Experiences in Building a Visual SLAM System from Open Source Components
In Proceedings of the IEEE International Conference on Robotics and Automation, (ICRA-11), 09.5.-13.5.2011, Shanghai, IEEE, pages 2644-2651, May/2011.
This paper shows that the field of visual SLAM has matured enough to build
a visual SLAM system from open source components. The system consists of
feature detection, data association, and sparse bundle adjustment. For all
three modules we evaluate different libraries w.r.t. ground truth.
We also present an extension of the SLAM system to create dense
voxel-maps. It employs dense stereo-matching and volumetric mapping
using the poses obtained from bundle adjustment, both implemented with open source libraries.
Apart from quantitative comparison we also report on specific
experiences with the various libraries.
Visual SLAM Computer Vision Stereo Matcing Data Association Sparse Bundle Adjustment