{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T16:37:51Z","timestamp":1775147871737,"version":"3.50.1"},"reference-count":44,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,1,8]],"date-time":"2023-01-08T00:00:00Z","timestamp":1673136000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Institute of Innovation and Technology (EIT)","award":["19018"],"award-info":[{"award-number":["19018"]}]},{"name":"European Institute of Innovation and Technology (EIT)","award":["5163\/KAVA\/2020\/2021\/2"],"award-info":[{"award-number":["5163\/KAVA\/2020\/2021\/2"]}]},{"name":"EIT RawMaterials GmbH","award":["19018"],"award-info":[{"award-number":["19018"]}]},{"name":"EIT RawMaterials GmbH","award":["5163\/KAVA\/2020\/2021\/2"],"award-info":[{"award-number":["5163\/KAVA\/2020\/2021\/2"]}]},{"name":"Minister of Science and Higher Education","award":["19018"],"award-info":[{"award-number":["19018"]}]},{"name":"Minister of Science and Higher Education","award":["5163\/KAVA\/2020\/2021\/2"],"award-info":[{"award-number":["5163\/KAVA\/2020\/2021\/2"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/s23020721","type":"journal-article","created":{"date-parts":[[2023,1,9]],"date-time":"2023-01-09T07:05:09Z","timestamp":1673247909000},"page":"721","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Analysis of Lidar Actuator System Influence on the Quality of Dense 3D Point Cloud Obtained with SLAM"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6486-1147","authenticated-orcid":false,"given":"Pawe\u0142","family":"Tryba\u0142a","sequence":"first","affiliation":[{"name":"Faculty of Geoengineering, Mining and Geology, Wroc\u0142aw University of Science and Technology, Na Grobli 15, 50-421 Wroclaw, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2067-4577","authenticated-orcid":false,"given":"Jaros\u0142aw","family":"Szrek","sequence":"additional","affiliation":[{"name":"Faculty of Mechanical Engineering, Wroclaw University of Science and Technology, \u0141ukasiewicza 5, 50-371 Wroclaw, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"B\u0142a\u017cej","family":"D\u0119bog\u00f3rski","sequence":"additional","affiliation":[{"name":"Faculty of Geoengineering, Mining and Geology, Wroc\u0142aw University of Science and Technology, Na Grobli 15, 50-421 Wroclaw, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6301-056X","authenticated-orcid":false,"given":"Bart\u0142omiej","family":"Zi\u0119tek","sequence":"additional","affiliation":[{"name":"Faculty of Geoengineering, Mining and Geology, Wroc\u0142aw University of Science and Technology, Na Grobli 15, 50-421 Wroclaw, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2630-3459","authenticated-orcid":false,"given":"Jan","family":"Blachowski","sequence":"additional","affiliation":[{"name":"Faculty of Geoengineering, Mining and Geology, Wroc\u0142aw University of Science and Technology, Na Grobli 15, 50-421 Wroclaw, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3163-8678","authenticated-orcid":false,"given":"Jacek","family":"Wodecki","sequence":"additional","affiliation":[{"name":"Faculty of Geoengineering, Mining and Geology, Wroc\u0142aw University of Science and Technology, Na Grobli 15, 50-421 Wroclaw, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4781-9972","authenticated-orcid":false,"given":"Rados\u0142aw","family":"Zimroz","sequence":"additional","affiliation":[{"name":"Faculty of Geoengineering, Mining and Geology, Wroc\u0142aw University of Science and Technology, Na Grobli 15, 50-421 Wroclaw, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Alismail, H., Baker, L.D., and Browning, B. (2014\u20137, 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.","DOI":"10.1109\/ICRA.2014.6907757"},{"key":"ref_2","unstructured":"Kubota, N., Kiguchi, K., Liu, H., and Obo, T. (2016, January 22\u201324). A Rotating Platform for Swift Acquisition of Dense 3D Point Clouds. Proceedings of the Intelligent Robotics and Applications, Tokyo, Japan."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"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.","DOI":"10.1109\/CONF-SPML54095.2021.00040"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"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.","DOI":"10.3390\/rs14122835"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"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.","DOI":"10.3390\/s21051773"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1104","DOI":"10.1109\/TRO.2012.2200990","article-title":"Zebedee: Design of a spring-mounted 3-d range sensor with application to mobile mapping","volume":"28","author":"Bosse","year":"2012","journal-title":"IEEE Trans. Robot."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Yoshida, T., Irie, K., Koyanagi, E., and Tomono, M. (2011, January 9\u201313). 