An Online Solution of LiDAR Scan Matching Aided Inertial Navigation System for Indoor Mobile Mapping

Multisensors (LiDAR/IMU/CAMERA) integrated Simultaneous Location and Mapping (SLAM) technology for navigation and mobile mapping in a GNSS-denied environment, such as indoor areas, dense forests, or urban canyons, becomes a promising solution. An online (real-time) version of such system can extreme...

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Main Authors: Xiaoji Niu, Tong Yu, Jian Tang, Le Chang
Format: Article
Language:English
Published: Hindawi Limited 2017-01-01
Series:Mobile Information Systems
Online Access:http://dx.doi.org/10.1155/2017/4802159
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spelling doaj-5d6e025c1a474f4fb028b86d977592f62021-07-02T09:51:53ZengHindawi LimitedMobile Information Systems1574-017X1875-905X2017-01-01201710.1155/2017/48021594802159An Online Solution of LiDAR Scan Matching Aided Inertial Navigation System for Indoor Mobile MappingXiaoji Niu0Tong Yu1Jian Tang2Le Chang3GNSS Research Centre, Wuhan University, 129 Luoyu Road, Wuhan 430079, ChinaGNSS Research Centre, Wuhan University, 129 Luoyu Road, Wuhan 430079, ChinaGNSS Research Centre, Wuhan University, 129 Luoyu Road, Wuhan 430079, ChinaGNSS Research Centre, Wuhan University, 129 Luoyu Road, Wuhan 430079, ChinaMultisensors (LiDAR/IMU/CAMERA) integrated Simultaneous Location and Mapping (SLAM) technology for navigation and mobile mapping in a GNSS-denied environment, such as indoor areas, dense forests, or urban canyons, becomes a promising solution. An online (real-time) version of such system can extremely extend its applications, especially for indoor mobile mapping. However, the real-time response issue of multisensors is a big challenge for an online SLAM system, due to the different sampling frequencies and processing time of different algorithms. In this paper, an online Extended Kalman Filter (EKF) integrated algorithm of LiDAR scan matching and IMU mechanization for Unmanned Ground Vehicle (UGV) indoor navigation system is introduced. Since LiDAR scan matching is considerably more time consuming than the IMU mechanism, the real-time synchronous issue is solved via a one-step-error-state-transition method in EKF. Stationary and dynamic field tests had been performed using a UGV platform along typical corridor of office building. Compared to the traditional sequential postprocessed EKF algorithm, the proposed method can significantly mitigate the time delay of navigation outputs under the premise of guaranteeing the positioning accuracy, which can be used as an online navigation solution for indoor mobile mapping.http://dx.doi.org/10.1155/2017/4802159
collection DOAJ
language English
format Article
sources DOAJ
author Xiaoji Niu
Tong Yu
Jian Tang
Le Chang
spellingShingle Xiaoji Niu
Tong Yu
Jian Tang
Le Chang
An Online Solution of LiDAR Scan Matching Aided Inertial Navigation System for Indoor Mobile Mapping
Mobile Information Systems
author_facet Xiaoji Niu
Tong Yu
Jian Tang
Le Chang
author_sort Xiaoji Niu
title An Online Solution of LiDAR Scan Matching Aided Inertial Navigation System for Indoor Mobile Mapping
title_short An Online Solution of LiDAR Scan Matching Aided Inertial Navigation System for Indoor Mobile Mapping
title_full An Online Solution of LiDAR Scan Matching Aided Inertial Navigation System for Indoor Mobile Mapping
title_fullStr An Online Solution of LiDAR Scan Matching Aided Inertial Navigation System for Indoor Mobile Mapping
title_full_unstemmed An Online Solution of LiDAR Scan Matching Aided Inertial Navigation System for Indoor Mobile Mapping
title_sort online solution of lidar scan matching aided inertial navigation system for indoor mobile mapping
publisher Hindawi Limited
series Mobile Information Systems
issn 1574-017X
1875-905X
publishDate 2017-01-01
description Multisensors (LiDAR/IMU/CAMERA) integrated Simultaneous Location and Mapping (SLAM) technology for navigation and mobile mapping in a GNSS-denied environment, such as indoor areas, dense forests, or urban canyons, becomes a promising solution. An online (real-time) version of such system can extremely extend its applications, especially for indoor mobile mapping. However, the real-time response issue of multisensors is a big challenge for an online SLAM system, due to the different sampling frequencies and processing time of different algorithms. In this paper, an online Extended Kalman Filter (EKF) integrated algorithm of LiDAR scan matching and IMU mechanization for Unmanned Ground Vehicle (UGV) indoor navigation system is introduced. Since LiDAR scan matching is considerably more time consuming than the IMU mechanism, the real-time synchronous issue is solved via a one-step-error-state-transition method in EKF. Stationary and dynamic field tests had been performed using a UGV platform along typical corridor of office building. Compared to the traditional sequential postprocessed EKF algorithm, the proposed method can significantly mitigate the time delay of navigation outputs under the premise of guaranteeing the positioning accuracy, which can be used as an online navigation solution for indoor mobile mapping.
url http://dx.doi.org/10.1155/2017/4802159
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