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    ASIA unversity > 資訊學院 > 資訊傳播學系 > 會議論文 >  Item 310904400/6900


    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/6900


    Title: An incremental-learning-by-navigation approach to vision-based autonomous land vehicle guidance in indoor environments using vertical line information and multi-weighted generalized Hough transform technique,
    Authors: G. Y. Chen;W. H. Tsai
    Contributors: Department of Information Communication
    Date: 1996-8
    Issue Date: 2009-12-23 19:35:05 (UTC+8)
    Publisher: Asia University
    Abstract: An incremental learning by navigation approach to vision based autonomous land vehicle (ALV) guidance in indoor environments is proposed. The approach consists of three stages: initial learning, navigation, and model updating. In the initial learning stage, the ALV is driven manually, and environment images and other status data are recorded automatically. Then, an offline procedure is performed to build an initial environment model. In the navigation stage, the ALV moves along the learned environment automatically, locates itself by model matching, and records necessary information for model updating. In the model updating stage, an offline procedure is performed to refine the learned model. A more precise model is obtained after each navigation-and-update iteration. Used environment features are vertical straight lines in camera views. A multiweighted generalized Hough transform is proposed for model matching. A real ALV was used as the testbed, and successful navigation experiments show the feasibility of the proposed approach
    Relation: Proceedings of 1996 Conference on Computer Vision, Graphics and Image Processing, Nantou, Taiwan, Republic of China,
    Appears in Collections:[資訊傳播學系] 會議論文

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