3D laser scanner with gazing ability. Proceedings of the 2011 IEEE International Conference on Robotics and Automation, Shanghai, China.","DOI":"10.1109\/ICRA.2011.5980385"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2692","DOI":"10.1109\/LRA.2022.3144795","article-title":"ART-SLAM: Accurate Real-Time 6DoF LiDAR SLAM","volume":"7","author":"Frosi","year":"2022","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Bosse, M., and Zlot, R. (2009, January 12\u201317). Continuous 3D scan-matching with a spinning 2D laser. Proceedings of the 2009 IEEE International Conference on Robotics and Automation, Kobe, Japan.","DOI":"10.1109\/ROBOT.2009.5152851"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"723","DOI":"10.1002\/rob.21543","article-title":"Automatic Calibration of Spinning Actuated Lidar Internal Parameters","volume":"32","author":"Alismail","year":"2015","journal-title":"J. Field Robot."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"5261","DOI":"10.1109\/TGRS.2018.2812782","article-title":"Bias impact analysis and calibration of terrestrial mobile lidar system with several spinning multibeam laser scanners","volume":"56","author":"Ravi","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Yu, Y., Zhang, W., Yang, F., and Li, G. (2022). Rate-Distortion Optimized Geometry Compression for Spinning LiDAR Point Cloud. IEEE Trans. Multimed. (Early Access).","DOI":"10.1109\/TMM.2022.3154160"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Lehtola, V.V., Kaartinen, H., N\u00fcchter, A., Kaijaluoto, R., Kukko, A., Litkey, P., Honkavaara, E., Rosnell, T., Vaaja, M.T., and Virtanen, J.P. (2017). Comparison of the Selected State-Of-The-Art 3D Indoor Scanning and Point Cloud Generation Methods. Remote Sens., 9.","DOI":"10.3390\/rs9080796"},{"key":"ref_14","unstructured":"Pauly, M., Gross, M., and Kobbelt, L.P. (November, January 27). Efficient simplification of point-sampled surfaces. Proceedings of the IEEE Visualization, 2002, VIS 2002, Boston, MA, USA."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"269","DOI":"10.5194\/isprsannals-I-3-269-2012","article-title":"Diagnostic-robust statistical analysis for local surface fitting in 3D point cloud data","volume":"I-3","author":"Nurunnabi","year":"2012","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Mohammadi, M.E., Wood, R.L., and Wittich, C.E. (2019). Non-temporal point cloud analysis for surface damage in civil structures. ISPRS Int. J. Geo-Inf., 8.","DOI":"10.3390\/ijgi8120527"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Tan, Y., and Li, Y. (2019). UAV Photogrammetry-Based 3D Road Distress Detection. ISPRS Int. J. Geo-Inf., 8.","DOI":"10.3390\/ijgi8090409"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1177\/0278364906061157","article-title":"Automatic three-dimensional underground mine mapping","volume":"25","author":"Huber","year":"2006","journal-title":"Int. J. Robot. Res."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Nuchter, A., Surmann, H., Lingemann, K., Hertzberg, J., and Thrun, S. (May, January 26). 6D SLAM with an application in autonomous mine mapping. Proceedings of the IEEE International Conference on Robotics and Automation, 2004. Proceedings, ICRA \u201904, 2004, New Orleans, LA, USA.","DOI":"10.1109\/ROBOT.2004.1308117"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Ren, Z., Wang, L., and Bi, L. (2019). Robust GICP-based 3D LiDAR SLAM for underground mining environment. Sensors, 19.","DOI":"10.3390\/s19132915"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Reyhanoglu, M., and Cubber, G.D. (2020). A System for Continuous Underground Site Mapping and Exploration. Unmanned Robotic Systems and Applications, IntechOpen. Chapter 4.","DOI":"10.5772\/intechopen.77608"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"758","DOI":"10.1002\/rob.21504","article-title":"Efficient large-scale three-dimensional mobile mapping for underground mines","volume":"31","author":"Zlot","year":"2014","journal-title":"J. Field Robot."},{"key":"ref_23","first-page":"1939","article-title":"Analysis of SLAM-Based Lidar Data Quality Metrics for Geotechnical Underground Monitoring","volume":"39","author":"Fahle","year":"2022","journal-title":"Mining Metall. Explor."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"14124","DOI":"10.1109\/ACCESS.2018.2889304","article-title":"Efficient Laser-Based 3D SLAM for Coal Mine Rescue Robots","volume":"7","author":"Li","year":"2019","journal-title":"IEEE Access"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1080\/00396265.2021.1944545","article-title":"Advancements in underground mine surveys by using SLAM-enabled handheld laser scanners","volume":"54","author":"Ellmann","year":"2021","journal-title":"Surv. Rev."},{"key":"ref_26","unstructured":"Ebadi, K., Bernreiter, L., Biggie, H., Catt, G., Chang, Y., Chatterjee, A., Denniston, C.E., Desch\u00eanes, S.P., Harlow, K., and Khattak, S. (2022). Present and future of slam in extreme underground environments. arXiv."