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 …
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 …
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 approach with multiple experience pools for UAV's autonomous motion planning in complex unknown environments
Z Hu, K Wan, X Gao, Y Zhai, Q Wang - Sensors, 2020 - mdpi.com
Autonomous motion planning (AMP) of unmanned aerial vehicles (UAVs) is aimed at
enabling a UAV to safely fly to the target without human intervention. Recently, several …
enabling a UAV to safely fly to the target without human intervention. Recently, several …
Reinforcement-learning-aided safe planning for aerial robots to collect data in dynamic environments
B Khamidehi, ES Sousa - IEEE Internet of Things Journal, 2022 - ieeexplore.ieee.org
We study the data collection problem in an Internet of Things (IoT) network where an
unmanned aerial vehicle (UAV) is utilized to aggregate data from a set of IoT devices. We …
unmanned aerial vehicle (UAV) is utilized to aggregate data from a set of IoT devices. We …
[HTML][HTML] Relevant experience learning: A deep reinforcement learning method for UAV autonomous motion planning in complex unknown environments
HU Zijian, GAO Xiaoguang, WAN Kaifang… - Chinese Journal of …, 2021 - Elsevier
Abstract Unmanned Aerial Vehicles (UAVs) play a vital role in military warfare. In a variety of
battlefield mission scenarios, UAVs are required to safely fly to designated locations without …
battlefield mission scenarios, UAVs are required to safely fly to designated locations without …
DRL-based improvement for autonomous UAV motion path planning in unknown environments
B Xin, C He - 2022 7th International Conference on Control and …, 2022 - ieeexplore.ieee.org
In this paper, we proposed an empirical playback-based deep reinforcement learning (DRL)
approach to solve the problems related to autonomous path planning for unmanned aerial …
approach to solve the problems related to autonomous path planning for unmanned aerial …
Vision-based distributed multi-UAV collision avoidance via deep reinforcement learning for navigation
H Huang, G Zhu, Z Fan, H Zhai, Y Cai… - 2022 IEEE/RSJ …, 2022 - ieeexplore.ieee.org
Online path planning for multiple unmanned aerial vehicle (multi-UAV) systems is
considered a challenging task. It needs to ensure collision-free path planning in real-time …
considered a challenging task. It needs to ensure collision-free path planning in real-time …
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 …
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