Robust world-modelling and navigation in a real world

This article will discuss a qualitative, topological and robust world-modelling technique with special regard to navigation tasks for mobile robots operating in unknown environments. As a central aspect, the reliability regarding error-tolerance and stability will be emphasized. Benefits and problem...

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Published in:Neurocomputing (Amsterdam) 1996, Vol.13 (2), p.247-260
Main Author: Zimmer, Uwe R.
Format: Article
Language:English
Subjects:
Artificial neural networks
Mobile robots
Navigation
Self-organization
World-modelling
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description This article will discuss a qualitative, topological and robust world-modelling technique with special regard to navigation tasks for mobile robots operating in unknown environments. As a central aspect, the reliability regarding error-tolerance and stability will be emphasized. Benefits and problems involved in exploration as well as in navigation tasks are discussed. The proposed method demands very low constraints for the kind and quality of the employed sensors as well as for the kinematic precision of the utilized mobile platform. Hard real-time constraints can be handled due to the low computational complexity. The principal discussions are supported by real-world experiments with the mobile robot ‘ALICE’ 1 1 The project ALICE is supported by the EU-project DG XII, F-5 (Teleman). .
doi_str_mv 10.1016/0925-2312(95)00097-6
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source ScienceDirect Freedom Collection 2022-2024
subjects Artificial neural networks
Mobile robots
Navigation
Self-organization
World-modelling
title Robust world-modelling and navigation in a real world
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