A Markerless AR Guidance Method for Large-Scale Wire and Cable Laying of Electromechanical Products
Junhao Geng, Mengbo Chen, Xinyang Zhao, Yu Liu, Yongsheng Ma
Abstract
Large-scale wires and cables (W&Cs) are the nerves of large and complex electromechanical products vital to their regular operation. The laying process of W&C has been highly dependent on manual work and urgently needs intelligent guidance like augmented reality (AR). However, model registration and occlusion handling based on AR for large-scale W&C laying scenes cannot achieve high-quality results to date because of the lack of texture, the local field of vision, and other characteristics. Therefore, a markerless AR guidance method for large-scale W&C laying is proposed to address this long-lasting problem. First, camera, ultrawideband, and inertial measurement unit sensors are integrated to coarsely register the W&C models based on coordinate transformation and mapping virtual and physical spaces. Then, a local edge matching method is used to register the W&C models based on the coarse one finely. Next, the occlusion relationships of the W&C models are handled based on assembly constraints; the models are anchored in the simultaneous localization and mapping map for visual and continuous guidance. A locomotive W&C laying case study and evaluation results show that this method meets industrial application requirements regarding efficiency, accuracy, and robustness and has several advantages compared to other methods, including extra-large scale, automatic registration, and virtual-real fusion.