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Intelligent Autonomous Systems 18

Volume 2 Proceedings of the 18th International Conference IAS18-2023

  • Conference proceedings
  • © 2024

Overview

Editors:
  1. Soon-Geul Lee

    1. Department of Mechanical Engineering, Kyung Hee University, Yongin-si, Korea (Republic of)

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  2. Jinung An

    1. Department of Interdisciplinary Engineering, Daegu Gyeongbuk Institute of Science and DGIST R4-708, Daegu, Korea (Republic of)

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  3. Nak Young Chong

    1. School of Information Science, Japan Advanced Institute of Science and And Technology JAIST, Ishikawa, Japan

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  4. Marcus Strand

    1. DHBW Karlsruhe, Cooperative State University Baden-Wuerttemberg Karlsruhe, Karlsruhe, Germany

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  5. Joo H. Kim

    1. Department of Mechanical and Aerospace Engineering, New York University, New York, USA

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  • Presents the latest research and innovations in intelligent autonomous systems
  • Addresses the emerging role of autonomous robots in industrial production
  • Offers a rich source of ideas for new research directions

Part of the book series: Lecture Notes in Networks and Systems (LNNS, volume 794)

Included in the following conference series:

Conference proceedings info: IAS 2023.

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Table of contents (39 papers)

  1. Front Matter

    Pages i-xiv
    Download chapter PDF

  2. Data Fusion and Machine Learning for Intelligent Robots

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Affecta-Context: The Context-Guided Behavior Adaptation Framework

      • Morten Roed Frederiksen, Kasper Støy
      Pages 3-15

    3. LTS-NET: End-to-End Unsupervised Learning of Long-Term 3D Stable Objects

      • Ibrahim Hroob, Sergi Molina, Riccardo Polvara, Grzegorz Cielniak, Marc Hanheide
      Pages 17-29

    4. EA-Repose: Efficient and Accurate Feature-Metric-Based 6D Object Pose Refinement via Deep Reinforcement Learning

      • Peiyuan Ni, Zhiyang Liu, Haozhe Wang, Lei Zhou, Marcelo H. Ang Jr.
      Pages 31-44

    5. Chop-SAT: A New Method for Knowledge-Based Agent Decision Making

      • Thomas C. Henderson, Amelia Lessen, Ishaan Rajan, Tessa Nishida, Kutay Eken
      Pages 45-54

    6. Performance Comparison of SAC Methods for Radar Dynamic Object Classification

      • Yeong Sang Park, Dooseop Choi, Kyoung-Wook Min
      Pages 55-64

    7. Sim2Real When Data Is Scarce: Image Transformation for Industrial Applications

      • Moritz Weisenböhler, Philipp Augenstein, Björn Hein, Christian Wurll, Kai Furmans
      Pages 65-76

    8. Give Pedestrian More Choice: Socially Aware Navigation Using Reinforcement Learning with Human Action Entropy Maximization

      • Jiaxu Wu, Hajime Asama, Qi An, Atsushi Yamashita
      Pages 77-90

    9. Data Aggregation (DAgger) Algorithm Using Adversarial Agent Policy for Dynamic Situations

      • Joonwoo Ahn, Seho Shin, Jahoo Koo, Minsoo Kim, Jaeheung Park
      Pages 91-104

    10. Target Acquisition by Reinforcement Learning-Based Bin Tilting with a Robotic Arm

      • Qiuyang Li, Ziyan Gao, Armagan Elibol, Nak Young Chong
      Pages 105-115

    11. Automatic Corona Discharge Detection for Cable Safety Inspection

      • Jemo Maeng, Yunjae Heo, Kyoobin Lee
      Pages 117-126

    12. HoLLiE C—A Multifunctional Bimanual Mobile Robot Supporting Versatile Care Applications

      • Lea Steffen, Martin Schulze, Christian Eichmann, Robin Koch, Andreas Hermann, Rosa Frietsch Mussulin et al.
      Pages 127-140

