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Articles | Volume XLIII-B2-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 215–220, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-215-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 215–220, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-215-2022
 
30 May 2022
30 May 2022

EVALUATION OF A COMPACT HELMET-BASED LASER SCANNING SYSTEM FOR ABOVEGROUND AND UNDERGROUND 3D MAPPING

J. Li1, B. Yang1, Y. Chen2, W. Wu1, Y. Yang1, X. Zhao1, and R. Chen3 J. Li et al.
  • 1State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
  • 2Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, Xiamen University, Xiamen 361005, China
  • 3Guangxi Zhuang Autonomous Region Remote Sensing Institute of Nature Resources, Nanning 53000, China

Keywords: HLS (helmet-based laser scanning), ubiquitous point cloud, 3D mapping, SLAM, urban underground space

Abstract. As a strategic resource, urban underground space can be used for rail transportation, commercial streets, which has high economic and social benefits, and is of great significance to sustainable city development. Due to denied Global Navigation Satellite System (GNSS) signal, traditional mobile mapping systems have difficulty collecting accurate 3D point clouds in urban underground space. Thus, a helmet-based laser scanning system, named "WHU-Helmet", is integrated in this paper to make up for the shortcomings of the existing traditional mobile mapping systems. "WHU-Helmet" is mainly equipped with four types of sensors: a GNSS receiver (optional), an IMU, a laser scanner, and a global shutter camera. "WHU-Helmet" is not relying on GNSS signal and has the advantages of low cost, small volume and easy operation. Using "WHU-Helmet", a multi-scale Normal Distributions Transform (NDT) based LiDAR-IMU SLAM is implemented to collect underground 3D point cloud in real-time. To validate the performance of "WHU-Helmet" in aboveground and underground 3D mapping, experiments were conducted in a typical urban metro station. The experiments show that the average and RMSE of HLS point errors of "WHU-Helmet" are 0.44 meters and 0.23 meters, respectively, showing great potential of "WHU-Helmet" in the application of aboveground and underground 3D mapping.