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Building Maps Based on a Learned Classification of Ultrasonic Range Data

Kurz, Andreas (2023)
Building Maps Based on a Learned Classification of Ultrasonic Range Data.
In: IFAC Proceedings Volumes, 1993, 26 (1)
doi: 10.26083/tuprints-00023360
Article, Secondary publication, Publisher's Version

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Item Type: Article
Type of entry: Secondary publication
Title: Building Maps Based on a Learned Classification of Ultrasonic Range Data
Language: English
Date: 2023
Place of Publication: Darmstadt
Year of primary publication: 1993
Publisher: IFAC - International Federation of Automatic Control
Journal or Publication Title: IFAC Proceedings Volumes
Volume of the journal: 26
Issue Number: 1
Series Volume: 26
DOI: 10.26083/tuprints-00023360
Corresponding Links:
Origin: Secondary publication service
Abstract:

This paper introduces an approach for learning environmental maps based on ultrasonic range data. A neural network concept (self-organizing feature map) is used to learn a classification of the range data which makes it possible to discern situations. As a consequence the free-apace is partitioned into situation areas which are defined as regions wherein a specific situation can be recognized. Using dead-reckoning such situation areas can be attached to graph nodes generating a map of the free-space in the form of a graph representation. In this context it is discussed how the dead-reckoning drift can be compensated.
Uncontrolled Keywords: Classification, data reduction, learning systems, navigation, neural nets, pattern recognition, ultrasonic transducers, vehicles
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-233605
Additional Information:

Zugl. Konferenzveröffentlichung: 1st IFAC International Workshop on Intelligent Autonomous Vehicles (IAV-93), 18.-21.04.1993, Southampton, England
Classification DDC: 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering
Divisions: 18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik > Control Methods and Intelligent Systems
Date Deposited: 10 Mar 2023 10:17
Last Modified: 10 Aug 2023 08:36
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/23360
PPN: 508131189
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