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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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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