Systematic Comparison of ORB-SLAM2 and LDSO based on Varying Simulated Environmental Factors

Adam Kalisz, Tong Ling, Florian Particke, Christian Hofmann, Jörn Thielecke

2020

Abstract

Although the number of outstanding but highly complex Visual SLAM systems which are published as open source has increased in recent years, they often lack a systematic evaluation of their weaknesses and failure cases. This work systematically discusses the key differences of two state-of-the-art Visual SLAM algorithms, the indirect ORB-SLAM2 and the direct LDSO, by extensive experiments in varying environments. The evaluation is principally focused to the trajectory accuracy and robustness of the algorithms in specific situations. However, details about individual components used for the estimation of trajectories in both systems are presented. In order to investigate crucial aspects, a custom dataset was created in a 3D modeling software, Blender, to acquire the data for all experiments. The experimental results demonstrate the strengths and weaknesses of the systems. In particular, this research contributes insight into: 1. The influence of moving objects in a usually static scene. 2. How both systems react on periodicly changing scene lighting, both local and global. 3. The role of initialization on the resistance to dynamic changes in the scene.

Paper Citation

in Harvard Style

Kalisz A., Ling T., Particke F., Hofmann C. and Thielecke J. (2020). Systematic Comparison of ORB-SLAM2 and LDSO based on Varying Simulated Environmental Factors. In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP; ISBN 978-989-758-402-2, SciTePress, pages 173-180. DOI: 10.5220/0008879401730180

in Bibtex Style

@conference{visapp20,
author={Adam Kalisz and Tong Ling and Florian Particke and Christian Hofmann and Jörn Thielecke},
title={Systematic Comparison of ORB-SLAM2 and LDSO based on Varying Simulated Environmental Factors},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP},
year={2020},
pages={173-180},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008879401730180},
isbn={978-989-758-402-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP
TI - Systematic Comparison of ORB-SLAM2 and LDSO based on Varying Simulated Environmental Factors
SN - 978-989-758-402-2
AU - Kalisz A.
AU - Ling T.
AU - Particke F.
AU - Hofmann C.
AU - Thielecke J.
PY - 2020
SP - 173
EP - 180
DO - 10.5220/0008879401730180
PB - SciTePress