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.
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.
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|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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