{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T03:32:38Z","timestamp":1779334358044,"version":"3.51.4"},"reference-count":23,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T00:00:00Z","timestamp":1772755200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper presents a method for material classification of objects detected by a laser scanner (LiDAR) used in autonomous mobile robot navigation. The proposed approach operates on a single-frame LiDAR scan composed of single-beam echoes and addresses materials with different reflective properties, including transparent glass surfaces. Material classification is performed by comparing measured reflection intensity profiles, defined as functions of distance and beam incidence angle, with reference profiles constructed for selected material classes. In addition to normalized reflection intensity, the gradient of the intensity profile is used to support discrimination in regions where material-dependent characteristics overlap. Experimental results obtained in indoor environments containing glass surfaces demonstrate that the proposed method enables reliable material type classification without multi-scan data accumulation or multi-sensor fusion.<\/jats:p>","DOI":"10.3390\/s26051666","type":"journal-article","created":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T11:05:44Z","timestamp":1772795144000},"page":"1666","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Material Identification of Scanned Objects Based on the Classification of the Laser Reflection Intensity Profile"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4432-1845","authenticated-orcid":false,"given":"Marcin","family":"S\u0142omiany","sequence":"first","affiliation":[{"name":"Security and Defence Systems Division, \u0141ukasiewicz Research Network\u2014Industrial Research Institute for Automation and Measurements PIAP, 02-486 Warsaw, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0721-1105","authenticated-orcid":false,"given":"Jacek","family":"Dyba\u0142a","sequence":"additional","affiliation":[{"name":"Faculty of Automotive and Construction Machinery Engineering, Warsaw University of Technology, 02-524 Warsaw, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9089-0224","authenticated-orcid":false,"given":"Grzegorz","family":"Gawdzik","sequence":"additional","affiliation":[{"name":"Security and Defence Systems Division, \u0141ukasiewicz Research Network\u2014Industrial Research Institute for Automation and Measurements PIAP, 02-486 Warsaw, Poland"},{"name":"Institute of Information Technology, Warsaw University of Life Sciences, 02-776 Warsaw, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0505-277X","authenticated-orcid":false,"given":"Mateusz","family":"Macia\u015b","sequence":"additional","affiliation":[{"name":"Security and Defence Systems Division, \u0141ukasiewicz Research Network\u2014Industrial Research Institute for Automation and Measurements PIAP, 02-486 Warsaw, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6755-1830","authenticated-orcid":false,"given":"Arkadiusz","family":"Or\u0142owski","sequence":"additional","affiliation":[{"name":"Institute of Information Technology, Warsaw University of Life Sciences, 02-776 Warsaw, Poland"},{"name":"Faculty of Cybernetics, Military University of Technology, 00-908 Warsaw, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,3,6]]},"reference":[{"key":"ref_1","unstructured":"Thrun, S., Burgard, W., and Fox, D. 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Proceedings of the 2017 IEEE International Conference on Robotics and Biomimetics (ROBIO), IEEE.","DOI":"10.1109\/ROBIO.2017.8324797"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/j.robot.2016.11.003","article-title":"Detecting glass in Simultaneous Localisation and Mapping","volume":"88","author":"Wang","year":"2017","journal-title":"Robot. Auton. Syst."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"3616","DOI":"10.1109\/TIE.2016.2523460","article-title":"Localization of a Mobile Robot Using a Laser Range Finder in a Glass-Walled Environment","volume":"63","author":"Kim","year":"2016","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Meng, J., Wang, S., Li, G., Jiang, L., Xie, Y., and Liu, C. (2020). Accurate LiDAR-based Localization in Glass-walled Environment. Proceedings of the 2020 IEEE\/ASME International Conference on Advanced Intelligent Mechatronics (AIM), IEEE.","DOI":"10.1109\/AIM43001.2020.9158915"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1108\/IJIUS-05-2018-0013","article-title":"Multi-data sensor fusion framework to detect transparent object for the efficient mobile robot mapping","volume":"7","author":"Singh","year":"2019","journal-title":"Int. J. Intell. Unmanned Syst."},{"key":"ref_9","unstructured":"Yang, S.W., and Wang, C.C. (2008). Dealing with laser scanner failure: Mirrors and windows. Proceedings of the 2008 IEEE International Conference on Robotics and Automation, IEEE."},{"key":"ref_10","first-page":"82","article-title":"Dedicated Filter for Robust Occupancy Grid Mapping","volume":"4","author":"Nagla","year":"2015","journal-title":"Int. J. Robot. Autom."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1506","DOI":"10.1080\/01691864.2020.1819873","article-title":"Online glass confidence map building using laser rangefinder for mobile robots","volume":"34","author":"Jiang","year":"2020","journal-title":"Adv. Robot."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"23517","DOI":"10.1109\/ACCESS.2023.3252909","article-title":"Intensity-Based Identification of Reflective Surfaces for Occupancy Grid Map Modification","volume":"11","author":"Mora","year":"2023","journal-title":"IEEE Access"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1016\/j.robot.2016.10.014","article-title":"Identification of transparent and specular reflective material in laser scans to discriminate affected measurements for faultless robotic SLAM","volume":"87","author":"Koch","year":"2017","journal-title":"Robot. Auton. Syst."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Blinn, J.F. (1977). Models of light reflection for computer synthesized pictures. SIGGRAPH \u201977: Proceedings of the 4th Annual Conference on Computer Graphics and Interactive Techniques, Association for Computing Machinery.","DOI":"10.1145\/563858.563893"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Tibebu, H., Roche, J., De Silva, V., and Kondoz, A. (2021). LiDAR-Based Glass Detection for Improved Occupancy Grid Mapping. Sensors, 21.","DOI":"10.3390\/s21072263"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Shan, T., Englot, B., Meyers, D., Wang, W., Ratti, C., and Rus, D. (2020). LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping. Proceedings of the 2020 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE.","DOI":"10.1109\/IROS45743.2020.9341176"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Kim, G., Ashraf, I., Eom, J., and Park, Y. (2021). Concurrent Firing Light Detection and Ranging System for Autonomous Vehicles. Remote Sens., 13.","DOI":"10.3390\/rs13091767"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"117734","DOI":"10.1016\/j.eswa.2022.117734","article-title":"A survey of state-of-the-art on visual SLAM","volume":"205","author":"Kazerouni","year":"2022","journal-title":"Expert Syst. Appl."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Klank, U., Carton, D., and Beetz, M. (2011). Transparent object detection and reconstruction on a mobile platform. Proceedings of the 2011 IEEE International Conference on Robotics and Automation, IEEE.","DOI":"10.1109\/ICRA.2011.5979793"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1109\/5254.708428","article-title":"Support vector machines","volume":"13","author":"Hearst","year":"1998","journal-title":"IEEE Intell. Syst. Their Appl."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1109\/TIT.1967.1053964","article-title":"Nearest neighbor pattern classification","volume":"13","author":"Cover","year":"1967","journal-title":"IEEE Trans. Inf. Theory"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"580","DOI":"10.1109\/TSMC.1985.6313426","article-title":"A fuzzy K-nearest neighbor algorithm","volume":"SMC-15","author":"Keller","year":"1985","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_23","unstructured":"Olson, D.L., and Delen, D. (2008). Advanced Data Mining Techniques, Springer Publishing Company, Incorporated. [1st ed.]."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/26\/5\/1666\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T11:11:10Z","timestamp":1772795470000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/26\/5\/1666"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,6]]},"references-count":23,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2026,3]]}},"alternative-id":["s26051666"],"URL":"https:\/\/doi.org\/10.3390\/s26051666","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,6]]}}}