Safety-Aware Autonomous Systems : Preparing Robots for Life in the Real World
Book Details
Format
Paperback / Softback
ISBN-10
1643685651
ISBN-13
9781643685656
Publisher
IOS Press
Imprint
IOS Press,US
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Apr 29th, 2025
Print length
330 Pages
Weight
540 grams
Product Classification:
Mathematics & science
AI Summary
Ksh 21,600.00
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In an era where autonomous systems such as AI-enabled robots and intelligent transportation systems are poised to transform workplaces, public spaces, and homes, ensuring their safety and reliability is paramount. This book, Safety-Aware Autonomous Systems - Preparing Robots for Life in the Real World, explores how to equip these systems to navigate dynamic, unpredictable environments while maintaining robust safety and efficiency. Central to this research is the development of methods for uncertainty management and probabilistic safety guarantees, enabling autonomous systems to adapt to ever-changing real-world conditions. The book delves into key innovations in runtime monitoring, anomaly detection, and motion planning, providing a holistic framework for safe and effective operations. With a focus on bridging learning, reasoning, and interaction, it also addresses the integration of prediction, classification, and decision-making under uncertainty. Offering a rigorous yet practical approach to preparing robots for life in the real world, this work will appeal to researchers, practitioners, and policymakers shaping the future of autonomous technologies.
In an era where autonomous systems such as AI-enabled robots and intelligent transportation systems are poised to transform workplaces, public spaces, and homes, ensuring their safety and reliability is paramount. This book, Safety-Aware Autonomous Systems - Preparing Robots for Life in the Real World, explores how to equip these systems to navigate dynamic, unpredictable environments while maintaining robust safety and efficiency. Central to this research is the development of methods for uncertainty management and probabilistic safety guarantees, enabling autonomous systems to adapt to ever-changing real-world conditions. The book delves into key innovations in runtime monitoring, anomaly detection, and motion planning, providing a holistic framework for safe and effective operations. With a focus on bridging learning, reasoning, and interaction, it also addresses the integration of prediction, classification, and decision-making under uncertainty. Offering a rigorous yet practical approach to preparing robots for life in the real world, this work will appeal to researchers, practitioners, and policymakers shaping the future of autonomous technologies.
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