This 'Open Access' SpringerBrief provides foundational knowledge for designing autonomous, asynchronous systems and explains aspects of users relevant to designing for these systems, introduces principles for user-centered design, and prepares readers for more advanced and specific readings. It provides context and the implications for design choices made during the design and development of the complex systems that are part of operation centers. As such, each chapter includes principles to summarize the design implication that engineers can use to inform their own design of interfaces for operation centers and similar systems. It includes example materials for the design of a fictitious system, which are referenced in the book and can be duplicated and extended for real systems. The design materials include a system overview, the system architecture, an example scenario, a stakeholder analysis, a task analysis, a description of the system and interface technology, and contextualized design guidelines. The guidelines can be specified because the user, the task, and the technology are well specified as an example. Building Better Interfaces for Remote Autonomous Systems is for working system engineers who are designing interfaces used in high throughput, high stake, operation centers (op centers) or control rooms, such as network operation centers (NOCs). Intended users will have a technical undergraduate degree (e.g., computer science) with little or no training in design, human sciences, or with human-centered iterative design methods and practices. Background research for the book was supplemented by interaction with the intended audience through a related project with L3Harris Technologies (formerly Harris Corporation).

Given the fundamental challenges to society in this era, a radical rewrite of how we approach science and culture is necessary. This handbook applies Perceptual Control Theory (PCT) to achieve a much needed convergence across the physical, life and social sciences, the humanities and arts. In doing so it addresses challenges such as mental illness, dementia, cancer care, toxic masculinity and societal oppression. It also reveals how PCT can be applied to practical issues such as understanding healthcare service implementation and human-machine interaction, as well as deeper questions such as consciousness and imagination. This second volume of the successful interdisciplinary handbook offers rich examples of how the unifying perceptual control framework can provide a viable alternative to existing theories and methodologies for a timely paradigm shift. Examines the relationship between our perceptions, consciousness, and imagination Provides computational and mathematical models for physiological systems, such as human movement, human-machine interaction, and psychological processes such as recovery from mental health problems Presents health as control which leads to game-changing suggestions in designing interventions for health behavior, cancer support, care for dementia, and mental health services Helps readers comprehend goals of teachers and students in education from a PCT perspective to show how educative interactions could be less coercive and foster flourishing The value of PCT is demonstrated in understanding cultural memes and social challenges such as toxic masculinity

Proceedings of the 14th International Conference on Applied Human Factors and Ergonomics (AHFE 2023), July 20–24, 2023, San Francisco, USA

This book explores how Artificial Intelligence (AI), by leading to an increase in the autonomy of machines and robots, is offering opportunities for an expanded but uncertain impact on society by humans, machines, and robots. To help readers better understand the relationships between AI, autonomy, humans and machines that will help society reduce human errors in the use of advanced technologies (e.g., airplanes, trains, cars), this edited volume presents a wide selection of the underlying theories, computational models, experimental methods, and field applications. While other literature deals with these topics individually, this book unifies the fields of autonomy and AI, framing them in the broader context of effective integration for human-autonomous machine and robotic systems. The contributions, written by world-class researchers and scientists, elaborate on key research topics at the heart of effective human-machine-robot-systems integration. These topics include, for example, computational support for intelligence analyses; the challenge of verifying today’s and future autonomous systems; comparisons between today’s machines and autism; implications of human information interaction on artificial intelligence and errors; systems that reason; the autonomy of machines, robots, buildings; and hybrid teams, where hybrid reflects arbitrary combinations of humans, machines and robots. The contributors span the field of autonomous systems research, ranging from industry and academia to government. Given the broad diversity of the research in this book, the editors strove to thoroughly examine the challenges and trends of systems that implement and exhibit AI; the social implications of present and future systems made autonomous with AI; systems with AI seeking to develop trusted relationships among humans, machines, and robots; and the effective human systems integration that must result for trust in these new systems and their applications to increase and to be sustained.

The idea of autonomous systems that are able to make choices according to properties which allow them to experience, apprehend and assess their environment is becoming a reality. These systems are capable of auto-configuration and self-organization. This book presents a model for the creation of autonomous systems based on a complex substratum, made up of multiple electronic components that deploy a variety of specific features. This substratum consists of multi-agent systems which act continuously and autonomously to collect information from the environment which they then feed into the global system, allowing it to generate discerning and concrete representations of its surroundings. These systems are able to construct a so-called artificial corporeity which allows them to have a sense of self, to then behave autonomously, in a way reminiscent of living organisms.

This book establishes the foundations needed to realize the ultimate goals for artificial intelligence, such as autonomy and trustworthiness. Aimed at scientists, researchers, technologists, practitioners, and students, it brings together contributions offering the basics, the challenges and the state-of-the-art on trusted autonomous systems in a single volume. The book is structured in three parts, with chapters written by eminent researchers and outstanding practitioners and users in the field. The first part covers foundational artificial intelligence technologies, while the second part covers philosophical, practical and technological perspectives on trust. Lastly, the third part presents advanced topics necessary to create future trusted autonomous systems. The book augments theory with real-world applications including cyber security, defence and space.

Going beyond the traditional field of robotics to include other mobile vehicles, this reference and "recipe book" describes important theoretical concepts, techniques, and applications that can be used to build truly mobile intelligent autonomous systems (MIAS). With the infusion of neural networks, fuzzy logic, and genetic algorithm paradigms for MIAS, it blends modeling, sensors, control, estimation, optimization, signal processing, and heuristic methods in MIAS and robotics, and includes examples and applications throughout. Offering a comprehensive view of important topics, it helps readers understand the subject from a system-theoretic and practical point of view.