微細ねじのビンピッキングに向けた深層学習による物体検出の高精度化

―重なって垂直方向にピントがぼけた複数のねじの学習―

抄録

In conventional image-based classification methods for micro screws, screws in trays are identified one by one, which is time-consuming and labor-intensive. In this study, we succeeded in detecting and classifying multiple screws simultaneously and with high accuracy by learning with the object detection algorithm YOLO. When screws overlap, the focus of the image is blurred, but the blurred image is also learned to improve the recognition rate.