Affecta-Context: The Context-Guided Behavior Adaptation Framework -- LTS-NET: End-To-End Unsupervised Learning of Long-Term 3D Stable Objects -- EA-Repose: Efficient and Accurate Feature-Metric-Based 6D Object Pose Refinement Via Deep Reinforcement Learning -- Chop-SAT: A New Method for Knowledge-Based Agent Decision Making -- Performance Comparison of SAC Methods for Radar Dynamic Object Classification -- Sim2Real When Data Is Scarce: Image Transformation for Industrial Applications -- Give Pedestrian More Choice: Socially Aware Navigation Using Reinforcement Learning with Human Action Entropy Maximization -- Data Aggregation (DAgger) Algorithm Using Adversarial Agent Policy for Dynamic Situations -- Target Acquisition by Reinforcement Learning-Based Bin Tilting with a Robotic Arm.

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 heartfelt thanks to all the authors and editors who contributed to this edition.