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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 5/2009

01.06.2009 | ISNN 2008

Self-localization and obstacle avoidance for a mobile robot

verfasst von: Hongbo Wang, Ke Yu, Bingyi Mao

Erschienen in: Neural Computing and Applications | Ausgabe 5/2009

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Abstract

This article presents a fast self-localization method based on ZigBee wireless sensor network and laser sensor, an obstacle avoidance algorithm based on ultrasonic sensors for a mobile robot. The positioning system and positioning theory of ZigBee which can obtain a rough global localization of the mobile robot are introduced. To realize accurate local positioning, a laser sensor is used to extract the features from environment, then the environmental features and global reference map can be matched. From the matched environmental features, the position and orientation of the mobile robot can be obtained. To enable the mobile robot to avoid obstacle in real-time, a heuristic fuzzy neural network is developed by using heuristic fuzzy rules and the Kohonen clustering network. The experiment results show the effectiveness of the proposed method.
Vorheriger Artikel Sequential modeling of a low noise amplifier with neural networks and active learning
Nächster Artikel A motion location based video watermarking scheme using ICA to extract dynamic frames

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Metadaten
Titel
Self-localization and obstacle avoidance for a mobile robot
verfasst von
Hongbo Wang
Ke Yu
Bingyi Mao
Publikationsdatum
01.06.2009
Verlag
Springer-Verlag
Erschienen in
Neural Computing and Applications / Ausgabe 5/2009
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-009-0247-1

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