[1] [1] Huong G N, Resul H, Jrg F. Enabling deep learning using synthetic data: A case study for the automotive wiring harness manufacturing [J]. Procedia Cirp, 2022, 107(9):1263-1268.

[2] [2] Gao Y, Chen Z, Fang M, et al. Development of an Autonomous Soldering Robot for USB Wires [C]//2020 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM). IEEE, 2020, 1196-1201.

[3] [3] Jun N, Tang C W, Yan X. Three-dimensional precisio analysis with rigid and compliant motions for sheet meta assembly [J]. The International Journal of Advanced Manufacturing Technology, 2014, 73(5):805-819.

[4] [4] Trommnau J, Khnle J, Siegert J, et al. Overview of the State of the Art in the Production Process of Automotive Wire Harnesses, Current Research and Future Trends [J]. Procedia CIRP, 2019, 81(3):387-392.

[5] [5] Huo S, Duan A, Li C, et al. Keypoint - Based Bimanual Shaping of Deformable Linear Objects under Environmental Constraints using Hierarchical Action Planning [J]. IEEE Robotics and Automation Letters, 2022, 7(8):5222-5229.

[6] [6] Yan M, Zhu Y, Jin, et al. Self-supervised learning of state estimation for manipulating deformable linear objects [J]. IEEE robotics and automation letters, 2020, 5(2):2372-2379.

[7] [7] Wnuk M, Hinze C, Lechler A, et al. Kinematic Multibody Model Generation of Deformable Linear Objects from Point Clouds [J]. IEEE, 2021, 7(8):9545-9552.

[8] [8] Lv K C, Yu M R, Pu Y F, et al. Learning to Estimate 3-D States of Deformable Linear Objects from Single-Frame Occluded Point Clouds [C]//International Conference on Robotics and Automation (ICRA), 2023, 7119-7125.

[9] [9] Keipour A, Bandari M, Schaal S. Deformable One-Dimensional Object Detection for Routing and Manipulation [J]. IEEE Robotics and Automation Letters, 2022, 7(8):4329-4336.

[10] [10] Zhu J, Navarro B, Fraisse, P, et al. Dual-arm robotic manipulation of flexible cables [C]//2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018, 479-484.

[11] [11] Caporali A, Zanella R, De Greogrio D, et al. Ariadne +: Deep learning-based augmented framework for the instance segmentation of wires [J]. IEEE Transactions on Industrial Informatics,2022,18(12):8607-8617.

[13] [13] Ronneberger O, Fischer P, Brox T. U-Net: Convolutional Networks for Biomedical Image Segmentation [C]//International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer International Publishing, 2015, 234-241.

[14] [14] He K M, Zhang X Y, Ren S Q, et al. Deep residual learning for image recognition [C]//2016 IEEE Conference on Computer Vision and Pattern Recognition. Las Vegas: IEEE, 2016, 770-778.

[15] [15] Hu J, Shen L, Sun G, et al. Squeeze-and-Excitation Networks [C]//IEEE Transactions on Pattern Analysis and Machine Intelligence. IEEE, 2017, 99.

[16] [16] Chen W, Sui L, Xu Z, et al. Improved Zhang-Suen thinning algorithm in binary line drawing applications [C]//2012 International Conference on Systems and Informatics (ICSAI2012), 2012, 1947-1950.

[18] [18] Zanella R, CaporalI A, Tadaka K, et al. Auto generated Wires Dataset for Semantic Segmentation with Domain-Independence [C]//2021 International Conference on Computer, Control and Robotics (ICCCR), 2021, 92-298.

[19] [19] Oktay O, Schlemper J, Folgoc L L, et al. Attention U-Net: Learning Where to Look for the Pancreas [J]. Computing Research Repository abs, 2018, 6(8):34-44.

[21] [21] Widiarti A R. Comparing Hilditch, Rosenfeld, Zhang-Suen, and Nagendraprasad-Wang-Gupta Thinning [J]. InternationalScholarly and Scientific Research & Innovation, 2011, 5 (6):563-567.

[22] [22] Kumar A, Teja V. Edge detection based on Otsu method and Stentiford algorithm [J]. International Journal of Engineering Research Technology,2014,3(11):1527-1530.

[23] [23] Zhou R W, Quek C, Ng G S. A novel single-pass thinning algorithm and an effective set of performance criteria [J]. Pattern Recognition Letters,1995,16(12):1267-1275.

[24] [24] Gramblicka M, Vasky J. Comparison of thinning algorithms for vectorization of engineering drawings [J]. Journal of Theoretical and Applied Information Technology, 2016, 94(2): 265.