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Road Terrain Classification Technology for Autonomous Vehicle / by Shifeng Wang.

By: Wang, Shifeng., autor
Contributor(s): SpringerLink (Online service)
Series: (Engineering (Springer-11647)); (Unmanned System Technologies, 2523-3734).Publisher: Singapore : Springer Singapore : Imprint: Springer, 2019Description: 1 recurso en línea (XVI, 97 páginas) : 43 ilustraciones, 32 ilustraciones a color.ISBN: 9789811361555.Subject: Vehículos de motor -- Control automáticoOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
Introduction -- Review of Related Work -- Acceleration Based Road Terrain Classification -- Image Based Road Terrain Classification -- LRF Based Road Terrain Classification -- Multiple-Sensor Based Road Terrain Classification -- Conclusion and Future Direction.
Abstract: This book provides cutting-edge insights into autonomous vehicles and road terrain classification, and introduces a more rational and practical method for identifying road terrain. It presents the MRF algorithm, which combines the various sensors' classification results to improve the forward LRF for predicting upcoming road terrain types. The comparison between the predicting LRF and its corresponding MRF show that the MRF multiple-sensor fusion method is extremely robust and effective in terms of classifying road terrain. The book also demonstrates numerous applications of road terrain classification for various environments and types of autonomous vehicle, and includes abundant illustrations and models to make the comparison tables and figures more accessible. .
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería TL152.8 2019 EB (Browse shelf(Opens below)) Acceso electrónico eBooks24062722
Total holds: 0

Introduction -- Review of Related Work -- Acceleration Based Road Terrain Classification -- Image Based Road Terrain Classification -- LRF Based Road Terrain Classification -- Multiple-Sensor Based Road Terrain Classification -- Conclusion and Future Direction.

This book provides cutting-edge insights into autonomous vehicles and road terrain classification, and introduces a more rational and practical method for identifying road terrain. It presents the MRF algorithm, which combines the various sensors' classification results to improve the forward LRF for predicting upcoming road terrain types. The comparison between the predicting LRF and its corresponding MRF show that the MRF multiple-sensor fusion method is extremely robust and effective in terms of classifying road terrain. The book also demonstrates numerous applications of road terrain classification for various environments and types of autonomous vehicle, and includes abundant illustrations and models to make the comparison tables and figures more accessible. .

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