Deep reinforcement learning based mobile robot navigation: A review
K Zhu, T Zhang - Tsinghua Science and Technology, 2021 - ieeexplore.ieee.org
Navigation is a fundamental problem of mobile robots, for which Deep Reinforcement
Learning (DRL) has received significant attention because of its strong representation and …
Learning (DRL) has received significant attention because of its strong representation and …
A review of deep reinforcement learning for smart building energy management
Global buildings account for about 30% of the total energy consumption and carbon
emission, raising severe energy and environmental concerns. Therefore, it is significant and …
emission, raising severe energy and environmental concerns. Therefore, it is significant and …
Deep learning in the industrial internet of things: Potentials, challenges, and emerging applications
Recent advances in the Internet of Things (IoT) are giving rise to a proliferation of
interconnected devices, allowing the use of various smart applications. The enormous …
interconnected devices, allowing the use of various smart applications. The enormous …
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 …
Autonomous unmanned aerial vehicle navigation using reinforcement learning: A systematic review
F AlMahamid, K Grolinger - Engineering Applications of Artificial …, 2022 - Elsevier
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 …
in different applications such as packages delivery, traffic monitoring, search and rescue …
Towards autonomous multi-UAV wireless network: A survey of reinforcement learning-based approaches
Unmanned aerial vehicle (UAV)-based wireless networks have received increasing
research interest in recent years and are gradually being utilized in various aspects of our …
research interest in recent years and are gradually being utilized in various aspects of our …
Artificial intelligence for UAV-enabled wireless networks: A survey
MA Lahmeri, MA Kishk… - IEEE Open Journal of the …, 2021 - ieeexplore.ieee.org
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 …
the next-generation wireless communication networks. Their mobility and their ability to …
Feedback RRT* algorithm for UAV path planning in a hostile environment
J Guo, W Xia, X Hu, H Ma - Computers & Industrial Engineering, 2022 - Elsevier
Unmanned aerial vehicle (UAV) path planning in a hostile environment (UPPHE) considers
the features and information of defense systems to plan a risk-constrained shortest path for a …
the features and information of defense systems to plan a risk-constrained shortest path for a …
Deep reinforcement learning for flocking motion of multi-UAV systems: Learn from a digital twin
Over the past decades, unmanned aerial vehicles (UAVs) have been widely used in both
military and civilian fields. In these applications, flocking motion is a fundamental but crucial …
military and civilian fields. In these applications, flocking motion is a fundamental but crucial …
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 …