Lakehead University Library Logo
    • Login
    View Item 
    •   Knowledge Commons
    • Electronic Theses and Dissertations
    • Retrospective theses
    • View Item
    •   Knowledge Commons
    • Electronic Theses and Dissertations
    • Retrospective theses
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.
    quick search

    Browse

    All of Knowledge CommonsCommunities & CollectionsBy Issue DateAuthorTitleSubjectDisciplineAdvisorCommittee MemberThis CollectionBy Issue DateAuthorTitleSubjectDisciplineAdvisorCommittee Member

    My Account

    Login

    Statistics

    View Usage Statistics

    Vision-based trajectory tracking algorithm with obstacle avoidance for a wheeled mobile robot

    Thumbnail

    View/Open

    YangX2005m-1b.pdf (2.386Mb)

    Date

    2005

    Author

    Yang, Xiusong

    Degree

    Master of Science

    Discipline

    Engineering : Control

    Subject

    Robot vision
    Mobile robots (Automatic control)

    Metadata

    Show full item record

    Abstract

    Wheeled mobile robots are becoming increasingly important in industry as means of transportation, inspection, and operation because of their efficiency and flexibility. The design of efficient algorithms for autonomous or quasi-autonomous mobile robots navigation in dynamic environments is a challenging problem that has been the focus of many researchers dining the past few decades. Computer vision, maybe, is not the most successful sensing modality used in mobile robotics until now (sonar and infra-red sensors for example being preferred), but it is the sensor which is able to give the information ’’what” and ’’where” most completely for the objects a robot is likely to encounter. In this thesis, we deal with using vision system to navigate the mobile robot to track a reference trajectory and using a sensor-based obstacle avoidance method to pass by the objects located on the trajectory. A tracking control algorithm is also described in this thesis. Finally, The experimental results are presented to verify the tracking and control algorithms.

    URI

    http://knowledgecommons.lakeheadu.ca/handle/2453/2802

    Collections

    • Retrospective theses

    Lakehead University Library
    Contact Us | Send Feedback

     


    Lakehead University Library
    Contact Us | Send Feedback