Abstract
Industrial robots and associated control methods are continuously developing. With the recent progress in the field of artificial intelligence, new perspectives in industrial robot control strategies have emerged, and prospects towards cognitive robots have arisen. AI-based robotic systems are strongly becoming one of the main areas of focus, as flexibility and deep understanding of complex manufacturing processes are becoming the key advantage to raise competitiveness. This review first expresses the significance of smart industrial robot control in manufacturing towards future factories by listing the needs, requirements and introducing the envisioned concept of smart industrial robots. Secondly, the current trends that are based on different learning strategies and methods are explored. Current computer-vision, deep reinforcement learning and imitation learning based robot control approaches and possible applications in manufacturing are investigated. Gaps, challenges, limitations and open issues are identified along the way.
Highlights
Smart Industrial Robot ControlIndustrial robots and their control methods have come a long way since their first appearance in manufacturing [1]
These requirements are neither feasible nor sustainable to be achieved by standard control methods
Research on mimicking human sight has been conducted for a long time; the majority of Deep-Reinforcement Learning (DRL)-based grasping methods are based on visual perception; one of the grasping goals is to achieve more human-like performance
Summary
Industrial robots and their control methods have come a long way since their first appearance in manufacturing [1]. The majority of industrial robots that are installed in production floors have been traditionally programmed to meet specific needs of respective factories and mostly tailored to perform “dull, dirty, or dangerous” jobs [7]. Such industrial robot systems are neither intelligent nor able to adapt to the dynamic environment nor learn tasks by themselves. We investigate how they are applied in the automation of industrial processes by considering the advantages and disadvantages of each control mechanism.
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