Zhitao Wang, Yo-Seop Hwang, Yun-ki Kim, Donghyuk Lee, Jangmyung Lee
{"title":"基于LRF传感器的SURF算法移动机器人室内定位","authors":"Zhitao Wang, Yo-Seop Hwang, Yun-ki Kim, Donghyuk Lee, Jangmyung Lee","doi":"10.1109/SICE.2015.7285500","DOIUrl":null,"url":null,"abstract":"In this paper we proposed a method to implement estimation of mobile robot's position by using SURF (Speeded Up Robust Features) algorithm based on depth image in indoor environment. SURF which is derived from SIFT algorithm has the advantage of fast calculation speed and a strong robustness. The depth image is generated from a 2D LRF (Laser Range Finder) sensor which is controlled to rotate around its y-axis. According to the interest points in each frame of depth image, we find the position relationship between each two frames and make a match between the corresponding interest points. In the experiment, we will show the implementation of position estimation using the method we proposed in this paper. The accuracy and efficiency of the proposed method has also been proved in the experiment.","PeriodicalId":405766,"journal":{"name":"Annual Conference of the Society of Instrument and Control Engineers of Japan","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Mobile robot indoor localization using SURF algorithm based on LRF sensor\",\"authors\":\"Zhitao Wang, Yo-Seop Hwang, Yun-ki Kim, Donghyuk Lee, Jangmyung Lee\",\"doi\":\"10.1109/SICE.2015.7285500\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we proposed a method to implement estimation of mobile robot's position by using SURF (Speeded Up Robust Features) algorithm based on depth image in indoor environment. SURF which is derived from SIFT algorithm has the advantage of fast calculation speed and a strong robustness. The depth image is generated from a 2D LRF (Laser Range Finder) sensor which is controlled to rotate around its y-axis. According to the interest points in each frame of depth image, we find the position relationship between each two frames and make a match between the corresponding interest points. In the experiment, we will show the implementation of position estimation using the method we proposed in this paper. The accuracy and efficiency of the proposed method has also been proved in the experiment.\",\"PeriodicalId\":405766,\"journal\":{\"name\":\"Annual Conference of the Society of Instrument and Control Engineers of Japan\",\"volume\":\"76 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-07-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annual Conference of the Society of Instrument and Control Engineers of Japan\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SICE.2015.7285500\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annual Conference of the Society of Instrument and Control Engineers of Japan","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SICE.2015.7285500","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mobile robot indoor localization using SURF algorithm based on LRF sensor
In this paper we proposed a method to implement estimation of mobile robot's position by using SURF (Speeded Up Robust Features) algorithm based on depth image in indoor environment. SURF which is derived from SIFT algorithm has the advantage of fast calculation speed and a strong robustness. The depth image is generated from a 2D LRF (Laser Range Finder) sensor which is controlled to rotate around its y-axis. According to the interest points in each frame of depth image, we find the position relationship between each two frames and make a match between the corresponding interest points. In the experiment, we will show the implementation of position estimation using the method we proposed in this paper. The accuracy and efficiency of the proposed method has also been proved in the experiment.