Smart Industrial Robot Control Trends, Challenges and Opportunities within Manufacturing

被引：109

作者：

Arents, Janis ^{[1
]}

Greitans, Modris ^{[1
]}

机构：

[1] Inst Elect & Comp Sci, 14 Dzerbenes St, LV-1006 Riga, Latvia

来源：

APPLIED SCIENCES-BASEL | 2022年 / 12卷 / 02期

关键词：

smart industrial robots; cognitive robotics; computer vision; reinforcement learning; imitation learning; synthetic data; simulation; smart manufacturing; future factories; artificial intelligence; MANIPULATION TASKS; DEEP; VISION; RECOGNITION; FRAMEWORK;

D O I：

10.3390/app12020937

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

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.

引用

页数：20

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