Springer Tracts in Advanced Robotics

Random Finite Sets for Robot Mapping & SLAM

New Concepts in Autonomous Robotic Map Representations

Authors: Mullane, J.S., Vo, B.-N., Adams, M.D., Vo, B.-T.

  • First book on the use of random finite sets (RFS) and finite set statistics (FISST) in robotics
  • Focuses on a critical area of autonomous robotic research - the representation of the environment and its uncertainty
  • Written by leading experts in the field
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About this book

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.

Table of contents (7 chapters)

  • Introduction

    Mullane, John (et al.)

    Pages 1-8

  • Why Random Finite Sets?

    Mullane, John (et al.)

    Pages 11-25

  • Estimation with Random Finite Sets

    Mullane, John (et al.)

    Pages 27-42

  • An RFS Theoretic for Bayesian Feature-Based Robotic Mapping

    Mullane, John (et al.)

    Pages 45-76

  • An RFS ‘Brute Force’ Formulation for Bayesian SLAM

    Mullane, John (et al.)

    Pages 79-96

Buy this book

eBook $109.00
price for USA (gross)
  • ISBN 978-3-642-21390-8
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $149.99
price for USA
  • ISBN 978-3-642-21389-2
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $129.99
price for USA
  • ISBN 978-3-642-26831-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Rent the eBook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
  • can be used across all devices
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Bibliographic Information

Bibliographic Information
Book Title
Random Finite Sets for Robot Mapping & SLAM
Book Subtitle
New Concepts in Autonomous Robotic Map Representations
Authors
Series Title
Springer Tracts in Advanced Robotics
Series Volume
72
Copyright
2011
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer Berlin Heidelberg
eBook ISBN
978-3-642-21390-8
DOI
10.1007/978-3-642-21390-8
Hardcover ISBN
978-3-642-21389-2
Softcover ISBN
978-3-642-26831-1
Series ISSN
1610-7438
Edition Number
1
Number of Pages
XXIV, 148
Topics