Simultaneous localization and mapping in unknown environment using dynamic matching of images and registration of point clouds
This paper investigates the usage of the RGB D cameras for generation of dense 3D maps of environments. The proposed approach to generation of dense three dimensional maps of indoor environments with a complex infrastructure is based on multisensor dynamic information, spatial alignment of successive frames of data, view based loop closure detection (the robot returns to the primary point) the alignment of the complete sequence of data (mapping and registration of image sequences and sparse clouds three dimensional pixels) A new dynamic matching algorithm combining visual features and depth information to build global consistent maps is proposed. We evaluate the RGB D Mapping in indoor environments of Chelyabinsk State University.
2016 2nd International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)