Multisensor Fusion and Integration in the Wake of Big Data, Deep Learning and Cyber Physical System

An Edition of the Selected Papers from the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2017)

  • Sukhan Lee
  • Hanseok Ko
  • Songhwai Oh
Conference proceedings MFI 2017

Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 501)

Table of contents

  1. Front Matter
    Pages i-viii
  2. Multi-sensor Fusion: Theory and Practice

    1. Front Matter
      Pages 1-3
    2. Florian Rosenthal, Benjamin Noack, Uwe D. Hanebeck
      Pages 22-38
    3. Justin D. Brody, Anna M. R. Dixon, Daniel Donavanik, Ryan M. Robinson, William D. Nothwang
      Pages 52-75
    4. Tran Tuan Nguyen, Jens Spehr, Jonas Sitzmann, Marcus Baum, Sebastian Zug, Rudolf Kruse
      Pages 98-118
    5. Achim Kuwertz, Dirk Mühlenberg, Jennifer Sander, Wilmuth Müller
      Pages 119-139
    6. Gaochao Feng, Deqiang Han, Yi Yang, Jiankun Ding
      Pages 140-152
  3. Multi-sensor Fusion Applications in Robotics

    1. Front Matter
      Pages 153-155
    2. Sangwook Park, Chul Jin Cho, Younglo Lee, Andrew Da Costa, SangHo Lee, Hanseok Ko
      Pages 157-167
    3. Daniel Bender, Wolfgang Koch, Daniel Cremers
      Pages 168-185
    4. Mårten Lager, Elin A. Topp, Jacek Malec
      Pages 186-209
    5. Mohammad Aldibaja, Noaki Suganuma, Keisuke Yoneda, Ryo Yanase, Akisue Kuramoto
      Pages 210-218
    6. Johannes Buyer, Martin Vollert, Mihai Kocsis, Nico Sußmann, Raoul Zöllner
      Pages 219-238
    7. Xiuyi Fan, Huiguo Zhang, Cyril Leung, Zhiqi Shen
      Pages 253-267
    8. Yanyan Bao, Fuchun Sun, Xinfeng Hua, Bin Wang, Jianqin Yin
      Pages 268-283
  4. Back Matter
    Pages 299-300

About these proceedings


This book includes selected papers from the 13th IEEE International Conference on Multisensor Integration and Fusion for Intelligent Systems (MFI 2017) held in Daegu, Korea, November 16–22, 2017. It covers various topics, including sensor/actuator networks, distributed and cloud architectures, bio-inspired systems and evolutionary approaches, methods of cognitive sensor fusion, Bayesian approaches, fuzzy systems and neural networks, biomedical applications, autonomous land, sea and air vehicles, localization, tracking, SLAM, 3D perception, manipulation with multifinger hands, robotics, micro/nano systems, information fusion and sensors, and multimodal integration in HCI and HRI. The book is intended for robotics scientists, data and information fusion scientists, researchers and professionals at universities, research institutes and laboratories.


Multisensor Fusion Integration Sensor/Actuator Networks Distributed Architectures Cloud Architectures Bio-inspired Systems Cognitive Sensor Fusion Bayesian Approaches Fuzzy Systems Autonomous Vehicles

Editors and affiliations

  • Sukhan Lee
    • 1
  • Hanseok Ko
    • 2
  • Songhwai Oh
    • 3
  1. 1.Intelligent Systems Research InstituteSungkyunkwan UniversitySuwonKorea (Republic of)
  2. 2.School of Electrical EngineeringKorea UniversitySeoulKorea (Republic of)
  3. 3.Department of Electrical and Computer EngineeringSeoul National UniversitySeoulKorea (Republic of)

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing AG, part of Springer Nature 2018
  • Publisher Name Springer, Cham
  • eBook Packages Engineering Engineering (R0)
  • Print ISBN 978-3-319-90508-2
  • Online ISBN 978-3-319-90509-9
  • Series Print ISSN 1876-1100
  • Series Online ISSN 1876-1119
  • Buy this book on publisher's site