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Utilization of Convolution Neural Network Based Road Detection in Mobile Robot Localization
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SYSNO ASEP 0508666 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Utilization of Convolution Neural Network Based Road Detection in Mobile Robot Localization Author(s) Krejsa, Jiří (UT-L) RID, ORCID
Věchet, Stanislav (UT-L) RID, ORCIDNumber of authors 2 Source Title Engineering mechanics 2019. Book of full texts. - Prague : Institute of Thermomechanics of the Czech Academy of Sciences, 2019 / Zolotarev I. ; Radolf V. - ISSN 1805-8248 - ISBN 978-80-87012-71-0 Pages s. 203-206 Number of pages 4 s. Publication form Print - P Action Engineering mechanics 2019 /25./ Event date 13.05.2019 - 16.05.2019 VEvent location Svratka Country CZ - Czech Republic Event type EUR Language eng - English Country CZ - Czech Republic Keywords convolution neural network ; localization ; road detection Subject RIV JB - Sensors, Measurment, Regulation OECD category Robotics and automatic control Institutional support UT-L - RVO:61388998 Annotation Mobile robot on-road navigation requires fusion of both global and local sensory information with an emphasis on the road detection processing. The paper deals with the road detection based on convolution neural networks (CNN) using commonly available tools such as TensorFlow and Keras. The road is defined by its linear boundaries. Network output is formed by the road definition together with classification parameters and serves as a local sensor in Kalman filter based localization. CNN based road detection is currently capable to successfully detect about 90% of images. Workplace Institute of Thermomechanics Contact Marie Kajprová, kajprova@it.cas.cz, Tel.: 266 053 154 ; Jana Lahovská, jaja@it.cas.cz, Tel.: 266 053 823 Year of Publishing 2020
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