教師資料查詢 | 類別: 期刊論文 | 教師: 王銀添 Wang Yin-tien (瀏覽個人網頁)

標題:Robot Simultaneous Localization and Mapping Using Speeded-Up Robust Features
學年101
學期1
出版(發表)日期2013/01/01
作品名稱Robot Simultaneous Localization and Mapping Using Speeded-Up Robust Features
作品名稱(其他語言)
著者Wang, Yin-tien; Chi, Chen-tung; Feng, Ying-chieh
單位淡江大學機械與機電工程學系
出版者Stafa-Zurich: Trans Tech Publications Ltd.
著錄名稱、卷期、頁數Applied Mechanics and Materials 284-287, pp.2142-2146
摘要An algorithm for robot mapping is proposed in this paper using the method of speeded-up robust features (SURF). Since SURFs are scale- and orientation-invariant features, they have higher repeatability than that of the features obtained by other detection methods. Even in the cases of using moving camera, the SURF method can robustly extract the features from image sequences. Therefore, SURFs are suitable to be utilized as the map features in visual simultaneous localization and mapping (SLAM). In this article, the procedures of detection and matching of the SURF method are modified to improve the image processing speed and feature recognition rate. The sparse representation of SURF is also utilized to describe the environmental map in SLAM tasks. The purpose is to reduce the computation complexity in state estimation using extended Kalman filter (EKF). The EKF SLAM with SURF-based map is developed and implemented on a binocular vision system. The integrated system has been successfully validated to fulfill the basic capabilities of SLAM system.
關鍵字Robot Mapping;Speeded-Up Robust Features (SURF);EKF-SLAM
語言英文
ISSN1662-7482
期刊性質國外
收錄於EI;
產學合作
通訊作者Wang, Y.T.
審稿制度
國別瑞士
公開徵稿
出版型式,電子版,紙本
相關連結
Google+ 推薦功能,讓全世界都能看到您的推薦!