Smart Industrial Robot Control Trends, Challenges and Opportunities within Manufacturing

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.

Automated summary

Industrial robots and associated control methods are continuously developing, and with recent progress in artificial intelligence, new perspectives in control strategies have emerged, leading to the possibility of cognitive robots. AI-based robotic systems are becoming a focal point due to their flexibility and deep understanding of complex manufacturing processes, which enhance competitiveness. This review highlights the importance of smart industrial robot control in future factories and explores current trends in learning strategies and methods, including computer vision, deep reinforcement learning, and imitation learning, along with their potential applications in manufacturing. Gaps, challenges, limitations, and open issues are also identified.