{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,8]],"date-time":"2025-11-08T17:50:24Z","timestamp":1762624224805,"version":"build-2065373602"},"reference-count":30,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2019,9,25]],"date-time":"2019-09-25T00:00:00Z","timestamp":1569369600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51804278","51504219"],"award-info":[{"award-number":["51804278","51504219"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Scientific Research Projects of Universities of Henan","award":["20A620005"],"award-info":[{"award-number":["20A620005"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Light detection and ranging (LiDAR) is one of the popular technologies to acquire critical information for building information modelling. To allow an automatic acquirement of building information, the first and most important step of LiDAR technology is to accurately determine the important gesture information that micro electromechanical (MEMS) based inertial measurement unit (IMU) sensors can provide from the moving robot. However, during the practical building mapping, serious errors may happen due to the inappropriate installation of a MEMS-IMU. Through this study, we analyzed the different systematic errors, such as biases, scale errors, and axial installation deviation, that happened during the building mapping, based on a robot equipped with MEMS-IMU. Based on this, an error calibration model was developed. The problems of the deviation between the calibrated and horizontal planes were solved by a new sampling method. For this method, the calibrated plane was rotated twice; the gravity acceleration of the six sides of the MEMS-IMU was also calibrated by the practical values, and the whole calibration process was completed after solving developed model based on the least-squares method. Finally, the building mapping was then calibrated based on the error calibration model, and also the Gmapping algorithm. It was indicated from the experiments that the proposed model is useful for the error calibration, which can increase the prediction accuracy of yaw by 1\u20132\u00b0 based on MEMS-IMU; the mapping results are more accurate when compared to the previous methods. The research outcomes can provide a practical basis for the construction of the building information modelling model.<\/jats:p>","DOI":"10.3390\/s19194150","type":"journal-article","created":{"date-parts":[[2019,9,26]],"date-time":"2019-09-26T03:06:51Z","timestamp":1569467211000},"page":"4150","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["An Onsite Calibration Method for MEMS-IMU in Building Mapping Fields"],"prefix":"10.3390","volume":"19","author":[{"given":"Sen","family":"Li","sequence":"first","affiliation":[{"name":"School of Building Environment Engineering, Zhengzhou University of Light Industry, 5 Dongfeng Road, Zhengzhou 450002, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunchen","family":"Niu","sequence":"additional","affiliation":[{"name":"School of Building Environment Engineering, Zhengzhou University of Light Industry, 5 Dongfeng Road, Zhengzhou 450002, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chunyong","family":"Feng","sequence":"additional","affiliation":[{"name":"School of Building Environment Engineering, Zhengzhou University of Light Industry, 5 Dongfeng Road, Zhengzhou 450002, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haiqiang","family":"Liu","sequence":"additional","affiliation":[{"name":"China Academy of Electronics and Information Technology, 11 Shuangyuan Road, Beijing 100041, China"},{"name":"XinJiang Lianhai INA-INT Information Technology Ltd., 567 Dongrong Street, Urumqi 830000, Xinjiang, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dan","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Building Environment Engineering, Zhengzhou University of Light Industry, 5 Dongfeng Road, Zhengzhou 450002, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hengjie","family":"Qin","sequence":"additional","affiliation":[{"name":"School of Building Environment Engineering, Zhengzhou University of Light Industry, 5 Dongfeng Road, Zhengzhou 450002, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,9,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1537","DOI":"10.1016\/j.jclepro.2019.04.156","article-title":"Digital twin aided sustainability-based lifecycle management for railway turnout systems","volume":"228","author":"Kaewunruen","year":"2019","journal-title":"J. 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