A quality improvement method for 3D laser slam point clouds based on geometric primitives of the scan scene

3D laser simultaneous localization and mapping (SLAM) technology is one of the most efficient methods to capture spatial information. However, the low-accuracy SLAM point cloud limits its application in many fields. To address the problem, a laser SLAM point cloud quality improvement method based on...

Full description

Saved in:
Bibliographic Details
Published in:International journal of remote sensing Vol. 42; no. 1; pp. 378 - 388
Main Authors: Sun, Wenxiao, Wang, Jian, Jin, Fengxiang, Yang, Yikun
Format: Journal Article
Language:English
Published: London Taylor & Francis 02.01.2021
Taylor & Francis Ltd
Subjects:
Accuracy
Algorithms
Data
data quality
geometry
Global navigation satellite system
global positioning systems
Lasers
Navigation
Navigation satellites
Navigation systems
Navigational satellites
Random sampling
Simultaneous localization and mapping
Spatial data
Three dimensional models
ISSN:0143-1161, 1366-5901, 1366-5901
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:3D laser simultaneous localization and mapping (SLAM) technology is one of the most efficient methods to capture spatial information. However, the low-accuracy SLAM point cloud limits its application in many fields. To address the problem, a laser SLAM point cloud quality improvement method based on geometric primitive (PCQI-GP) is proposed, which mainly includes extraction of reference datum and point cloud data correction. More specifically, the point cloud data quality is evaluated through extracting the geometric primitives of the scanning scene using the random sampling consistency algorithm, and the high-accuracy point cloud is defined as the reference datum. Furthermore, the primitive parameters extracted from reference datum are adopted to construct constraint conditions, and the coordinates of drifting point cloud data are corrected. Experiments are conducted with data collected by a handheld laser scan system in two challenging scenes to evaluate the PCQI-GP method. Compared with the theoretical design values, the correction accuracy of the PCQI-GP method is less than 3 cm. The experimental results demonstrate that the proposed method can effectively improve the quality of the laser SLAM point cloud in the area without global navigation satellite system (GNSS) signal and sufficient feature points.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:0143-1161
1366-5901
1366-5901
DOI:10.1080/2150704X.2020.1811911