勾配膨張類似度演算によるクラウド型位置推定技術の高精度化

抄録

This paper proposed a method of improvement of Localization Accuracy of Cloud-based Localization System using 3D CAD map (Universal Map) by gradient dilation matching. This system only prepares line segment datebase images made from 3D wireframe map in advance to estimate location. This system estimates a location by matching sensing image and database images. But, if this system uses conventional similarity operation, there was a case in which image matching failure occurs. So, I developed gradient dilation image which is converted from line segment images and new similarity operation to reduce matching failure. gradient dilation image is dilated line segments and give a gradient to density. gradient dilation matching improved localization accuracy by 90% in Universal Map.