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Gabor-gist Visual Homing

  • Author / Creator
    Mills, Michael J
  • Many robotic systems are required to navigate or home to learned location using minimal resources. Autonomous robots are generally limited in computation and storage resources, imposing significant challenges on algorithm design. Particularly when only visual data is used, these algorithms need to be robust and efficient. In addition, independence from a scene model is preferred. Extraction of models and calibration procedures are time consuming and sensitive to changes in the environ- ment. Visual homing without a geometric model is studied in mapless or qualitative visual homing. In this thesis, we adopt a framework based on View-Sequenced Route Representation (VSRR) and contribute in two areas: Compact representa- tion of the path and visual homing along a desired route using the representation, and secondly develop an algorithm which localizes the robot using a novel concept we call eigensegments. The effectiveness of the system is demonstrated with both indoor and outdoor environments.

  • Subjects / Keywords
  • Graduation date
    2013-11
  • Type of Item
    Thesis
  • Degree
    Master of Science
  • DOI
    https://doi.org/10.7939/R33X83T9G
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Master's
  • Department
    • Department of Computing Science
  • Supervisor / co-supervisor and their department(s)
    • Zhang, Hong (Computing Science)
  • Examining committee members and their departments
    • Zhang, Hong (Computing Science)
    • Ray, Nilanjan (Computing Science)
    • Jagersand, Martin (Computing Science)