Autonomous unmanned aerial vehicle navigation using reinforcement learning: A systematic review
There is an increasing demand for using Unmanned Aerial Vehicle (UAV), known as drones,
in different applications such as packages delivery, traffic monitoring, search and rescue …
in different applications such as packages delivery, traffic monitoring, search and rescue …
Unmanned aerial vehicle navigation in underground structure inspection: A review
Many years after construction, a number of existing old tunnels and underground structures
are deteriorating with time as evidenced by cracks, large deformations, water leakage and …
are deteriorating with time as evidenced by cracks, large deformations, water leakage and …
Communication aware UAV swarm surveillance based on hierarchical architecture
Multi-agent unmanned aerial vehicle (UAV) teaming becomes an essential part in science
mission, modern warfare surveillance, and disaster rescuing. This paper proposes a …
mission, modern warfare surveillance, and disaster rescuing. This paper proposes a …
Fapp: Fast and adaptive perception and planning for uavs in dynamic cluttered environments
Obstacle avoidance for Unmanned Aerial Vehicles (UAVs) in cluttered environments is
significantly challenging. Existing obstacle avoidance for UAVs either focuses on fully static …
significantly challenging. Existing obstacle avoidance for UAVs either focuses on fully static …
Deep q-learning for two-hop communications of drone base stations
In this paper, we address the application of the flying Drone Base Stations (DBS) in order to
improve the network performance. Given the high degrees of freedom of a DBS, it can …
improve the network performance. Given the high degrees of freedom of a DBS, it can …
Benchmarking off-policy deep reinforcement learning algorithms for uav path planning
This paper presents a benchmarking of off-policy Reinforcement Learning (RL) algorithms
for Unmanned Aerial Vehicle (UAV) path planning. The focus is on assessing the …
for Unmanned Aerial Vehicle (UAV) path planning. The focus is on assessing the …
Adaptive Depth Graph Neural Network-based Dynamic Task Allocation for UAV-UGVs Under Complex Environments
Z Ma, J **ong, H Gong, X Wang - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
This paper investigates dynamic task allocation (DTA) for unmanned aerial vehicles (UAVs)
and unmanned ground vehicles (UGVs) in complex urban environments using an adaptive …
and unmanned ground vehicles (UGVs) in complex urban environments using an adaptive …
HVDC transmission line fault identification: a learning based UAV control strategy
Electricity Transmission plays an imperative role in smooth provision of power to the
consumers. High voltage direct current (HVDC) system has a lead over high voltage …
consumers. High voltage direct current (HVDC) system has a lead over high voltage …
VizNav: A Modular Off-Policy Deep Reinforcement Learning Framework for Vision-Based Autonomous UAV Navigation in 3D Dynamic Environments
Unmanned aerial vehicles (UAVs) provide benefits through eco-friendliness, cost-
effectiveness, and reduction of human risk. Deep reinforcement learning (DRL) is widely …
effectiveness, and reduction of human risk. Deep reinforcement learning (DRL) is widely …
A control architecture for fixed-wing aircraft based on the convolutional neural networks
This paper develops a nonlinear architecture to control different fixed-wing aircraft. This
architecture has inner and outer loops. The inner loops, designed based on the …
architecture has inner and outer loops. The inner loops, designed based on the …