{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T14:07:27Z","timestamp":1766066847789,"version":"build-2065373602"},"reference-count":23,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2018,2,7]],"date-time":"2018-02-07T00:00:00Z","timestamp":1517961600000},"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 an improved calibration method of a rotating two-dimensional light detection and ranging (R2D-LIDAR) system, which can obtain the 3D scanning map of the surroundings. The proposed R2D-LIDAR system, composed of a 2D LIDAR and a rotating unit, is pervasively used in the field of robotics owing to its low cost and dense scanning data. Nevertheless, the R2D-LIDAR system must be calibrated before building the geometric model because there are assembled deviation and abrasion between the 2D LIDAR and the rotating unit. Hence, the calibration procedures should contain both the adjustment between the two devices and the bias of 2D LIDAR itself. The main purpose of this work is to resolve the 2D LIDAR bias issue with a flat plane based on the Levenberg\u2013Marquardt (LM) algorithm. Experimental results for the calibration of the R2D-LIDAR system prove the reliability of this strategy to accurately estimate sensor offsets with the error range from \u221215 mm to 15 mm for the performance of capturing scans.<\/jats:p>","DOI":"10.3390\/s18020497","type":"journal-article","created":{"date-parts":[[2018,2,7]],"date-time":"2018-02-07T12:20:29Z","timestamp":1518006029000},"page":"497","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":38,"title":["An Improved Calibration Method for a Rotating 2D LIDAR System"],"prefix":"10.3390","volume":"18","author":[{"given":"Yadan","family":"Zeng","sequence":"first","affiliation":[{"name":"Quanzhou Institute of Equipment Manufacturing, Haixi Institutes, Chinese Academy of Sciences, Jinjiang 362200, China"}]},{"given":"Heng","family":"Yu","sequence":"additional","affiliation":[{"name":"Quanzhou Institute of Equipment Manufacturing, Haixi Institutes, Chinese Academy of Sciences, Jinjiang 362200, China"},{"name":"College of Electrical and Control Engineering, North University of China, Taiyuan 030051, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7417-7974","authenticated-orcid":false,"given":"Houde","family":"Dai","sequence":"additional","affiliation":[{"name":"Quanzhou Institute of Equipment Manufacturing, Haixi Institutes, Chinese Academy of Sciences, Jinjiang 362200, China"}]},{"given":"Shuang","family":"Song","sequence":"additional","affiliation":[{"name":"Harbin Institute of Technology Shenzhen Graduate School, Shenzhen 518000, China"}]},{"given":"Mingqiang","family":"Lin","sequence":"additional","affiliation":[{"name":"Quanzhou Institute of Equipment Manufacturing, Haixi Institutes, Chinese Academy of Sciences, Jinjiang 362200, China"}]},{"given":"Bo","family":"Sun","sequence":"additional","affiliation":[{"name":"Suzhou Sino-Germany Robooster Intelligent Technology Co., Ltd., Suzhou 215000, China"}]},{"given":"Wei","family":"Jiang","sequence":"additional","affiliation":[{"name":"Quanzhou Institute of Equipment Manufacturing, Haixi Institutes, Chinese Academy of Sciences, Jinjiang 362200, China"},{"name":"College of Electrical and Control Engineering, North University of China, Taiyuan 030051, China"}]},{"given":"Max","family":"Meng","sequence":"additional","affiliation":[{"name":"Harbin Institute of Technology Shenzhen Graduate School, Shenzhen 518000, China"},{"name":"Department of Electric Engineering, Chinese University of Hong Kong, Hong Kong, China"}]}],"member":"1968","published-online":{"date-parts":[[2018,2,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Ye, Y., Fu, L., and Li, B. 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