English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 63184/95884 (66%)
造访人次 : 4527935      在线人数 : 274
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: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/118052


    题名: Highly autonomous visualization map-generation mobile robot system design through the robot operating system platform
    作者: Shih-An Li, Hsuan-Ming Feng, Kung-Han Chen and Wen-Hung Huang
    日期: 2018-05
    上传时间: 2020-01-21 12:10:50 (UTC+8)
    摘要: This article proposes highly autonomous map generation and path navigation based on the Robot Operating System (ROS) platform. The mobile robot concurrently completes visualized map generation and path navigation even in an unknown environment. Autonomous visualization robot systems combine the Simultaneous Localization and Mapping (SLAM) and dynamic search techniques to self-drive to any desired target. The Hector SLAM is applied with only one LiDAR to continuously extract high-accuracy information from grid maps of neighboring environments. Due to the related robot radius, the grid maps are flexibly approximated by weighted scalar formulas. Then, the novel hybrid neighboring and global path planning is determined to achieve the appropriate position for fitting mobile robot navigation applications. In neighborhood search, the A* algorithm first explores the shortest path selection between robot and target with the perceptual information of the LiDAR. Global path selection with the dynamic window approach (DWA) is applied to improve the previous neighborhood search of the A* algorithm. The DWA accurately predicts all possible moving paths and chooses the best path planning. The mobile robot follows the shortest path and avoids obstacles to achieve the appropriate target. Based on repeated executions, the mobile robot explores its neighboring block and updates into global maps. The global path-planning scheme is restarted if the robot finds obstacles. This strategy allows robots to fit the appropriate maps, and to quickly react and effectively avoid the danger when they encounter some unexpected conditions. Several mobile robot navigation experiments illustrate that the autonomous path-planning and self-localization abilities can achieve the desired goals through the support of the flexible ROS platform. It is expedient to rebuild the visualized maps for the appropriate mobile robot applications even in unknown, unusual and complicated environments.
    關聯: Journal of Imaging Science and Technology 62(3), 030403(9 pages)
    DOI: 10.2352/J.ImagingSci.Technol.2018.62.3.030403
    显示于类别:[電機工程學系暨研究所] 期刊論文

    文件中的档案:

    档案 描述 大小格式浏览次数
    index.html0KbHTML49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