    13. Accelerated Video Annotation Driven by Deep Detector and Tracker

      • Eric Price, Aamir Ahmad
      Pages 141-153

    14. VGG-16 Neural Network-Based Visual Artificial Potential Field for Autonomous Navigation of Ground Robots

      • Antonio Galiza Cerdeira Gonzalez, Gentiane Venture, Ikuo Mizuuchi
      Pages 155-168

    15. Approaches of Safe and Efficient 3D UAM Traffic Management Using VR, AR, and MR with AI; HCI Requirements for Digital Twin Application

      • Chang-Geun Oh, Mikyoung Lee
      Pages 169-177

    16. Determining Grasp Positions with 4-Finger Gripper Manipulator Using Reinforcement Learning

      • Myunghyun Kim, Sumin Kang, Sungwoo Yang, Jargalbaatar Yura, Donghan Kim
      Pages 179-186

    17. Learning Mechanical Impulse Response for Understanding Surface Characteristics

      • Joohyun Lee, Semin Ryu, Seung-Chan Kim
      Pages 187-189

    18. Development of Autonomous Driving for Passenger Boarding Bridge (PBB) Through Aircraft Door Detection Based on YOLO Object Detection Algorithm

      • Ihnsik Weon, Beomchan Park, Hyeon-Joong Kim, Jong-Hyuk Park
      Pages 191-198

    19. Human Detection in Thermal Images Using Transfer Learning

      • Jeon-Seong Kang, Beom-joon Park, Hyun-Joon Chung
      Pages 199-205
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Other volumes

  1. Intelligent Autonomous Systems 18

  2. Intelligent Autonomous Systems 18

Keywords

About this book

Intelligent autonomous systems are increasingly being applied in various fields, ranging from industrial applications to professional services and household domains. These advancements in technology and application domains have brought forth the need for continuous research and development to address new challenges in deploying intelligent autonomous systems in a reliable and user-independent manner

   This book is a compilation that aims to serve researchers and practitioners in related fields by providing a timely dissemination of recent progress in the areas of autonomous mobility and robotics. The contents of this book are based on a collection of papers presented at the 18th International Conference on Intelligent Autonomous Systems (IAS18 2023), held at the Suwon Convention Center in Suwon, Korea. The conference took place fully in person from July 4 to 7, 2023, with the theme “Impact and Effect of AI on Intelligent Autonomous Systems.” It encompassed discussions on theories, applications, and creative innovations in intelligent autonomous systems, covering topics such as autonomous vehicles, intelligent agents, smart sensors and actuators, smart haptics, human–machine interaction, digital twin, digital health, and metaverse, VR, AR, or MR. For ease of reading, the 91 papers have been grouped into five chapters: Chapter 1: Intelligent Autonomous Vehicles; Chapter 2: Autonomous Robots; Chapter 3: Intelligent Perception and Sensors; Chapter 4: Data Fusion and Machine Learning for Intelligent Robots; and Chapter 5: Applied Autonomous Systems.

   The articles included in this book underwent a rigorous peer-review process and were presented at the IAS18-2023 conference.  For researchers working in the field of intelligent autonomous systems technology, we believe this book provides valuable insights into recent advances in autonomous technologies and applications, thereby enriching their studies. We extend our heartfeltthanks to all the authors and editors who contributed to this edition.


Editors and Affiliations

  • Department of Mechanical Engineering, Kyung Hee University, Yongin-si, Korea (Republic of)

    Soon-Geul Lee

  • Department of Interdisciplinary Engineering, Daegu Gyeongbuk Institute of Science and DGIST R4-708, Daegu, Korea (Republic of)

    Jinung An

  • School of Information Science, Japan Advanced Institute of Science and And Technology JAIST, Ishikawa, Japan

    Nak Young Chong

  • DHBW Karlsruhe, Cooperative State University Baden-Wuerttemberg Karlsruhe, Karlsruhe, Germany

    Marcus Strand

  • Department of Mechanical and Aerospace Engineering, New York University, New York, USA

    Joo H. Kim

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