Guiding a mobile robot with cellular neural networks

Xavier Vilasís-Cardona, Sonia Luengo, Jordi Solsona, Alessandro Maraschini, Giada Apicella, Marco Balsi

Producción científica: Artículo en revista indizadaArtículorevisión exhaustiva

15 Citas (Scopus)

Resumen

We show how cellular neural networks (CNNs) are capable of providing the necessary signal processing needed for visual navigation of an autonomous mobile robot. In this way, even complex feature detection and object recognition can be obtained in real time by analogue hardware, making fully autonomous real-time operation feasible. An autonomous robot was first simulated and then implemented by simulating the CNN with a DSP. The robot is capable of navigating in a maze following lines painted on the floor. Images are processed entirely by a CNN-based algorithm, and navigation is controlled by a fuzzy-rule-based algorithm.

Idioma originalInglés
Páginas (desde-hasta)611-624
Número de páginas14
PublicaciónInternational Journal of Circuit Theory and Applications
Volumen30
N.º6
DOI
EstadoPublicada - nov 2002

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