{"title":"基于特征的同步定位和映射","authors":"T. R. Gayathri, R. P. Aneesh, G. Nayar","doi":"10.1109/ICCS1.2017.8326034","DOIUrl":null,"url":null,"abstract":"Simultaneous Localisation and Mapping (SLAM) is a new technique in Robotics used to track moving objects. In this paper, a graph based SLAM is proposed to map the trajectory with line features. This system extracts both line and point features from the scene. The line features are used mostly because point features are less informative. This algorithm is designed and developed with line features by modeling the moving objects. The position of these objects is identified with indoor and outdoor datasets. ‘Kitty’ dataset are used for testing this algorithm. Stereovision cameras are used to capture the real time data. The shape, color and depth features are also extracted to plot the trajectory. This method has been successfully implemented with real time data.","PeriodicalId":367360,"journal":{"name":"2017 IEEE International Conference on Circuits and Systems (ICCS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Feature based simultaneous localisation and mapping\",\"authors\":\"T. R. Gayathri, R. P. Aneesh, G. Nayar\",\"doi\":\"10.1109/ICCS1.2017.8326034\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Simultaneous Localisation and Mapping (SLAM) is a new technique in Robotics used to track moving objects. In this paper, a graph based SLAM is proposed to map the trajectory with line features. This system extracts both line and point features from the scene. The line features are used mostly because point features are less informative. This algorithm is designed and developed with line features by modeling the moving objects. The position of these objects is identified with indoor and outdoor datasets. ‘Kitty’ dataset are used for testing this algorithm. Stereovision cameras are used to capture the real time data. The shape, color and depth features are also extracted to plot the trajectory. This method has been successfully implemented with real time data.\",\"PeriodicalId\":367360,\"journal\":{\"name\":\"2017 IEEE International Conference on Circuits and Systems (ICCS)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE International Conference on Circuits and Systems (ICCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCS1.2017.8326034\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Circuits and Systems (ICCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCS1.2017.8326034","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Feature based simultaneous localisation and mapping
Simultaneous Localisation and Mapping (SLAM) is a new technique in Robotics used to track moving objects. In this paper, a graph based SLAM is proposed to map the trajectory with line features. This system extracts both line and point features from the scene. The line features are used mostly because point features are less informative. This algorithm is designed and developed with line features by modeling the moving objects. The position of these objects is identified with indoor and outdoor datasets. ‘Kitty’ dataset are used for testing this algorithm. Stereovision cameras are used to capture the real time data. The shape, color and depth features are also extracted to plot the trajectory. This method has been successfully implemented with real time data.