[HTML][HTML] A review on reinforcement learning for contact-rich robotic manipulation tasks
Í Elguea-Aguinaco, A Serrano-Muñoz… - Robotics and Computer …, 2023 - Elsevier
Research and application of reinforcement learning in robotics for contact-rich manipulation
tasks have exploded in recent years. Its ability to cope with unstructured environments and …
tasks have exploded in recent years. Its ability to cope with unstructured environments and …
[HTML][HTML] A comprehensive survey on the application of deep and reinforcement learning approaches in autonomous driving
Abstract Recent advances in Intelligent Transport Systems (ITS) and Artificial Intelligence
(AI) have stimulated and paved the way toward the widespread introduction of Autonomous …
(AI) have stimulated and paved the way toward the widespread introduction of Autonomous …
Survey of deep reinforcement learning for motion planning of autonomous vehicles
S Aradi - IEEE Transactions on Intelligent Transportation …, 2020 - ieeexplore.ieee.org
Academic research in the field of autonomous vehicles has reached high popularity in
recent years related to several topics as sensor technologies, V2X communications, safety …
recent years related to several topics as sensor technologies, V2X communications, safety …
Deep reinforcement learning-based automatic exploration for navigation in unknown environment
This paper investigates the automatic exploration problem under the unknown environment,
which is the key point of applying the robotic system to some social tasks. The solution to this …
which is the key point of applying the robotic system to some social tasks. The solution to this …
Image enhancement for tuberculosis detection using deep learning
The latest World Health Organization's (WHO) study on 2018 is showing that about 1.5
million people died and around 10 million people are infected with tuberculosis (TB) each …
million people died and around 10 million people are infected with tuberculosis (TB) each …
Federated learning for connected and automated vehicles: A survey of existing approaches and challenges
Machine learning (ML) is widely used for key tasks in Connected and Automated Vehicles
(CAV), including perception, planning, and control. However, its reliance on vehicular data …
(CAV), including perception, planning, and control. However, its reliance on vehicular data …
Multiple vehicle cooperation and collision avoidance in automated vehicles: Survey and an AI-enabled conceptual framework
Prospective customers are becoming more concerned about safety and comfort as the
automobile industry swings toward automated vehicles (AVs). A comprehensive evaluation …
automobile industry swings toward automated vehicles (AVs). A comprehensive evaluation …
Fedopt: Towards communication efficiency and privacy preservation in federated learning
Artificial Intelligence (AI) has been applied to solve various challenges of real-world
problems in recent years. However, the emergence of new AI technologies has brought …
problems in recent years. However, the emergence of new AI technologies has brought …
A survey of deep reinforcement learning algorithms for motion planning and control of autonomous vehicles
In this survey, we systematically summarize the current literature on studies that apply
reinforcement learning (RL) to the motion planning and control of autonomous vehicles …
reinforcement learning (RL) to the motion planning and control of autonomous vehicles …
Formation control with collision avoidance through deep reinforcement learning using model-guided demonstration
Z Sui, Z Pu, J Yi, S Wu - IEEE Transactions on Neural Networks …, 2020 - ieeexplore.ieee.org
Generating collision-free, time-efficient paths in an uncertain dynamic environment poses
huge challenges for the formation control with collision avoidance (FCCA) problem in a …
huge challenges for the formation control with collision avoidance (FCCA) problem in a …