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Article

Intelligent Perception System of Robot Visual Servo for Complex Industrial Environment

by 1, 2,* and 2
1
School of Electrical Engineering, Guangzhou College, South China University of Technology, Guangzhou 510006, China
2
School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510641, China
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(24), 7121; https://doi.org/10.3390/s20247121
Received: 28 September 2020 / Revised: 4 December 2020 / Accepted: 7 December 2020 / Published: 11 December 2020
Robot control based on visual information perception is a hot topic in the industrial robot domain and makes robots capable of doing more things in a complex environment. However, complex visual background in an industrial environment brings great difficulties in recognizing the target image, especially when a target is small or far from the sensor. Therefore, target recognition is the first problem that should be addressed in a visual servo system. This paper considers common complex constraints in industrial environments and proposes a You Only Look Once Version 2 Region of Interest (YOLO-v2-ROI) neural network image processing algorithm based on machine learning. The proposed algorithm combines the advantages of YOLO (You Only Look Once) rapid detection with effective identification of ROI (Region of Interest) pooling structure, which can quickly locate and identify different objects in different fields of view. This method can also lead the robot vision system to recognize and classify a target object automatically, improve robot vision system efficiency, avoid blind movement, and reduce the calculation load. The proposed algorithm is verified by experiments. The experimental result shows that the learning algorithm constructed in this paper has real-time image-detection speed and demonstrates strong adaptability and recognition ability when processing images with complex backgrounds, such as different backgrounds, lighting, or perspectives. In addition, this algorithm can also effectively identify and locate visual targets, which improves the environmental adaptability of a visual servo system View Full-Text
Keywords: deep learning; visual servoing; industry robot; intelligence perception deep learning; visual servoing; industry robot; intelligence perception
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MDPI and ACS Style

Luo, Y.; Li, S.; Li, D. Intelligent Perception System of Robot Visual Servo for Complex Industrial Environment. Sensors 2020, 20, 7121. https://doi.org/10.3390/s20247121

AMA Style

Luo Y, Li S, Li D. Intelligent Perception System of Robot Visual Servo for Complex Industrial Environment. Sensors. 2020; 20(24):7121. https://doi.org/10.3390/s20247121

Chicago/Turabian Style

Luo, Yongchao, Shipeng Li, and Di Li. 2020. "Intelligent Perception System of Robot Visual Servo for Complex Industrial Environment" Sensors 20, no. 24: 7121. https://doi.org/10.3390/s20247121

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