A multi-stage deep reinforcement learning with search-based optimization for air–ground unmanned system navigation
X Chen, Y Qi, Y Yin, Y Chen, L Liu, H Chen - Applied Sciences, 2023 - mdpi.com
An important challenge for air–ground unmanned systems achieving autonomy is
navigation, which is essential for them to accomplish various tasks in unknown …
navigation, which is essential for them to accomplish various tasks in unknown …
Unmanned aerial vehicle path planning algorithm based on deep reinforcement learning in large-scale and dynamic environments
R Xie, Z Meng, L Wang, H Li, K Wang, Z Wu - IEEE Access, 2021 - ieeexplore.ieee.org
Path planning is one of the key technologies for autonomous flight of Unmanned Aerial
Vehicle. Traditional path planning algorithms have some limitations and deficiencies in the …
Vehicle. Traditional path planning algorithms have some limitations and deficiencies in the …
Deep reinforcement learning for mapless navigation of unmanned aerial vehicles
RB Grando, JC de Jesus… - 2020 Latin American …, 2020 - ieeexplore.ieee.org
This paper presents a deep reinforcement learning-based system for goal-oriented mapless
navigation for Unmanned Aerial Vehicles (UAVs). In this context, image-based sensing …
navigation for Unmanned Aerial Vehicles (UAVs). In this context, image-based sensing …
Autonomous navigation of UAV in multi-obstacle environments based on a deep reinforcement learning approach
Path planning is one of the most essential part in autonomous navigation. Most existing
works suppose that the environment is static and fixed. However, path planning is widely …
works suppose that the environment is static and fixed. However, path planning is widely …
Multi-agent deep reinforcement learning for UAVs navigation in unknown complex environment
Y Xue, W Chen - IEEE Transactions on Intelligent Vehicles, 2023 - ieeexplore.ieee.org
As unmanned aerial vehicles (UAVs) play an increasingly significant role in modern society,
using reinforcement learning to build safe multi-UAV navigation algorithms has become a …
using reinforcement learning to build safe multi-UAV navigation algorithms has become a …
Explainable Deep Reinforcement Learning for UAV autonomous path planning
Autonomous navigation in unknown environment is still a hard problem for small Unmanned
Aerial Vehicles (UAVs). Recently, some neural network-based methods are proposed to …
Aerial Vehicles (UAVs). Recently, some neural network-based methods are proposed to …
Multiple Unmanned Aerial Vehicle Autonomous Path Planning Algorithm Based on Whale-Inspired Deep Q-Network
In emergency rescue missions, rescue teams can use UAVs and efficient path planning
strategies to provide flexible rescue services for trapped people, which can improve rescue …
strategies to provide flexible rescue services for trapped people, which can improve rescue …
A hierarchical reinforcement learning algorithm based on attention mechanism for UAV autonomous navigation
Z Liu, Y Cao, J Chen, J Li - IEEE Transactions on Intelligent …, 2022 - ieeexplore.ieee.org
Unmanned Aerial Vehicles (UAVs) are increasingly being used in many challenging and
diversified applications. Meanwhile, UAV's ability of autonomous navigation and obstacle …
diversified applications. Meanwhile, UAV's ability of autonomous navigation and obstacle …
A hybrid human-in-the-loop deep reinforcement learning method for UAV motion planning for long trajectories with unpredictable obstacles
Unmanned Aerial Vehicles (UAVs) can be an important component in the Internet of Things
(IoT) ecosystem due to their ability to collect and transmit data from remote and hard-to …
(IoT) ecosystem due to their ability to collect and transmit data from remote and hard-to …
[HTML][HTML] UAV navigation in high dynamic environments: A deep reinforcement learning approach
Abstract Unmanned Aerial Vehicle (UAV) navigation is aimed at guiding a UAV to the
desired destinations along a collision-free and efficient path without human interventions …
desired destinations along a collision-free and efficient path without human interventions …