Random Finite Sets for Robot Mapping and SLAM: New Concepts in Autonomous Robotic Map Representations
By Mullane, John St.; Vo, Ba-Ngu; Adams, Martin D.; Vo, Ba-Tuong; Mullane, John St.; Vo, Ba-Ngu; Adams, Martin D.; Vo, Ba-Tuong
Language: English
Published by Springer, Berlin, 2011
Series: Book 71 of 153 - Springer Tracts in Advanced Robotics
- Hardcover
- New
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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172 pages. 9.00x6.25x0.75 inches. In Stock.
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- Title
- Random Finite Sets for Robot Mapping and SLAM: New Concepts in Autonomous Robotic Map Representations
- Author
- By Mullane, John St.; Vo, Ba-Ngu; Adams, Martin D.; Vo, Ba-Tuong; Mullane, John St.; Vo, Ba-Ngu; Adams, Martin D.; Vo, Ba-Tuong
- Publisher
- Springer, Berlin
- Publication year
- 2011
- Condition
- Brand New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3642213898
- ISBN 13
- 9783642213892
- Item weight
- 0.39 kilograms
- Series
- Book 71 of 153: Springer Tracts in Advanced Robotics
"Synopsis" may belong to another edition of this title.
From the Back Cover
Simultaneous Localisation and Map (SLAM) building algorithms, which rely on random vectors to represent sensor measurements and feature maps are known to be extremely fragile in the presence of feature detection and data association uncertainty. Therefore new concepts for autonomous map representations are given in this book, based on random finite sets (RFSs). It will be shown that the RFS representation eliminates the necessity of fragile data association and map management routines. It fundamentally differs from vector based approaches since it estimates not only the spatial states of features but also the number of map features which have passed through the field(s) of view of a robot's sensor(s), an attribute which is necessary for SLAM.
The book also demonstrates that in SLAM, a valid measure of map estimation error is critical. It will be shown that under an RFS-SLAM representation, a consistent metric, which gauges both feature number as well as spatial errors, can be defined.
The concepts of RFS map representations are accompanied with autonomous SLAM experiments in urban and marine environments. Comparisons of RFS-SLAM with state of the art vector based methods are given, along with pseudo-code implementations of all the RFS techniques presented.
John Mullane received the B.E.E. degree from University College Cork, Ireland, and Ph.D degree from Nanyang Technological University (NTU), Singapore.
Ba-Ngu Vo is Winthrop Professor and Chair of Signal Processing, University of Western Australia (UWA). He received joint Bachelor degrees (Science and Elec. Eng.), UWA, and Ph.D., Curtin University.
Martin Adams is Professor in autonomous robotics research, University of Chile. He holds bachelors, masters and doctoral degrees from Oxford University.
Ba-Tuong Vo is Assistant Professor, UWA. He received his B.Sc, B.E and Ph.D. degrees from UWA.
"About the title" may belong to another edition of this title.
Revaluation Books
Exeter, United Kingdom
AbeBooks seller since January 6, 2003
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