相关论文: Deep Learning and Reinforcement Learning for Auton…

Unmanned aerial vehicles (UAV) are commonly used for missions in unknown environments, where an exact mathematical model of the environment may not be available. This paper provides a framework for using reinforcement learning to allow the…

Obstacle avoidance for small unmanned aircraft is vital for the safety of future urban air mobility (UAM) and Unmanned Aircraft System (UAS) Traffic Management (UTM). There are many techniques for real-time robust drone guidance, but many…

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 operations, and military combat engagements. In all of these…

In the last decade, the rapid growth of Unmanned Aircraft Systems (UAS) and Unmanned Aircraft Vehicles (UAV) in communication, defense, and transportation has increased. The application of UAS will continue to increase rapidly. This has led…

This paper presents a comprehensive literature review on applications of deep reinforcement learning in communications and networking. Modern networks, e.g., Internet of Things (IoT) and Unmanned Aerial Vehicle (UAV) networks, become more…

Unmanned aerial vehicles (UAVs) can be powerful Internet-of-Things components to execute sensing tasks over the next-generation cellular networks, which are generally referred to as the cellular Internet of UAVs. However, due to the high…

CCTV-based surveillance using unmanned aerial vehicles (UAVs) is considered a key technology for security in smart city environments. This paper creates a case where the UAVs with CCTV-cameras fly over the city area for flexible and…

Unmanned Aerial Vehicles (UAVs) are increasingly used in automated inspection, delivery, and navigation tasks that require reliable autonomy. This project develops a reinforcement learning (RL) approach to enable a single UAV to…

This paper presents a new reward function that can be used for deep reinforcement learning in unmanned aerial vehicle (UAV) control and navigation problems. The reward function is based on the construction and estimation of the time of…

Unmanned aerial vehicles (UAVs) are emerging in commercial spaces and will support many applications and services, such as smart agriculture, dynamic network deployment, and network coverage extension, surveillance and security. The…

Unmanned aircraft systems (UAS), or unmanned aerial vehicles (UAVs), often referred to as drones, have been experiencing healthy growth in the United States and around the world. The positive uses of UAS have the potential to save lives,…

The deployment of unmanned aerial vehicles (UAVs) in many different settings has provided various solutions and strategies for networking paradigms. Therefore, it reduces the complexity of the developments for the existing problems, which…

Unmanned aerial vehicles (UAVs) are envisioned to complement the 5G communication infrastructure in future smart cities. Hot spots easily appear in road intersections, where effective communication among vehicles is challenging. UAVs may…

Unmanned aerial vehicles (UAVs) are considered as one of the promising technologies for the next-generation wireless communication networks. Their mobility and their ability to establish line of sight (LOS) links with the users made them…

The emergence of mobile robotics, particularly in the automotive industry, introduces a promising era of enriched user experiences and adept handling of complex navigation challenges. The realization of these advancements necessitates a…

Air transportation is essential for society, and it is increasing gradually due to its importance. To improve the airspace operation, new technologies are under development, such as Unmanned Aircraft Systems (UAS). In fact, in the past few…

Unmanned Aerial vehicles (UAVs) are widely used as network processors in mobile networks, but more recently, UAVs have been used in Mobile Edge Computing as mobile servers. However, there are significant challenges to use UAVs in complex…

Path Planning methods for autonomous control of Unmanned Aerial Vehicle (UAV) swarms are on the rise because of all the advantages they bring. There are more and more scenarios where autonomous control of multiple UAVs is required. Most of…

Fast and reliable wireless communication has become a critical demand in human life. In the case of mission-critical (MC) scenarios, for instance, when natural disasters strike, providing ubiquitous connectivity becomes challenging by using…

Predicting the outcomes of integrating Unmanned Aerial Systems (UAS) into the National Aerospace (NAS) is a complex problem which is required to be addressed by simulation studies before allowing the routine access of UAS into the NAS. This…