Seamless navigation and mapping using an INS/GNSS/grid-based SLAM semi-tightly coupled integration scheme

Kai-Wei Chiang, G. J. Tsai, Hsiu-Wen Chang, C. Joly, N. EI-Sheimy

Research output: Contribution to journalArticle

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Abstract

Mobile Mapping Systems (MMS) with Inertial Navigation System / Global Navigation Satellite System (INS/GNSS) and mapping sensors have been widely developed in recent years. However current systems and results are still prone to errors, especially in GNSS-denied or multipath environments. To provide robust and stable navigation information, particularly for mapping in long-term GNSS-denied environments, we propose a semi-tightly coupled integration scheme which integrates INS/GNSS with grid-based Simultaneous Localization and Mapping (SLAM). Although traditional SLAM using LiDAR can map the GNSS-denied environment efficiently, it is only in local localization. The proposed integration scheme is based on the Extended Kalman Filter (EKF) with motion constraints. In this scheme, a measurement model for grid-based SLAM is aided by the heading and velocity information. A special innovation of this scheme is the improved fusion of GNSS/INS with the use of grid-based SLAM serves like virtual odometer and virtual compass, thus gaining reliable measurements and error models to maintain good performance during INS-only mode. In addition, the initial values for example position and heading, are given to solve global localization and loop closure problems in SLAM. Finally, a smoothing and multi-resolution map strategy are applied offline to increase the robustness and performance of the proposed grid-based SLAM. Evaluation based on experimental data shows the significant improvement by the proposed semi-tightly coupled integration scheme with low-cost INS/GNSS and LiDAR, which is able to achieve 1–2 m’ accuracy in terms of positioning and mapping. An approximately 60% improvement was achieved during long-term GNSS-denied environments using the proposed integration scheme.

Original languageEnglish
Pages (from-to)181-196
Number of pages16
JournalInformation Fusion
Volume50
DOIs
Publication statusPublished - 2019 Oct 1

Fingerprint

Inertial navigation systems
Navigation
Satellites
Extended Kalman filters
Fusion reactions
Innovation

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Information Systems
  • Hardware and Architecture

Cite this

Chiang, Kai-Wei ; Tsai, G. J. ; Chang, Hsiu-Wen ; Joly, C. ; EI-Sheimy, N. / Seamless navigation and mapping using an INS/GNSS/grid-based SLAM semi-tightly coupled integration scheme. In: Information Fusion. 2019 ; Vol. 50. pp. 181-196.
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Seamless navigation and mapping using an INS/GNSS/grid-based SLAM semi-tightly coupled integration scheme. / Chiang, Kai-Wei; Tsai, G. J.; Chang, Hsiu-Wen; Joly, C.; EI-Sheimy, N.

In: Information Fusion, Vol. 50, 01.10.2019, p. 181-196.

Research output: Contribution to journalArticle

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AU - Tsai, G. J.

AU - Chang, Hsiu-Wen

AU - Joly, C.

AU - EI-Sheimy, N.

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