物体画像の背景除去を用いた自動合成画像生成によるロボットの認識のためのオンサイトティーチングシステム

抄録

On-site teaching systems that can teach robots to recognize objects in environments such as factories or convenience stores where objects change are important. In this paper, we propose an on-site teaching system for robot recognition using automatic synthesized image generation with object image background removal. The proposed on-site teaching system generates automatic synthesized images using a background removal method to provide data for robot object recognition. Additionally, deep learning is used to construct a model for recognizing objects from the automatic synthesized images. The proposed system shows that the accuracy of object detection using images with background removal is higher than that without background removal. Furthermore, the proposed system was used to perform picking operations on factory shelves using real robots in a short period.