance, monitoring …
(UAVs), can be deployed in a wide range of applications including surveillance, monitoring …
[HTML][HTML] Emerging technologies for 6G communication networks: Machine learning approaches
The fifth generation achieved tremendous success, which brings high hopes for the next
generation, as evidenced by the sixth generation (6G) key performance indicators, which …
generation, as evidenced by the sixth generation (6G) key performance indicators, which …
[HTML][HTML] Energy-efficient UAV movement control for fair communication coverage: A deep reinforcement learning approach
Unmanned Aerial Vehicles (UAVs) are considered an important element in wireless
communication networks due to their agility, mobility, and ability to be deployed as mobile …
communication networks due to their agility, mobility, and ability to be deployed as mobile …