Deep reinforcement learning in smart manufacturing: A review and prospects
To facilitate the personalized smart manufacturing paradigm with cognitive automation
capabilities, Deep Reinforcement Learning (DRL) has attracted ever-increasing attention by …
capabilities, Deep Reinforcement Learning (DRL) has attracted ever-increasing attention by …
[HTML][HTML] A state-of-the-art survey on deep learning theory and architectures
In recent years, deep learning has garnered tremendous success in a variety of application
domains. This new field of machine learning has been growing rapidly and has been …
domains. This new field of machine learning has been growing rapidly and has been …
Deep reinforcement learning in production systems: a systematic literature review
Shortening product development cycles and fully customisable products pose major
challenges for production systems. These not only have to cope with an increased product …
challenges for production systems. These not only have to cope with an increased product …
[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 …
The history began from alexnet: A comprehensive survey on deep learning approaches
Deep learning has demonstrated tremendous success in variety of application domains in
the past few years. This new field of machine learning has been growing rapidly and applied …
the past few years. This new field of machine learning has been growing rapidly and applied …
Towards Self-X cognitive manufacturing network: An industrial knowledge graph-based multi-agent reinforcement learning approach
Empowered by the advanced cognitive computing, industrial Internet-of-Things, and data
analytics techniques, today's smart manufacturing systems are ever-increasingly equipped …
analytics techniques, today's smart manufacturing systems are ever-increasingly equipped …
Variable compliance control for robotic peg-in-hole assembly: A deep-reinforcement-learning approach
CC Beltran-Hernandez, D Petit, IG Ramirez-Alpizar… - Applied Sciences, 2020 - mdpi.com
Featured Application Assembly tasks with industrial robot manipulators. Abstract Industrial
robot manipulators are playing a significant role in modern manufacturing industries …
robot manipulators are playing a significant role in modern manufacturing industries …
[HTML][HTML] A survey of robot manipulation in contact
In this survey, we present the current status on robots performing manipulation tasks that
require varying contact with the environment, such that the robot must either implicitly or …
require varying contact with the environment, such that the robot must either implicitly or …
Reinforcement learning on variable impedance controller for high-precision robotic assembly
J Luo, E Solowjow, C Wen, JA Ojea… - … on Robotics and …, 2019 - ieeexplore.ieee.org
Precise robotic manipulation skills are desirable in many industrial settings, reinforcement
learning (RL) methods hold the promise of acquiring these skills autonomously. In this …
learning (RL) methods hold the promise of acquiring these skills autonomously. In this …
Deep reinforcement learning for industrial insertion tasks with visual inputs and natural rewards
Connector insertion and many other tasks commonly found in modern manufacturing
settings involve complex contact dynamics and friction. Since it is difficult to capture related …
settings involve complex contact dynamics and friction. Since it is difficult to capture related …