3D-Map Construction from RGB-D Images with Artificial Markers in Less Textured Environment

Abstract

In a conventional method of constructing a 3D-map from RGB-D images, we find a set of corresponding points in every two images, and find a frame translation between them, and merge them. However, in actual robot workspaces such as plants and office buildings, we frequently find an almost uniform workspace with less textured objects such as corridors and halls, where we cannot find the corresponding points from images. On the other hand, because it is an artificial environment, we can put artificial makers such as QR codes, for making a robot friendly environment. In this paper, we present an RGB-D image merging method by finding the corresponding points from visual features of artificial markers and investigate a position accuracy of merged 3D-maps.