{"title":"用于户外巡逻机器人的单激光测距仪可驾驶道路区域检测","authors":"Youjin Shin, C. Jung, W. Chung","doi":"10.1109/IVS.2010.5548080","DOIUrl":null,"url":null,"abstract":"For outdoor navigation, it is necessary to find the relevant features of outdoor road environments and detect drivable region for robot's motion. This paper presents a methodology for extracting the drivable road region by detecting the prominent road features and obstacles through a single laser range finder. The prominent features of roads are curbs and the road surface. The laser range finder is mounted on the mobile robot, looks down the road with a small tilt angle, and obtains two-dimensional range data. The proposed method is computationally more efficient in comparison with vision-based techniques and applicable for various road conditions in target environment. Experimental results confirm the reliability of the algorithm.","PeriodicalId":123266,"journal":{"name":"2010 IEEE Intelligent Vehicles Symposium","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"33","resultStr":"{\"title\":\"Drivable road region detection using a single laser range finder for outdoor patrol robots\",\"authors\":\"Youjin Shin, C. Jung, W. Chung\",\"doi\":\"10.1109/IVS.2010.5548080\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For outdoor navigation, it is necessary to find the relevant features of outdoor road environments and detect drivable region for robot's motion. This paper presents a methodology for extracting the drivable road region by detecting the prominent road features and obstacles through a single laser range finder. The prominent features of roads are curbs and the road surface. The laser range finder is mounted on the mobile robot, looks down the road with a small tilt angle, and obtains two-dimensional range data. The proposed method is computationally more efficient in comparison with vision-based techniques and applicable for various road conditions in target environment. Experimental results confirm the reliability of the algorithm.\",\"PeriodicalId\":123266,\"journal\":{\"name\":\"2010 IEEE Intelligent Vehicles Symposium\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-06-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"33\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE Intelligent Vehicles Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IVS.2010.5548080\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE Intelligent Vehicles Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IVS.2010.5548080","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Drivable road region detection using a single laser range finder for outdoor patrol robots
For outdoor navigation, it is necessary to find the relevant features of outdoor road environments and detect drivable region for robot's motion. This paper presents a methodology for extracting the drivable road region by detecting the prominent road features and obstacles through a single laser range finder. The prominent features of roads are curbs and the road surface. The laser range finder is mounted on the mobile robot, looks down the road with a small tilt angle, and obtains two-dimensional range data. The proposed method is computationally more efficient in comparison with vision-based techniques and applicable for various road conditions in target environment. Experimental results confirm the reliability of the algorithm.
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