English  |  正體中文  |  简体中文  |  Items with full text/Total items : 90429/105609 (86%)
Visitors : 10382542      Online Users : 648
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    ASIA unversity > 資訊學院 > 資訊傳播學系 > 會議論文 >  Item 310904400/6923

    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/6923

    Title: Vision-based obstacle detection and avoidance for autonomous land vehicle navigation in outdoor roads
    Authors: K. H. Chen;W. H. Tsai
    Contributors: Department of Information Communication
    Date: 1999-8
    Issue Date: 2009-12-23 19:35:15 (UTC+8)
    Publisher: Asia University
    Abstract: An effective approach to obstacle detection and avoidance for autonomous land vehicle (ALV) navigation in outdoor road environments using computer vision and image sequence techniques is proposed. To judge whether an object newly appearing in the image of the current cycle taken by the ALV is an obstacle, the object shape boundary is first extracted from the image. After the translation from the ALV location in the current cycle to that in the next cycle is estimated, the position of the object shape in the image of the next cycle is predicted, using coordinate transformation techniques based on the assumption that the height of the object is zero. The predicted object shape is then matched with the extracted shape of the object in the image of the next cycle to decide whether the object is an obstacle. We use a reasonable distance measure to compute the correlation measure between two shapes for shape matching. Finally, a safe navigation point is determined, and a turn angle is computed to guide the ALV toward the navigation point for obstacle avoidance. Successful navigation tests show that the proposed approach is effective for obstacle detection and avoidance in outdoor road environments.
    Relation: Proceedings of 1999 Conference on Computer Vision, Graphics and Image Processing, Taipei, Taiwan, Republic of China
    Appears in Collections:[資訊傳播學系] 會議論文

    Files in This Item:

    File Description SizeFormat

    All items in ASIAIR are protected by copyright, with all rights reserved.

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback