{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,24]],"date-time":"2026-01-24T01:36:57Z","timestamp":1769218617690,"version":"3.49.0"},"reference-count":26,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2022,3,22]],"date-time":"2022-03-22T00:00:00Z","timestamp":1647907200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"China Natural Science Foundation","award":["41901412"],"award-info":[{"award-number":["41901412"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Flatness is an important parameter for the quality assessment of concrete floors. Traditional flatness inspection methods have problems with sparse sampling and low efficiency for large concrete floors. In this paper, a rapid flatness inspection method for large concrete floors based on a wheeled robot with an aided inertial navigation system (INS) is proposed. The robot realizes high precision relative to the three-dimensional profile measurement of concrete floors through fusion of INS, odometers and total station. The overall measurement of concrete floor flatness is realized through a certain density of profiles. The measurement performance of the proposed method has been tested in laboratory, and the effectivity is tested in the flatness inspection of the concrete base of an ice floor in the National Speed Skating Oval of 2022 Beijing Winter Olympic Games. The results demonstrate that the floor flatness inspection accuracy can meet the requirement of \u00b10.5 mm over 5 m and the efficiency is several times that of the traditional method. This technology is promising for high precision and rapid flatness inspection of large floors.<\/jats:p>","DOI":"10.3390\/rs14071528","type":"journal-article","created":{"date-parts":[[2022,3,22]],"date-time":"2022-03-22T23:30:23Z","timestamp":1647991823000},"page":"1528","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Rapid Inspection of Large Concrete Floor Flatness Using Wheeled Robot with Aided-INS"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8537-2409","authenticated-orcid":false,"given":"Zhipeng","family":"Chen","sequence":"first","affiliation":[{"name":"School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China"},{"name":"Guangdong Key Laboratory of Urban Informatics, Shenzhen University, Shenzhen 518060, China"},{"name":"MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area, Shenzhen University, Shenzhen 518060, China"},{"name":"Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China"}]},{"given":"Qingquan","family":"Li","sequence":"additional","affiliation":[{"name":"Guangdong Key Laboratory of Urban Informatics, Shenzhen University, Shenzhen 518060, China"},{"name":"MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area, Shenzhen University, Shenzhen 518060, China"},{"name":"Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China"},{"name":"College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518060, China"}]},{"given":"Weixin","family":"Xue","sequence":"additional","affiliation":[{"name":"School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China"},{"name":"Guangdong Key Laboratory of Urban Informatics, Shenzhen University, Shenzhen 518060, China"},{"name":"MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area, Shenzhen University, Shenzhen 518060, China"},{"name":"Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2944-445X","authenticated-orcid":false,"given":"Dejin","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China"},{"name":"Guangdong Key Laboratory of Urban Informatics, Shenzhen University, Shenzhen 518060, China"},{"name":"MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area, Shenzhen University, Shenzhen 518060, China"},{"name":"Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1054-121X","authenticated-orcid":false,"given":"Siting","family":"Xiong","sequence":"additional","affiliation":[{"name":"Guangdong Key Laboratory of Urban Informatics, Shenzhen University, Shenzhen 518060, China"},{"name":"MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area, Shenzhen University, Shenzhen 518060, China"},{"name":"Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China"},{"name":"College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518060, China"}]},{"given":"Yu","family":"Yin","sequence":"additional","affiliation":[{"name":"Guangdong Key Laboratory of Urban Informatics, Shenzhen University, Shenzhen 518060, China"},{"name":"MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area, Shenzhen University, Shenzhen 518060, China"},{"name":"Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China"},{"name":"College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518060, China"}]},{"given":"Shiwang","family":"Lv","sequence":"additional","affiliation":[{"name":"Guangdong Key Laboratory of Urban Informatics, Shenzhen University, Shenzhen 518060, China"},{"name":"MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area, Shenzhen University, Shenzhen 518060, China"},{"name":"Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China"},{"name":"College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518060, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,22]]},"reference":[{"key":"ref_1","unstructured":"General Administration of Sport of China (2006). Technical Requirements and Test Methods for Natural Material Sports Field Part 3: Ice Rink, Standards Press of China."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.autcon.2019.01.002","article-title":"Non-Contact Sensing Based Geometric Quality Assessment of Buildings and Civil Structures: A Review","volume":"100","author":"Kim","year":"2019","journal-title":"Autom. Constr."},{"key":"ref_3","unstructured":"British Standards Institution (BSI) (2009). BS 8204\u2014Screeds, Bases and In Situ Flooring, BSI."},{"key":"ref_4","unstructured":"Henry, R.S., and Ingham, J.M. (2010, January 7\u20139). Field Measurements of Concrete Floor Surface Regularity. Proceedings of the The New Zealand Concrete Industry Conference, Wellington, New Zealand."},{"key":"ref_5","unstructured":"ASTM International (2001). ASTM E 1155-96-Standard Test Method for Determining FF Floor Flatness and FL Floor Levelness Numbers, American Concrete Institute."},{"key":"ref_6","unstructured":"American Concrete Institute (ACI) (2010). Specification for Tolerances for Concrete Construction and Materials and Commentary, American Concrete Institute."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Steffey, D., Uriz, P., and Osteraas, J. (2012). Using ASTM E1155 to Determine Finished Floor Quality: Minimum Sampling Requirements Used to Establish Compliant Floor Flatness and Levelness. Forensic Engineering, American Society of Civil Engineers.","DOI":"10.1061\/9780784412640.064"},{"key":"ref_8","unstructured":"Kangas, M.A. (2017). Concrete Screeding System with Floor Quality Feedback\/Control. (9,835,610), U.S. Patent."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1061\/(ASCE)0887-3801(2006)20:3(210)","article-title":"Improved Image Analysis for Evaluating Concrete Damage","volume":"20","author":"Hutchinson","year":"2006","journal-title":"J. Comput. Civ. Eng."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1061\/(ASCE)CO.1943-7862.0000126","article-title":"Machine Vision-Based Concrete Surface Quality Assessment","volume":"136","author":"Zhu","year":"2010","journal-title":"J. Constr. Eng. Manag."},{"key":"ref_11","first-page":"129","article-title":"Comparison of Three Accurate 3D Measurement Methods for Evaluating As-Built Floor Flatness","volume":"B5","author":"Nuikka","year":"2008","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1061\/(ASCE)CP.1943-5487.0000073","article-title":"Characterization of Laser Scanners and Algorithms for Detecting Flatness Defects on Concrete Surfaces","volume":"25","author":"Tang","year":"2011","journal-title":"J. Comput. Civ. Eng."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1016\/j.autcon.2014.03.028","article-title":"Automating Surface Flatness Control Using Terrestrial Laser Scanning and Building Information Models","volume":"44","author":"Guenet","year":"2014","journal-title":"Autom. Constr."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"107436","DOI":"10.1016\/j.measurement.2019.107436","article-title":"Terrestrial Laser Scanning Assisted Flatness Quality Assessment for Two Different Types of Concrete Surfaces","volume":"154","author":"Li","year":"2020","journal-title":"Measurement"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"103077","DOI":"10.1016\/j.autcon.2020.103077","article-title":"Automated Dimensional Quality Assessment for Formwork and Rebar of Reinforced Concrete Components Using 3D Point Cloud Data","volume":"112","author":"Kim","year":"2020","journal-title":"Autom. Constr."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Li, F., Li, H., Kim, M.-K., and Lo, K.-C. (2021). Laser Scanning Based Surface Flatness Measurement Using Flat Mirrors for Enhancing Scan Coverage Range. Remote Sens., 13.","DOI":"10.3390\/rs13040714"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Niu, X., Chen, Q., Kuang, J., and Liu, J. (2016, January 11\u201314). Return of Inertial Surveying-Trend or Illusion?. Proceedings of the 2016 IEEE\/ION Position, Location and Navigation Symposium (PLANS), Savannah, GA, USA.","DOI":"10.1109\/PLANS.2016.7479697"},{"key":"ref_18","unstructured":"Groves, P.D. (2008). Principles of GNSS, Inertial, and Multi-Sensor Integrated Navigation Systems, Artech House."},{"key":"ref_19","unstructured":"(2022, January 02). Leica Nova TS60-World\u2019s Most Accurate Total Station. Available online: https:\/\/leica-geosystems.com\/products\/total-stations\/robotic-total-stations\/leica-nova-ts60."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"S\u00e4rkk\u00e4, S. (2013). Bayesian Filtering and Smoothing, Cambridge University Press.","DOI":"10.1017\/CBO9781139344203"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"320","DOI":"10.1109\/TASSP.1976.1162830","article-title":"The Generalized Correlation Method for Estimation of Time Delay","volume":"24","author":"Knapp","year":"1976","journal-title":"IEEE Trans. Acoust. Speech Signal Process."},{"key":"ref_22","unstructured":"Shin, E.-H. (2005). Estimation Techniques for Low-Cost Inertial Navigation, Doctor."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"731","DOI":"10.1109\/70.964672","article-title":"The Aiding of a Low-Cost Strapdown Inertial Measurement Unit Using Vehicle Model Constraints for Land Vehicle Applications","volume":"17","author":"Dissanayake","year":"2001","journal-title":"IEEE Trans. Robot. Autom."},{"key":"ref_24","unstructured":"(2022, January 27). Trimble DiNi Level|Digital Levels|Trimble Geospatial. Available online: https:\/\/geospatial.trimble.com\/products-and-solutions\/trimble-dini-level."},{"key":"ref_25","first-page":"123","article-title":"Key technology of dynamic high-precision construction measurement in National Speed Skating Oval and its application","volume":"8","author":"LI","year":"2021","journal-title":"Bull. Surv. Mapp."},{"key":"ref_26","unstructured":"(2022, January 27). National Speed Skating Oval Aims to Produce \u201cFastest\u201d Ice for Skaters at Beijing 2022. Available online: https:\/\/www.beijing2022.cn\/wog.htm?cmsid=MHI2021111500663300."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/7\/1528\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:40:50Z","timestamp":1760136050000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/7\/1528"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,22]]},"references-count":26,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2022,4]]}},"alternative-id":["rs14071528"],"URL":"https:\/\/doi.org\/10.3390\/rs14071528","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,3,22]]}}}