Analysis of Lidar Actuator System Influence on the Quality of Dense 3D Point Cloud Obtained with SLAM
Author:
Trybała PawełORCID, Szrek JarosławORCID, Dębogórski Błażej, Ziętek BartłomiejORCID, Blachowski JanORCID, Wodecki JacekORCID, Zimroz RadosławORCID
Abstract
Mobile mapping technologies, based on techniques such as simultaneous localization and mapping (SLAM) and surface-from-motion (SfM), are being vigorously developed both in the scientific community and in industry. They are crucial concepts for automated 3D surveying and autonomous vehicles. For various applications, rotating multiline scanners, manufactured, for example, by Velodyne and Ouster, are utilized as the main sensor of the mapping hardware system. However, their principle of operation has a substantial drawback, as their scanning pattern creates natural gaps between the scanning lines. In some models, the vertical lidar field of view can also be severely limited. To overcome these issues, more sensors could be employed, which would significantly increase the cost of the mapping system. Instead, some investigators have added a tilting or rotating motor to the lidar. Although the effectiveness of such a solution is usually clearly visible, its impact on the quality of the acquired 3D data has not yet been investigated. This paper presents an adjustable mapping system, which allows for switching between a stable, tilting or fully rotating lidar position. A simple experiment in a building corridor was performed, simulating the conditions of a mobile robot passing through a narrow tunnel: a common setting for applications, such as mining surveying or industrial facility inspection. A SLAM algorithm is utilized to create a coherent 3D point cloud of the mapped corridor for three settings of the sensor movement. The extent of improvement in the 3D data quality when using the tilting and rotating lidar, compared to keeping a stable position, is quantified. Different metrics are proposed to account for different aspects of the 3D data quality, such as completeness, density and geometry coherence. The ability of SLAM algorithms to faithfully represent selected objects appearing in the mapped scene is also examined. The results show that the fully rotating solution is optimal in terms of most of the metrics analyzed. However, the improvement observed from a horizontally mounted sensor to a tilting sensor was the most significant.
Funder
European Institute of Technology Raw Materials GmbH
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Reference44 articles.
1. Alismail, H., Baker, L.D., and Browning, B. (2014–7, January 31). Continuous trajectory estimation for 3D SLAM from actuated lidar. Proceedings of the 2014 IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China. 2. Kubota, N., Kiguchi, K., Liu, H., and Obo, T. (2016, January 22–24). A Rotating Platform for Swift Acquisition of Dense 3D Point Clouds. Proceedings of the Intelligent Robotics and Applications, Tokyo, Japan. 3. Huang, L. (2021, January 14). Review on LiDAR-based SLAM Techniques. Proceedings of the 2021 International Conference on Signal Processing and Machine Learning (CONF-SPML), Stanford, CA, USA. 4. Xu, X., Zhang, L., Yang, J., Cao, C., Wang, W., Ran, Y., Tan, Z., and Luo, M. (2022). A Review of Multi-Sensor Fusion SLAM Systems Based on 3D LIDAR. Remote Sens., 14. 5. Wei, W., Shirinzadeh, B., Nowell, R., Ghafarian, M., Ammar, M.M.A., and Shen, T. (2021). Enhancing Solid State LiDAR Mapping with a 2D Spinning LiDAR in Urban Scenario SLAM on Ground Vehicles. Sensors, 21.
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|