Abstract
This paper consists of two parts. The first part is environmental map construction algorithm with RGB-D camera. 3D indoor environmental map is generated by feature based alignment. RANdom SAmple Consensus(RANSAC) is used to obtain the alignment between point clouds. Lastly, experiment is performed using RGB-D camera, and the computational cost of the map construction algorithm is evaluated. The second part is selecting shape feature. Two shape descriptors are evaluated about computational costs and errors, and either descriptor is selected to recognize landmarks.