Learning Dynamic Spatial Relations The Case of a Knowledge-based End
Andreas Bihlmaier describes a novel method to model dynamic spatial relations by machine learning techniques. The method is applied to the task of representing the tacit knowledge of a trained camera assistant in minimally-invasive surgery. The model is t
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Learning Dynamic Spatial Relations The Case of a Knowledge-based Endoscopic Camera Guidance Robot
Learning Dynamic Spatial Relations
Andreas Bihlmaier
Learning Dynamic Spatial Relations The Case of a Knowledge-based Endoscopic Camera Guidance Robot
Andreas Bihlmaier Karlsruhe, Germany PhD Thesis, Karlsruhe Institute of Technology (KIT), 2016
ISBN 978-3-658-14913-0 ISBN 978-3-658-14914-7 (eBook) DOI 10.1007/978-3-658-14914-7 Library of Congress Control Number: 2016946311 Springer Vieweg © Springer Fachmedien Wiesbaden 2016 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. 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 publisher, 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 publisher 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. Printed on acid-free paper This Springer Vieweg imprint is published by Springer Nature The registered company is Springer Fachmedien Wiesbaden GmbH
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Acknowledgement A number of people beyond the author of this PhD thesis have been essential to achieve the results presented here. My first “Thank You” is directed to Prof. Heinz W¨orn and Prof. Beat M¨ uller not only for their guidance and advice, but without them there would not even have been a research project to start my work on. In this context, I also want to acknowledge everyone involved in writing the Sonderforschungsbereich/Transregio 125 “Cognition-Guided Surgery”1 project proposal, in particular Oliver Weede, who set the goal within the project to research into autonomous endoscope guidance. Thanks to everybody involved into the SFB/Transregio 125 project. A special acknowledgement is mandatory for Hannes Kenngott, Martin Wagner and Patrick Mietkowski: Without your help nothing would have been possible. No interdisciplinary papers on surgical robotics would have been written; no prizes would have been won. The other important context was the Institute for Anthropomatics and Robotics – Intelligent Process Control and Robotics (IAR-IPR), which has a great culture of informal interactions, sincere criticism and mutual support, thanks to everybody there. Not least to the secretaries, without whom there would be no time left to do research.
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