Live Structural Modeling Using RGB-D SLAM
Nicolas Olivier, Hideaki Uchiyama, Masashi Mishima, Diego Thomas, Rin-Ichiro Taniguchi, Rafael Roberto, João Paulo Lima, Veronica Teichrieb
Abstract
This paper presents a method for localizing primitive shapes in a dense point cloud computed by the RGB-D SLAM system. To stably generate a shape map containing only primitive shapes, the primitive shape is incrementally modeled by fusing the shapes estimated at previous frames in the SLAM, so that an accurate shape can be finally generated. Specifically, the history of the fusing process is used to avoid the influence of error accumulation in the SLAM. The point cloud of the shape is then updated by fusing the points in all the previous frames into a single point cloud. In the experimental results, we show that metric primitive modeling in texture-less and unprepared environments can be achieved online.
BibTeX
@inproceedings{icra2018_livestructuralmo,
title = {Live Structural Modeling Using RGB-D SLAM},
author = {Nicolas Olivier and Hideaki Uchiyama and Masashi Mishima and Diego Thomas and Rin-Ichiro Taniguchi and Rafael Roberto and João Paulo Lima and Veronica Teichrieb},
booktitle = {ICRA 2018},
year = {2018}
}