Reinforcement Learning for Automated Industrial Robotics in Manufacturing
Author(s): Ravi Kumar Perumallapalli
Publication #: 2411012
Date of Publication: 05.01.2016
Country: USA
Pages: 1-8
Published In: Volume 2 Issue 1 January-2016
Abstract
Numerous technological sectors have been transformed by one of the most innovative applications of reinforcement learning (RL) in autonomous industrial robotics. As the demand for productivity, precision, and efficiency in manufacturing grows, automation has become increasingly vital. Traditional automation solutions often lacked the necessary flexibility and adaptability, even when they performed well. However, with the integration of reinforcement learning, robots can now interact with their environments to learn optimal behaviours, significantly enhancing the adaptability of robotic systems. This study explores the application of reinforcement learning in industrial robotics, focusing on design, architecture, and practical implementations. Reinforcement learning has enabled manufacturing robots to operate with unprecedented levels of autonomy, facilitating complex tasks that enhance productivity while minimizing the need for human intervention.
Keywords: Industrial Robotics, Automated Manufacturing, Machine Learning, Robotic Automation, Deep Learning, Industry 4.0, Process Optimization.
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