A Framework for Robust and Incremental Self-Localization

Matjaž Jogan and Matej Artač and Danijel Skočaj and Aleš Leonardis (2003) A Framework for Robust and Incremental Self-Localization. [Dataset] (Unpublished)

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Abstract

In this contribution we present a framework for an embodied robotic system that is capable of appearance-based self-localization. Specifically, we concentrate on the issues of robustness, flexibility, and scalability of the system. The framework presented is based on a panoramic eigenspace model of the environment. Its main feature is that it allows for simultaneous localization and map building using an incremental learning algorithm. Further, both the learning and the training processes are designed in a way to achieve robustness and adaptability to changes in the environment.

Item Type:

Dataset

Keywords:

autonomous systems, robotics, self-localization, cognitive vision, eigenspace methods

Language of Content:

English

Related URLs:

URL	URL Type
http://www.cobiss.si/scripts/cobiss?command=search&base=50070&select=(id=3575380)	Alternative location

Link to COBISS:

http://www.cobiss.si/scripts/cobiss?command=search&base=50070&select=(ID=)

Institution:

University of Ljubljana

Department:

Faculty of Computer and Information Science

Divisions:

Faculty of Computer and Information Science > Computer Vision Laboratory

Item ID:

Date Deposited:

22 May 2003

Last Modified:

11 Dec 2013 10:02

URI:

http://eprints.fri.uni-lj.si/id/eprint/83

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