Robotic equipment has been playing a central role since the proposal of smart
manufacturing. Since the beginning of the first integration of industrial robots into production …

Industrial robots and associated control methods are continuously developing. With the
recent progress in the field of artificial intelligence, new perspectives in industrial robot …

For many contemporary manufacturing processes, autonomous robotic operators have
become ubiquitous. Despite this, the number of human operators within these processes …

Deep reinforcement learning (DRL) has proven to be an effective framework for solving
various complex control problems. In manufacturing, industrial robots can be trained to learn …

Dexterous manipulation of the robot is an important part of realizing intelligence, but
manipulators can only perform simple tasks such as sorting and packing in a structured …

The majority of robots in factories today are operated with conventional control strategies
that require individual programming on a task-by-task basis, with no margin for error. As an …

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 …

Human–Robot Collaboration (HRC) is an interdisciplinary research area that has gained
attention within the smart manufacturing context. To address changes within manufacturing …

To facilitate the personalized smart manufacturing paradigm with cognitive automation
capabilities, Deep Reinforcement Learning (DRL) has attracted ever-increasing attention by …

Abstract The field of Neural Combinatorial Optimization (NCO) offers multiple learning-
based approaches to solve well-known combinatorial optimization tasks such as Traveling …