[HTML][HTML] Vision-based navigation techniques for unmanned aerial vehicles: Review and challenges
In recent years, unmanned aerial vehicles (UAVs), commonly known as drones, have
gained increasing interest in both academia and industries. The evolution of UAV …
gained increasing interest in both academia and industries. The evolution of UAV …
A comprehensive review of coverage path planning in robotics using classical and heuristic algorithms
CS Tan, R Mohd-Mokhtar, MR Arshad - IEEE Access, 2021 - ieeexplore.ieee.org
The small battery capacities of the mobile robot and the un-optimized planning efficiency of
the industrial robot bottlenecked the time efficiency and productivity rate of coverage tasks in …
the industrial robot bottlenecked the time efficiency and productivity rate of coverage tasks in …
UAV swarm intelligence: Recent advances and future trends
Y Zhou, B Rao, W Wang - Ieee Access, 2020 - ieeexplore.ieee.org
The dynamic uncertain environment and complex tasks determine that the unmanned aerial
vehicle (UAV) system is bound to develop towards clustering, autonomy, and intelligence. In …
vehicle (UAV) system is bound to develop towards clustering, autonomy, and intelligence. In …
[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 …
Multi-UAV path planning for wireless data harvesting with deep reinforcement learning
Harvesting data from distributed Internet of Things (IoT) devices with multiple autonomous
unmanned aerial vehicles (UAVs) is a challenging problem requiring flexible path planning …
unmanned aerial vehicles (UAVs) is a challenging problem requiring flexible path planning …
Artificial intelligence approaches for UAV navigation: Recent advances and future challenges
Unmanned aerial vehicles (UAVs) applications have increased in popularity in recent years
because of their ability to incorporate a wide variety of sensors while retaining cheap …
because of their ability to incorporate a wide variety of sensors while retaining cheap …
Deep reinforcement learning techniques for vehicular networks: Recent advances and future trends towards 6G
Employing machine learning into 6G vehicular networks to support vehicular application
services is being widely studied and a hot topic for the latest research works in the literature …
services is being widely studied and a hot topic for the latest research works in the literature …
Energy-efficient online path planning of multiple drones using reinforcement learning
Drones, typically unmanned aerial vehicles (UAVs), have many purposes. However,
simultaneous operation of multiple drones is challenging, considering the real-time …
simultaneous operation of multiple drones is challenging, considering the real-time …
UAV path planning for wireless data harvesting: A deep reinforcement learning approach
Autonomous deployment of unmanned aerial vehicles (UAVs) supporting next-generation
communication networks requires efficient trajectory planning methods. We propose a new …
communication networks requires efficient trajectory planning methods. We propose a new …
A multiagent deep reinforcement learning approach for path planning in autonomous surface vehicles: The Ypacaraí lake patrolling case
SY Luis, DG Reina, SLT Marín - IEEE Access, 2021 - ieeexplore.ieee.org
Autonomous surfaces vehicles (ASVs) excel at monitoring and measuring aquatic nutrients
due to their autonomy, mobility, and relatively low cost. When planning paths for such …
due to their autonomy, mobility, and relatively low cost. When planning paths for such …