Open AccessResearch on Laser-Visual Fusion-based Simultaneous Localization and Mapping
Author(s) -
Jianjie Zhenga,
Haitao Zhang,
Kai Tang,
Weidi Kong
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1682/1/012049
Subject(s) - simultaneous localization and mapping , computer vision , artificial intelligence , point cloud , robustness (evolution) , computer science , sensor fusion , laser scanning , strengths and weaknesses , laser , mobile robot , robot , biochemistry , chemistry , physics , philosophy , epistemology , optics , gene
In consideration of the restrictions of the single-sensor SLAM system in different application scenarios, this paper proposes a laser-visual sensor fusion strategy on the basis of analyzing the strengths and weaknesses of laser SLAM and visual SLAM. In the local mapping stage, the laser stability is used to facilitate the visual SLAM system while in the global map generation stage, the point cloud map with rich texture information as constructed by the visual SLAM system is used to improve the missing map information of the laser SLAM system and finally obtain a globally consistent 2D grid map. Through indoor real scene experiments, the fused SLAM system is verified so as to improve the accuracy of localization and mapping and yield a favorable robustness by combining the strengths of both effectively.