The Boeing Company

University of Washington

Volvo Car Corporation

Ekta U Samani

Sihao Ding

Adriana Willempje Blom-Schieber

Wei Guo

Ashis G Banerjee

Techniques are described for generating bird's eye view (BEV) images and segmentation maps. According to one or more embodiments, a system is provided comprising a processor that executes computer executable components stored in at least one memory, comprising a machine learning component that generates a synthesized bird's eye view image from a stitched image based on removing artifacts from the stitched image present from a transformation process. The system further comprising a generator that produces the synthesized bird's eye view image and a segmentation map, and a discriminator that predicts whether the synthesized bird's eye view image and the segmentation map are real or generated.

Generation of bird's-eye-view images and segmentation maps

A method of inspecting a composite structure formed of plies of tows is provided. The method involves receiving an image of an upper ply overlapping lower plies, the upper ply tow ends defining a boundary between plies, and applying extracted sub-images to a trained machine learning model to detect the upper or lower ply. Probability maps are produced in which pixels of the sub-images are associated with probabilities the pixels belong to an object class for the upper or lower ply. The method may also involve transforming the probability maps into reconstructed sub-images, stitching together a composite image, and applying the composite image to a feature detector to detect locations of tow ends of the upper ply. The method may also involve comparing the locations to as-designed locations of the tow ends, inspecting the composite structure, and indicating a result of the comparison.

Fiber placement tow end detection using machine learning

Growing community of inventors

Seattle, WA, United States of America

Ekta U Samani