An Industrial Self-Learning Robotic Platform Solution for Smart Factories Industrial Applications Using Machine and Deep Imitation Learning

Abstract

Smart Factory is a key platform for recent industrial revolution 4.0 and industrial robotic platform solutions using Artificial Intelligence are an integral measure of its cell’s configuration and reconfiguration. There are two different methods of machine learning used in industrial collaborative robotics systems, Computer Vision Machine Learning and Imitation Learning. Computer vision is a classical use of machine and deep learning methods and it needs a complex, expensive resources and is not suitable for various types of manufacturing automation environment. Imitation Learning is the most fascinating method, and the recent evolving industry is interested on it. The main aim of this research programme is to develop a self-learning robotic system platform solution using Machine and Deep Imitation Learning for smart factories’ industrial applications. A self-learning robotic system using deep imitation learning can reduce working time and give a less human error when performing high-precision processes. It can also improve the ability to configure robotic platform to facilitate a more flexible decisions and cost- effective manufacturing.