English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 55025/89277 (62%)
造访人次 : 10605417      在线人数 : 16
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜寻范围 查询小技巧:
  • 您可在西文检索词汇前后加上"双引号",以获取较精准的检索结果
  • 若欲以作者姓名搜寻,建议至进阶搜寻限定作者字段,可获得较完整数据
  • 进阶搜寻


    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/92585


    题名: Robot Simultaneous Localization and Mapping Using Speeded-Up Robust Features
    作者: Wang, Yin-tien;Chi, Chen-tung;Feng, Ying-chieh
    贡献者: 淡江大學機械與機電工程學系
    关键词: Robot Mapping;Speeded-Up Robust Features (SURF);EKF-SLAM
    日期: 2013-01-01
    上传时间: 2013-10-19 12:09:06 (UTC+8)
    出版者: Stafa-Zurich: Trans Tech Publications Ltd.
    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.
    關聯: Applied Mechanics and Materials 284-287, pp.2142-2146
    DOI: 10.4028/www.scientific.net/AMM.284-287.2142
    显示于类别:[機械與機電工程學系暨研究所] 期刊論文

    文件中的档案:

    档案 描述 大小格式浏览次数
    AMM.284-287.2142.pdf328KbAdobe PDF695检视/开启

    在機構典藏中所有的数据项都受到原著作权保护.

    TAIR相关文章

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回馈