INTELLIMAN. WP5 T5-1-1. Monocular Estimation of Connector Orientation: Combining Deformable Linear Object Priors and Smooth Angle Classification

The dataset contains data related to the development of a learning-based solution for the detection of manufacturing errors in the context of robotic wiring harness assembly. In particular, the dataset contains the training set, the validation set, and the test set used to develop the proposed neural networks-based error detector, and the scripts to train and test the neural networks and store the trained models. The data were produced in the framework of Horizon Europe INTELLIMAN project and are presented in the publication:
A. Caporali, K. Galassi, G. Berselli and G. Palli, "Monocular Estimation of Connector Orientation: Combining Deformable Linear Object Priors and Smooth Angle Classification," 2024 IEEE International Conference on Advanced Intelligent Mechatronics (AIM), Boston, MA, USA, 2024, pp. 799-804, doi: 10.1109/AIM55361.2024.10637081.