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Zhang, J., and Singh, S. (2014, January 12\u201316). LOAM: Lidar Odometry and Mapping in Real-time. Proceedings of the Robotics: Science and Systems, Berkeley, CA, USA.","DOI":"10.15607\/RSS.2014.X.007"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Kim, G., and Kim, A. (2018, January 1\u20135). Scan Context: Egocentric Spatial Descriptor for Place Recognition within 3D Point Cloud Map. Proceedings of the Proceedings of the IEEE\/RSJ International Conference on Intelligent Robots and Systems, Madrid, Spain.","DOI":"10.1109\/IROS.2018.8593953"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1856","DOI":"10.1109\/TRO.2021.3116424","article-title":"Scan context++: Structural place recognition robust to rotation and lateral variations in urban environments","volume":"38","author":"Kim","year":"2021","journal-title":"IEEE Trans. Robot."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1109\/TRO.2011.2170332","article-title":"Visual-Inertial-Aided Navigation for High-Dynamic Motion in Built Environments Without Initial Conditions","volume":"28","author":"Lupton","year":"2012","journal-title":"IEEE Trans. Robot."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Carlone, L., Kira, Z., Beall, C., Indelman, V., and Dellaert, F. (June, January 31). Eliminating conditionally independent sets in factor graphs: A unifying perspective based on smart factors. Proceedings of the 2014 IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China.","DOI":"10.1109\/ICRA.2014.6907483"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Forster, C., Carlone, L., Dellaert, F., and Scaramuzza, D. (2015, January 13\u201317). IMU Preintegration on Manifold for Efficient Visual-Inertial Maximum-a-Posteriori Estimation. Proceedings of the Robotics: Science and Systems Conference, Rome, Italy.","DOI":"10.15607\/RSS.2015.XI.006"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Foote, T. (2013, January 22\u201323). tf: The transform library. Proceedings of the 2013 IEEE Conference on Technologies for Practical Robot Applications (TePRA), Woburn, MA, USA.","DOI":"10.1109\/TePRA.2013.6556373"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Kim, G., and Kim, A. (2020\u201324, January 24). Remove, then Revert: Static Point cloud Map Construction using Multiresolution Range Images. Proceedings of the 2020 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Las Vegas, NV, USA.","DOI":"10.1109\/IROS45743.2020.9340856"},{"key":"ref_35","unstructured":"Olson, E., and Kaess, M. (2009, January 28). Evaluating the performance of map optimization algorithms. Proceedings of the RSS Workshop on Good Experimental Methodology in Robotics, Seattle, WA, USA."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1007\/s10514-009-9155-6","article-title":"On measuring the accuracy of SLAM algorithms","volume":"27","author":"Steder","year":"2009","journal-title":"Auton. Robot."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"He, Y., Hu, Z., Wu, K., and Wang, R. (2021). A Novel Method for Density Analysis of Repaired Point Cloud with Holes Based on Image Data. Remote Sens., 13.","DOI":"10.3390\/rs13173417"},{"key":"ref_38","first-page":"97","article-title":"Dimensionality based scale selection in 3D lidar point clouds","volume":"XXXVIII-5\/W12","author":"Mallet","year":"2011","journal-title":"Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Hackel, T., Wegner, J.D., and Schindler, K. (2016, January 27\u201330). Contour detection in unstructured 3D point clouds. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.178"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"9","DOI":"10.5194\/isprsannals-II-3-9-2014","article-title":"Shape distribution features for point cloud analysis-a geometric histogram approach on multiple scales","volume":"2","author":"Blomley","year":"2014","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_41","unstructured":"Huang, C., and Tseng, Y.H. (2008, January 10\u201314). Plane fitting methods of LiDAR point cloud. Proceedings of the 29th Asian Conference on Remote Sensing 2008, ACRS 2008, Colombo, Sri Lanka."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/0146-664X(82)90104-6","article-title":"Geometric modeling using octree encoding","volume":"19","author":"Meagher","year":"1982","journal-title":"Comput. Graph. Image Process."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"103675","DOI":"10.1016\/j.autcon.2021.103675","article-title":"Voxel-based representation of 3D point clouds: Methods, applications, and its potential use in the construction industry","volume":"126","author":"Xu","year":"2021","journal-title":"Autom. Constr."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Quigley, M., Conley, K., Gerkey, B., Faust, J., Foote, T., Leibs, J., Berger, E., Wheeler, R., and Ng, A.Y. (2009, January 12\u201317). ROS: An open-source Robot Operating System. Proceedings of the ICRA Workshop on Open Source Software, Kobe, Japan.","DOI":"10.1109\/MRA.2010.936956"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/2\/721\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:03:39Z","timestamp":1760119419000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/2\/721"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,8]]},"references-count":44,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2023,1]]}},"alternative-id":["s23020721"],"URL":"https:\/\/doi.org\/10.3390\/s23020721","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1,8]]}}}