A novel vision-based method for 3D profile extraction of wire harness in robotized assembly process. (October 2021) - Nguyen, Thong Phi; Yoon, Jonghun
Highlights: Wire harness manufacturing process is a tremendous challenge for being automatized. A CNN-based algorithm determines the arbitrarily formed wire harness profile. A correcting method based on depth values enhances the accuracy of 3D wire profile. Performance of algorithm is proved based on practical assembly test with dual robots. 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.