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Approaches to Probabilistic Model Learning for Mobile Manipulati...
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Approaches to Probabilistic Model Learning for Mobile Manipulation Robots,本书是概率模型应用于机器人方面不可多得的资料,作者Jürgen Sturm ,Springer-Verlag Berlin Heidelberg (2013)
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Approaches to Probabilistic
Model Learning for Mobile
Manipulation Robots
123
springer tracts in advanced robotics 89
star
Jürgen Sturm
Springer Tracts in Advanced Robotics 89
Editors
Prof. Bruno Siciliano
Dipartimento di Ingegneria Elettrica
e Tecnologie dell’Informazione
Università degli Studi di Napoli
Federico II
Via Claudio 21, 80125 Napoli
Italy
E-mail: siciliano@unina.it
Prof. Oussama Khatib
Artificial Intelligence Laboratory
Department of Computer Science
Stanford University
Stanford, CA 94305-9010
USA
E-mail: khatib@cs.stanford.edu
For further volumes:
http://www.springer.com/series/5208
Editorial Advisory Board
Oliver Brock, TU Berlin, Germany
Herman Bruyninckx, KU Leuven, Belgium
Raja Chatila, ISIR - UPMC & CNRS, France
Henrik Christensen, Georgia Tech, USA
Peter Corke, Queensland Univ. Technology, Australia
Paolo Dario, Scuola S. Anna Pisa, Italy
Rüdiger Dillmann, Univ. Karlsruhe, Germany
Ken Goldberg, UC Berkeley, USA
John Hollerbach, Univ. Utah, USA
Makoto Kaneko, Osaka Univ., Japan
Lydia Kavraki, Rice Univ., USA
Vijay Kumar, Univ. Pennsylvania, USA
Sukhan Lee, Sungkyunkwan Univ., Korea
Frank Park, Seoul National Univ., Korea
Tim Salcudean, Univ. British Columbia, Canada
Roland Siegwart, ETH Zurich, Switzerland
Gaurav Sukhatme, Univ. Southern California, USA
Sebastian Thrun, Stanford Univ., USA
Yangsheng Xu, Chinese Univ. Hong Kong, PRC
Shin’ichi Yuta, Tsukuba Univ., Japan
STAR (Springer Tracts in Advanced Robotics) has been promoted un-
der the auspices of EURON (European Robotics Research Network)
ROBOTICS
Research
Network
European
EURON
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Jürgen Sturm
Approaches to Probabilistic
Model Learning for Mobile
Manipulation Robots
ABC
Dr. Jürgen Sturm
Technische Universität München
Institute of Computer Science
Computer Vision Group
Boltzmannstraße 3
85748 Garching
Germany
ISSN 1610-7438 ISSN 1610-742X (electronic)
ISBN 978-3-642-37159-2 ISBN 978-3-642-37160-8 (eBook)
DOI 10.1007/978-3-642-37160-8
Springer Heidelberg New York Dordrecht London
Library of Congress Control Number: 2013936730
c
Springer-Verlag Berlin Heidelberg 2013
This work is subject to copyright. All rights are reserved by the Publisher, 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. Exempted from this legal reservation are brief excerpts in connection
with reviews or scholarly analysis or material supplied specifically for the purpose of being entered
and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of
this publication or parts thereof is permitted only under the provisions of the Copyright Law of the
Publisher’s location, in its current version, and permission for use must always be obtained from Springer.
Permissions for use may be obtained through RightsLink at the Copyright Clearance Center. Violations
are liable to prosecution under the respective Copyright Law.
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.
While the advice and information in this book are believed to be true and accurate at the date of pub-
lication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any
errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect
to the material contained herein.
Printed on acid-free paper
Springer is part of Springer Science+Business Media (www.springer.com)
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