English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 54043/88873 (61%)
造访人次 : 10548285      在线人数 : 36
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/987654321/116051

    题名: Cloud-Based Improved Monte Carlo Localization Algorithm with Robust Orientation Estimation for Mobile Robots
    作者: Li, I.H.;Wang, W.Y.;Li, C.Y.;Kao, J.Z.;Hsu, C.C.
    关键词: Robotics;Cloud computing;Particle filter;Monte Carlo localization
    日期: 2018-09-18
    上传时间: 2019-03-23 12:11:00 (UTC+8)
    出版者: Emerald
    摘要: Purpose
    This paper aims to demonstrate a cloud-based version of the improved Monte Carlo localization algorithm with robust orientation estimation (IMCLROE). The purpose of this system is to increase the accuracy and efficiency of indoor robot localization.

    The cloud-based IMCLROE is constructed with a cloud–client architecture that distributes computation between servers and a client robot. The system operates in two phases: in the offline phase, two maps are built under the MapReduce framework. This framework allows parallel and even distribution of map information to a cloud database in pre-described formats. In the online phase, an Apache HBase is adopted to calculate a pose in-memory and promptly send the result to the client robot. To demonstrate the efficiency of the cloud-based IMCLROE, a two-step experiment is conducted: first, a mobile robot implemented with a non-cloud IMCLROE and a UDOO single-board computer is tested for its efficiency on pose-estimation accuracy. Then, a cloud-based IMCLROE is implemented on a cloud–client architecture to demonstrate its efficiency on both pose-estimation accuracy and computation ability.

    For indoor localization, the cloud-based IMCLROE is much more effective in acquiring pose-estimation accuracy and relieving computation burden than the non-cloud system.

    The cloud-based IMCLROE achieves efficiency of indoor localization by using three innovative strategies: firstly, with the help of orientation estimation and weight calculation (OEWC), the system can sort out the best orientation. Secondly, the system reduces computation burden with map pre-caching. Thirdly, the cloud–client architecture distributes computation between the servers and client robot. Finally, the similar energy region (SER) technique provides a high-possibility region to the system, allowing the client robot to locate itself in a short time.
    關聯: Engineering Computation 36(1), p.178-203
    DOI: 10.1108/EC-03-2017-0081
    显示于类别:[機械與機電工程學系暨研究所] 期刊論文


    档案 描述 大小格式浏览次数
    Cloud-based improved Monte Carlo localization algorithm with robust orientation estimation for mobile robots.pdf723KbAdobe PDF0检视/开启



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