{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T10:15:38Z","timestamp":1768904138161,"version":"3.49.0"},"reference-count":35,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2018,5,29]],"date-time":"2018-05-29T00:00:00Z","timestamp":1527552000000},"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":["61305117"],"award-info":[{"award-number":["61305117"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U1713223"],"award-info":[{"award-number":["U1713223"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Industry-University Cooperation Project of Fujian Province","award":["2017H6101"],"award-info":[{"award-number":["2017H6101"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Environment perception is important for collision-free motion planning of outdoor mobile robots. This paper presents an adaptive obstacle detection method for outdoor mobile robots using a single downward-looking LiDAR sensor. The method begins by extracting line segments from the raw sensor data, and then estimates the height and the vector of the scanned road surface at each moment. Subsequently, the segments are divided into either road ground or obstacles based on the average height of each line segment and the deviation between the line segment and the road vector estimated from the previous measurements. A series of experiments have been conducted in several scenarios, including normal scenes and complex scenes. The experimental results show that the proposed approach can accurately detect obstacles on roads and could effectively deal with the different heights of obstacles in urban road environments.<\/jats:p>","DOI":"10.3390\/s18061749","type":"journal-article","created":{"date-parts":[[2018,5,30]],"date-time":"2018-05-30T03:04:27Z","timestamp":1527649467000},"page":"1749","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Adaptive Obstacle Detection for Mobile Robots in Urban Environments Using Downward-Looking 2D LiDAR"],"prefix":"10.3390","volume":"18","author":[{"given":"Cong","family":"Pang","sequence":"first","affiliation":[{"name":"Department of Automation, Xiamen University, Xiamen 361102, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3263-1486","authenticated-orcid":false,"given":"Xunyu","family":"Zhong","sequence":"additional","affiliation":[{"name":"Department of Automation, Xiamen University, Xiamen 361102, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5797-1412","authenticated-orcid":false,"given":"Huosheng","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Electronic Engineering, University of Essex, Wivenhoe Park, Colchester, Essex CO4 3SQ, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Tian","sequence":"additional","affiliation":[{"name":"Department of Automation, Xiamen University, Xiamen 361102, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiafu","family":"Peng","sequence":"additional","affiliation":[{"name":"Department of Automation, Xiamen University, Xiamen 361102, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianping","family":"Zeng","sequence":"additional","affiliation":[{"name":"Department of Automation, Xiamen University, Xiamen 361102, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,5,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1109\/JSEN.2015.2480742","article-title":"Pedestrian\/vehicle detection using a 2.5-d multi-layer laser scanner","volume":"16","author":"Kim","year":"2016","journal-title":"IEEE Sens. 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