Road Terrain Classification Technology for Autonomous Vehicle
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’ classif
- PDF / 4,292,854 Bytes
- 107 Pages / 453.544 x 683.151 pts Page_size
- 38 Downloads / 235 Views
Shifeng Wang
Road Terrain Classification Technology for Autonomous Vehicle
Unmanned System Technologies
Springer’s Unmanned Systems Technologies (UST) book series publishes the latest developments in unmanned vehicles and platforms in a timely manner, with the highest of quality, and written and edited by leaders in the field. The aim is to provide an effective platform to global researchers in the field to exchange their research findings and ideas. The series covers all the main branches of unmanned systems and technologies, both theoretical and applied, including but not limited to: • Unmanned aerial vehicles, unmanned ground vehicles and unmanned ships, and all unmanned systems related research in: • Robotics Design • Artificial Intelligence • Guidance, Navigation and Control • Signal Processing • Circuit and Systems • Mechatronics • Big Data • Intelligent Computing and Communication • Advanced Materials and Engineering The publication types of the series are monographs, professional books, graduate textbooks, and edited volumes.
More information about this series at http://www.springer.com/series/15608
Shifeng Wang
Road Terrain Classification Technology for Autonomous Vehicle
123
Shifeng Wang School of Optoelectronic Engineering Changchun University of Science and Technology Changchun, China
ISSN 2523-3734 ISSN 2523-3742 (electronic) Unmanned System Technologies ISBN 978-981-13-6154-8 ISBN 978-981-13-6155-5 (eBook) https://doi.org/10.1007/978-981-13-6155-5 Jointly published with China Machine Press, Beijing, China The print edition is not for sale in China Mainland. Customers from China Mainland please order the print book from: China Machine Press. Library of Congress Control Number: 2019932623 © China Machine Press, Beijing and Springer Nature Singapore Pte Ltd. 2019 This work is subject to copyright. All rights are reserved by the Publishers, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publishers, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publishers nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publishers remain neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is publis
Data Loading...
