Deep reinforcement learning for trajectory path planning and distributed inference in resource-constrained UAV swarms
The deployment flexibility and maneuverability of unmanned aerial vehicles (UAVs)
increased their adoption in various applications, such as wildfire tracking, border monitoring …
increased their adoption in various applications, such as wildfire tracking, border monitoring …
Dynamic navigation in unconstrained environments using reinforcement learning algorithms
The potential for the use of drones in logistics and transportation is continuously growing,
with multiple applications both in urban and rural environments. The safe navigation of …
with multiple applications both in urban and rural environments. The safe navigation of …
Neural network pruning and fast training for DRL-based UAV trajectory planning
Deep reinforcement learning (DRL) has been applied for optimal control of autonomous
UAV trajectory generation. The energy and payload capacity of small UAVs impose …
UAV trajectory generation. The energy and payload capacity of small UAVs impose …
Obstacle-aware waypoint generation for long-range guidance of deep-reinforcement-learning-based navigation approaches
Navigation of mobile robots within crowded environments is an essential task in various use
cases, such as delivery, health care, or logistics. Deep Reinforcement Learning (DRL) …
cases, such as delivery, health care, or logistics. Deep Reinforcement Learning (DRL) …
When digital twin meets deep reinforcement learning in multi-UAV path planning
Unmanned aerial vehicles (UAVs) path planning is one of the promising technologies in the
fifth-generation wireless communications. The gap between simulation and reality limits the …
fifth-generation wireless communications. The gap between simulation and reality limits the …
UAV path planning based on the average TD3 algorithm with prioritized experience replay
X Luo, Q Wang, H Gong, C Tang - IEEE Access, 2024 - ieeexplore.ieee.org
Path planning is one of the important components of the Unmanned Aerial Vehicle (UAV)
mission, and it is also the key guarantee for the successful completion of the UAV's mission …
mission, and it is also the key guarantee for the successful completion of the UAV's mission …
A vision based deep reinforcement learning algorithm for UAV obstacle avoidance
J Roghair, A Niaraki, K Ko, A Jannesari - Intelligent Systems and …, 2022 - Springer
Integration of reinforcement learning with unmanned aerial vehicles (UAVs) to achieve
autonomous flight has been an active research area in recent years. An important part …
autonomous flight has been an active research area in recent years. An important part …
Online deep reinforcement learning for autonomous UAV navigation and exploration of outdoor environments
BG Maciel-Pearson, L Marchegiani, S Akcay… - arXiv preprint arXiv …, 2019 - arxiv.org
With the rapidly growing expansion in the use of UAVs, the ability to autonomously navigate
in varying environments and weather conditions remains a highly desirable but as-of-yet …
in varying environments and weather conditions remains a highly desirable but as-of-yet …
A UAV path planning method based on deep reinforcement learning
The path planning of Unmanned Aerial Vehicle (UAV) is a critical component of rescue
operation. As impacted by the continuity of the task space and the high dynamics of the …
operation. As impacted by the continuity of the task space and the high dynamics of the …
[HTML][HTML] Deep-reinforcement-learning-based UAV autonomous navigation and collision avoidance in unknown environments
W Fei, ZHU Xiaoping, Z Zhou, T Yang - Chinese Journal of Aeronautics, 2024 - Elsevier
In some military application scenarios, Unmanned Aerial Vehicles (UAVs) need to perform
missions with the assistance of on-board cameras when radar is not available and …
missions with the assistance of on-board cameras when radar is not available and …