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Author:Swords, David
Title:Artificial neural network approach to mobile robot localization
Publication type:Master's thesis
Publication year:2012
Pages:xi + 99 + liitt. (+6)      Language:   eng
Department/School:Automaatio- ja systeemitekniikan laitos
Main subject:Automaatiotekniikka   (AS-84)
Supervisor:Halme, Aarne ; Gustafsson, Thomas
Instructor:Taipalus, Tapio
OEVS:
Electronic archive copy is available via Aalto Thesis Database.
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Location:P1 Ark Aalto  7454   | Archive
Keywords:artificial neural network
mobile robot localization
path-finding
Abstract (eng): In the robotics community, localization is considered a solved problem; however, the topic is still open to investigation.
Mobile robot localization has been focused on developing low-cost approaches and there has been great success using probabilistic methods.
Parallel to this, and to a much lesser extent, artificial neural networks (ANNs) have been applied to the problem area with varying success.

A system is proposed in this thesis where the typical probabilistic approach is replaced with one based purely on ANNs.
This type of localization attempts to harness the simplicity, scalability and adaptability that ANNs are known for.
The ANN approach allows for the encapsulation of a number of steps and elements well known in a probabilistic approach, resulting in the elimination of an internal explicit map, providing pose estimate on network output and network update at runtime.

First, a coordinate-based approach to localization is explored: 1D and 2D trained maps with pose estimates.
Second, the coordinate-based approach is eliminated in an effort to replicate a more biologically inspired localization.
Finally, a path-finding algorithm applying the new localization approach is presented.
ED:2012-11-30
INSSI record number: 45651
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