Three-dimensional Environment Modeling Based on Structure from Motion with Feature Point and Edge Information in Omnidirectional Image Sequence

Abstract

Map information is important for path planning and self-localization when mobile robots execute autonomous tasks. In an unknown environment, mobile robots should measure the environment and construct its map by themselves. Then, we propose a modeling method of 3D environment. To realize wide-ranging environment measurement, we use an omnidirectional camera. We can measure environments efficiently by using the camera, because it has a 360-degree horizontal field of view. Our proposed method is based on structure from motion. A measurement method using feature points is effective in an environment including textured objects. Conversely, if environments mostly have non-textured objects, it is difficult to estimate camera movement and construct its environment model precisely. However, non-textured objects often have straight-line edges. Edge information is available for modeling of environments including non-textured objects. Against complex environments including both textured objects and non-textured objects, we should utilize both feature point and edge information for 3D environment modeling. Our proposed method constructs a 3D environment model by using both feature point and edge information. Experimental results show the effectiveness of our proposed method.