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Open AccessArticle
Improved YOLOv5 Network for High-Precision Three-Dimensional Positioning and Attitude Measurement of Container Spreaders in Automated Quayside Cranes
by
Yujie Zhang
Yujie Zhang 1,2
,
Yangchen Song
Yangchen Song 1,
Luocheng Zheng
Luocheng Zheng 1,
Octavian Postolache
Octavian Postolache 3
,
Chao Mi
Chao Mi 1,4
and
Yang Shen
Yang Shen 4,5,*
1
Logistics Engineering College, Shanghai Maritime University, Shanghai 201306, China
2
School of Technology and Architecture, ISCTE-Instituto Universitário de Lisboa, 1649-026 Lisbon, Portugal
3
Instituto de Telecomunicações, ISCTE-Instituto Universitário de Lisboa, 1649-026 Lisbon, Portugal
4
Shanghai SMUVision Smart Technology Ltd., Shanghai 201306, China
5
Higher Technology College, Shanghai Maritime University, Shanghai 201306, China
*
Author to whom correspondence should be addressed.
Sensors 2024, 24(17), 5476; https://doi.org/10.3390/s24175476 (registering DOI)
Submission received: 21 July 2024
/
Revised: 13 August 2024
/
Accepted: 16 August 2024
/
Published: 23 August 2024
Abstract
For automated quayside container cranes, accurate measurement of the three-dimensional positioning and attitude of the container spreader is crucial for the safe and efficient transfer of containers. This paper proposes a high-precision measurement method for the spreader’s three-dimensional position and rotational angles based on a single vertically mounted fixed-focus visual camera. Firstly, an image preprocessing method is proposed for complex port environments. The improved YOLOv5 network, enhanced with an attention mechanism, increases the detection accuracy of the spreader’s keypoints and the container lock holes. Combined with image morphological processing methods, the three-dimensional position and rotational angle changes of the spreader are measured. Compared to traditional detection methods, the single-camera-based method for three-dimensional positioning and attitude measurement of the spreader employed in this paper achieves higher detection accuracy for spreader keypoints and lock holes in experiments and improves the operational speed of single operations in actual tests, making it a feasible measurement approach.
Share and Cite
MDPI and ACS Style
Zhang, Y.; Song, Y.; Zheng, L.; Postolache, O.; Mi, C.; Shen, Y.
Improved YOLOv5 Network for High-Precision Three-Dimensional Positioning and Attitude Measurement of Container Spreaders in Automated Quayside Cranes. Sensors 2024, 24, 5476.
https://doi.org/10.3390/s24175476
AMA Style
Zhang Y, Song Y, Zheng L, Postolache O, Mi C, Shen Y.
Improved YOLOv5 Network for High-Precision Three-Dimensional Positioning and Attitude Measurement of Container Spreaders in Automated Quayside Cranes. Sensors. 2024; 24(17):5476.
https://doi.org/10.3390/s24175476
Chicago/Turabian Style
Zhang, Yujie, Yangchen Song, Luocheng Zheng, Octavian Postolache, Chao Mi, and Yang Shen.
2024. "Improved YOLOv5 Network for High-Precision Three-Dimensional Positioning and Attitude Measurement of Container Spreaders in Automated Quayside Cranes" Sensors 24, no. 17: 5476.
https://doi.org/10.3390/s24175476
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