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Mobile robot localization using an omnidirectional camera

Iztok Oder (2014) Mobile robot localization using an omnidirectional camera. EngD thesis.

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    In future, robots will largely replace human labour. They will have to be as autonomous as possible. This includes the ability to self-navigate through space. A successful navigation requires the knowledge of one's location in space. Many methods that deal with the problem of self-localization exist. Usually these methods use data acquired with a depth sensor. In this thesis we explore the possibilities of self-localization using only panoramic images obtained with omnidirectional camera. Localization is performed using statistical methods PCA, KPCA, CCA and KCCA. These methods produce a low-dimensional subspace from high-dimensional input images. These images are than projected onto the subspace, which gives us an alternative representation of the environment that can be used for predicting the locations of test images. All methods are implemented for use with mobile robot ATRV mini. The accuracy of self-localization is evaluated and few suggestions for the improvement are proposed.

    Item Type: Thesis (EngD thesis)
    Keywords: self-localization, panoramic images, PCA, KPCA, CCA, KCCA, robot, robot operating system, omnidirectional camera
    Number of Pages: 75
    Language of Content: Slovenian
    Mentor / Comentors:
    Name and SurnameIDFunction
    doc. dr. Danijel Skočaj296Mentor
    Link to COBISS: http://www.cobiss.si/scripts/cobiss?command=search&base=51012&select=(ID=1536094147 )
    Institution: University of Ljubljana
    Department: Faculty of Computer and Information Science
    Item ID: 2703
    Date Deposited: 16 Sep 2014 16:33
    Last Modified: 04 Dec 2014 13:19
    URI: http://eprints.fri.uni-lj.si/id/eprint/2703

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