Authors:
Adam Kalisz
;
Tong Ling
;
Florian Particke
;
Christian Hofmann
and
Jörn Thielecke
Affiliation:
Department of Electrical, Electronic and Communication Engineering, Information Technology (LIKE), Friedrich-Alexander-Universität Erlangen-Nürnberg, Am Wolfsmantel 33, Erlangen, Germany
Keyword(s):
Visual, Simultaneous, Localization, And, Mapping, SLAM, ORB, LDSO, DSO, Comparison.
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.
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