Visual place recognition for persistent robot navigation in changing environments

Lowry, Stephanie Margaret (2014) Visual place recognition for persistent robot navigation in changing environments. PhD thesis, Queensland University of Technology.

Abstract

This thesis demonstrates that robots can learn about how the world changes, and can use this information to recognise where they are, even when the appearance of the environment has changed a great deal. The ability to localise in highly dynamic environments using vision only is a key tool for achieving long-term, autonomous navigation in unstructured outdoor environments. The proposed learning algorithms are designed to be unsupervised, and can be generated by the robot online in response to its observations of the world, without requiring information from a human operator or other external source.

Impact and interest:

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Full-text downloads:

87 since deposited on 28 Jan 2015
46 in the past twelve months

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ID Code: 79404
Item Type: QUT Thesis (PhD)
Supervisor: Milford, Michael & Wyeth, Gordon
Keywords: Appearance-based localisation, Persistent robot navigation, Visual place recognition, Localisation, Long-term autonomy
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Institution: Queensland University of Technology
Deposited On: 28 Jan 2015 01:54
Last Modified: 08 Sep 2015 06:47

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