Data for: WHU-Helmet: A helmet-based multi-sensor SLAM dataset for the evaluation of real-time 3D mapping in large-scale GNSS-denied environments (doi:10.21979/N9/OYIYZV)

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Document Description

Citation

Title:

Data for: WHU-Helmet: A helmet-based multi-sensor SLAM dataset for the evaluation of real-time 3D mapping in large-scale GNSS-denied environments

Identification Number:

doi:10.21979/N9/OYIYZV

Distributor:

DR-NTU (Data)

Date of Distribution:

2023-04-08

Version:

3

Bibliographic Citation:

Li, Jianping, 2023, "Data for: WHU-Helmet: A helmet-based multi-sensor SLAM dataset for the evaluation of real-time 3D mapping in large-scale GNSS-denied environments", https://doi.org/10.21979/N9/OYIYZV, DR-NTU (Data), V3

Study Description

Citation

Title:

Data for: WHU-Helmet: A helmet-based multi-sensor SLAM dataset for the evaluation of real-time 3D mapping in large-scale GNSS-denied environments

Identification Number:

doi:10.21979/N9/OYIYZV

Authoring Entity:

Li, Jianping (Nanyang Technological University)

Software used in Production:

ROS

Grant Number:

42130105

Grant Number:

42201477

Grant Number:

41725005

Grant Number:

2022M712441

Grant Number:

2022TQ0234

Grant Number:

2022TQ0234

Distributor:

DR-NTU (Data)

Access Authority:

Li, Jianping

Depositor:

Li, Jianping

Date of Deposit:

2023-04-08

Holdings Information:

https://doi.org/10.21979/N9/OYIYZV

Study Scope

Keywords:

Computer and Information Science, Earth and Environmental Sciences, Engineering, Computer and Information Science, Earth and Environmental Sciences, Engineering, SLAM, LiDAR, Point clouds

Abstract:

Real-time 3D mapping of large-scale Global Navigation Satellite System (GNSS)-denied environments plays an important role in forest inventory management, disaster emergency response, and underground facility maintenance. Compact helmet laser scanning (HLS) systems keep the same direction as the user’s line of sight and have the advantage of “what you see is what you get”, providing a promising and efficient solution for 3D geospatial information acquisition. However, the violent motion of the helmet, the limited field of view of the laser scanner, and the repeated symmetrical geometric structures in GNSS-denied environments pose enormous challenges for the existing simultaneous localization and mapping (SLAM) algorithms. To promote the development of HLS and explore its application in large-scale GNSS-denied environments, the first large-scale HLS dataset covering multiple difficult GNSS-denied areas (e.g., forests, mountains, underground spaces) was built in this study. Besides using an additional very high accuracy fiber-optic inertial measurement unit (IMU), a novel post-processing multi-source fusion method—progressive trajectory correction (PTC)—is proposed to generate a reliable ground-truth trajectory for the benchmark, which overcomes the problems of scan matching degradation and non-rigid distortion. The accuracies of the ground truth are controlled and checked by manually surveyed feature points along the trajectory. Finally, the existing state-of-the-art SLAM methods were evaluated on the WHU-Helmet dataset, summarizing the future HLS SLAM research trends. The full dataset is available for download at: https://github.com/kafeiyin00/WHU-HelmetDataset.

Kind of Data:

ROSBAG

Methodology and Processing

Sources Statement

Data Access

Other Study Description Materials

Related Studies

<a href="https://github.com/kafeiyin00/WHU-HelmetDataset">https://github.com/kafeiyin00/WHU-HelmetDataset</a>

Related Publications

Citation

Identification Number:

10.1109/TGRS.2023.3275307

Bibliographic Citation:

Li, J., Wu, W., Yang, B., Zou, X., Yang, Y., Zhao, X., & Dong, Z. (2023). WHU-Helmet: A helmet-based multi-sensor SLAM dataset for the evaluation of real-time 3D mapping in large-scale GNSS-denied environments. IEEE Transactions on Geoscience and Remote Sensing.

Citation

Identification Number:

10356/172258

Bibliographic Citation:

Li, J., Wu, W., Yang, B., Zou, X., Yang, Y., Zhao, X. & Dong, Z. (2023). WHU-helmet: a helmet-based multisensor SLAM dataset for the evaluation of real-time 3-D mapping in large-scale GNSS-denied environments. IEEE Transactions On Geoscience and Remote Sensing, 61, 3275307-.

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