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 …
Smart industrial robot control trends, challenges and opportunities within manufacturing
J Arents, M Greitans - Applied Sciences, 2022 - mdpi.com
Industrial robots and associated control methods are continuously developing. With the
recent progress in the field of artificial intelligence, new perspectives in industrial robot …
recent progress in the field of artificial intelligence, new perspectives in industrial robot …
[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 …
Residual reinforcement learning for robot control
Conventional feedback control methods can solve various types of robot control problems
very efficiently by capturing the structure with explicit models, such as rigid body equations …
very efficiently by capturing the structure with explicit models, such as rigid body equations …
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 …
[HTML][HTML] Robotic assembly of timber joints using reinforcement learning
In architectural construction, automated robotic assembly is challenging due to occurring
tolerances, small series production and complex contact situations, especially in assembly …
tolerances, small series production and complex contact situations, especially in assembly …
A review of robotic assembly strategies for the full operation procedure: planning, execution and evaluation
Y Jiang, Z Huang, B Yang, W Yang - Robotics and Computer-Integrated …, 2022 - Elsevier
The application of robots in mechanical assembly increases the efficiency of industrial
production. With the requirements of flexible manufacturing, it has become a research …
production. With the requirements of flexible manufacturing, it has become a research …
Joinable: Learning bottom-up assembly of parametric cad joints
Physical products are often complex assemblies combining a multitude of 3D parts modeled
in computer-aided design (CAD) software. CAD designers build up these assemblies by …
in computer-aided design (CAD) software. CAD designers build up these assemblies by …
Offline meta-reinforcement learning for industrial insertion
Reinforcement learning (RL) can in principle let robots automatically adapt to new tasks, but
current RL methods require a large number of trials to accomplish this. In this paper, we …
current RL methods require a large number of trials to accomplish this. In this paper, we …