A novel vision-based method for 3D profile extraction of wire harness in robotized assembly process
- Authors
- Nguyen, T.P.; Yoon, J.
- Issue Date
- Oct-2021
- Publisher
- Elsevier B.V.
- Keywords
- Automation system; Convolutional neural network; Machine vision; Wire harness assembly
- Citation
- Journal of Manufacturing Systems, v.61, pp.365 - 374
- Indexed
- SCIE
SCOPUS
- Journal Title
- Journal of Manufacturing Systems
- Volume
- 61
- Start Page
- 365
- End Page
- 374
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/108204
- DOI
- 10.1016/j.jmsy.2021.10.003
- ISSN
- 0278-6125
- Abstract
- Automating stages for deformable objects in the production line, in which assembling a wire harness into a predefined position is a complex task owing to the specialized characteristics of the objects. Besides a few automatized systems proposed in the other studies to implement this task under simplified setup conditions, a significant portion of this process remains to be completed manually in industrial environments. To construct an automatic wire harness assembly system, the development of a method that can automatically detect the wire harness profile in a 3D environment and, consequently, guide robot arms to implement assembly tasks is indispensable. Therefore, this study presents an approach that satisfies this requirement, which not only proposes a deep learning-based system to detect the wire profile, but also improves the accuracy of the detected results through a correction method according to the depth values of contiguous areas. The verification of the approach in a robot system that highlights its usefulness and practicality demonstrates the potential of the proposed method to replace people and consequently, reduce labour costs in factory environments. © 2021
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Collections - COLLEGE OF ENGINEERING SCIENCES > DEPARTMENT OF MECHANICAL ENGINEERING > 1. Journal Articles
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