This book describes the latest research accomplishments, innovations, and visions in the field of robotics as presented at the 13th International Conference on Intelligent Autonomous Systems (IAS), held in Padua in July 2014, by leading researchers, engineers, and practitioners from across the world. The contents amply confirm that robots, machines, and systems are rapidly achieving intelligence and autonomy, mastering more and more capabilities such as mobility and manipulation, sensing and perception, reasoning, and decision making. A wide range of research results and applications are covered, and particular attention is paid to the emerging role of autonomous robots and intelligent systems in industrial production, which reflects their maturity and robustness. The contributions have been selected through a rigorous peer-review process and contain many exciting and visionary ideas that will further galvanize the research community, spurring novel research directions. The series of biennial IAS conferences commenced in 1986 and represents a premiere event in robotics.

A collection of papers dealing with complete systems of intelligent robots, focusing on autonomy. The contributions cover intelligent perception, intelligent planning and control, and integrated systems.

This work addresses the environmental recognition of autonomous off-road vehicles. Algorithms, like deep learning, offer impressive performance regarding the classification and segmentation of a scene. However, context changes, scene variabilities, or disturbances pose significant challenges to these approaches and cause perception failures. A challenge is achieving the universal applicability of perception algorithms. Usually, an algorithm fails in particular situations due to unconsidered circumstances in the design phase, and complexity prevents fully considering all details. Accordingly, this thesis aims to increase the perception’s robustness through context and data incorporation. Furthermore, it derives concepts for transferring methods to other robots and scenes. A hint that such a task is achievable provides human cognition, which is remarkably skillful and adjusts to arbitrary situations. Biologically motivated perception and cognitive research indicate how an achievable perception design might function, leading to guidelines for artificial perception conception. The paradigm of behavior-based systems suits these criteria due to modularity, reactivity, and robustness. It allows realizing robust and transferable perception and control systems. Consequently, the thesis proposes a novel and reconfigurable behavior-based top-down and bottom-up perception approach. Quality assessment for data filtering and deviation control is a central aspect, resulting in improved perception and data fusion results. Attentional processing allows for selecting data based on attractiveness, task, environmental context, and history. Further, context assessment of classification results enables reasoning according to the robot’s memories and knowledge. Validation uses five demonstrator vehicles operating in diverse environments and fulfilling distinct tasks. Here, a robust performance was achievable, and perception adjusted well to the tested scenes and hardware layouts.

This book presents the latest advances and research achievements in the fields of autonomous robots and intelligent systems, presented at the IAS-15 conference, held in Baden-Baden, Germany, in June 2018. It brings together contributions from researchers, engineers and practitioners from all over the world on the main trends of robotics: navigation, path planning, robot vision, human detection, and robot design – as well as a wide range of applications. This installment of the conference reflects the rise of machine learning and deep learning in the robotics field, as employed in a variety of applications and systems. All contributions were selected using a rigorous peer-review process to ensure their scientific quality. The series of biennial IAS conferences was started in 1986: since then, it has become an essential venue for the robotics community.

“IAS has been held every two years since 1986 providing venue for the latest accomplishments and innovations in advanced intelligent autonomous systems. New technologies and application domains continuously pose new challenges to be overcome in order to apply intelligent autonomous systems in a reliable and user-independent way in areas ranging from industrial applications to professional service and household domains. The present book contains the papers presented at the 17th International Conference on Intelligent Autonomous Systems (IAS-17), which was held from June 13–16, 2022, in Zagreb, Croatia. In our view, 62 papers, authored by 196 authors from 19 countries, are a testimony to the appeal of the conference considering travel restrictions imposed by the COVID-19 pandemic. Our special thanks go to the authors and the reviewers for their effort—the results of their joint work are visible in this book. We look forward to seeing you at IAS-18 in 2023 in Suwon, South Korea!”

The objective of this book is to provide the reader with a comprehensive coverage on the Robot Operating Systems (ROS) and latest related systems, which is currently considered as the main development framework for robotics applications. The book includes twenty-seven chapters organized into eight parts. Part 1 presents the basics and foundations of ROS. In Part 2, four chapters deal with navigation, motion and planning. Part 3 provides four examples of service and experimental robots. Part 4 deals with real-world deployment of applications. Part 5 presents signal-processing tools for perception and sensing. Part 6 provides software engineering methodologies to design complex software with ROS. Simulations frameworks are presented in Part 7. Finally, Part 8 presents advanced tools and frameworks for ROS including multi-master extension, network introspection, controllers and cognitive systems. This book will be a valuable companion for ROS users and developers to learn more ROS capabilities and features.

This book presents the results of the successful Sensors Special Issue on Intelligent Vehicles that received submissions between March 2019 and May 2020. The Guest Editors of this Special Issue are Dr. David Fernández-Llorca, Dr. Ignacio Parra-Alonso, Dr. Iván García-Daza and Dr. Noelia Parra-Alonso, all from the Computer Engineering Department at the University of Alcalá (Madrid, Spain). A total of 32 manuscripts were finally accepted between 2019 and 2020, presented by top researchers from all over the world. The reader will find a well-representative set of current research and developments related to sensors and sensing for intelligent vehicles. The topics of the published manuscripts can be grouped into seven main categories: (1) assistance systems and automatic vehicle operation, (2) vehicle positioning and localization, (3) fault diagnosis and fail-x systems, (4) perception and scene understanding, (5) smart regenerative braking systems for electric vehicles, (6) driver behavior modeling and (7) intelligent sensing. We, the Guest Editors, hope that the readers will find this book to contain interesting papers for their research, papers that they will enjoy reading as much as we have enjoyed organizing this Special Issue