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Safe Autonomy with Control Barrier Functions [electronic resource] : Theory and Applications / by Wei Xiao, Christos G. Cassandras, Calin Belta.

By: Xiao, Wei [author.].
Contributor(s): Cassandras, Christos G [author.] | Belta, Calin [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Synthesis Lectures on Computer Science: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2023Edition: 1st ed. 2023.Description: XX, 212 p. 56 illus., 54 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783031275760.Subject(s): Control engineering | Robotics | Automation | Machine learning | Dynamics | Nonlinear theories | Artificial intelligence | Control, Robotics, Automation | Control and Systems Theory | Machine Learning | Applied Dynamical Systems | Artificial Intelligence | AutomationAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 629.8 Online resources: Click here to access online
Contents:
Introduction to Autonomy and Safety -- Control Barrier Functions -- High Order Control Barrier Functions -- Feasibility Guarantees for CBFs -- Adaptive CBFs -- Safety Guarantees for Systems with Unknown Dynamics -- Applications to Traffic Networks -- Applications to Robotics -- Conclusions and Future Directions.
In: Springer Nature eBookSummary: This book presents the concept of Control Barrier Function (CBF), which captures the evolution of safety requirements during the execution of a system and can be used to enforce safety. Safety is formalized using an emerging state-of-the-art approach based on CBFs, and many illustrative examples from autonomous driving, traffic control, and robot control are provided. Safety is central to autonomous systems since they are intended to operate with minimal or no human supervision, and a single failure could result in catastrophic results. The authors discuss how safety can be guaranteed via both theoretical and application perspectives. This presented method is computationally efficient and can be easily implemented in real-time systems that require high-frequency reactive control. In addition, the CBF approach can easily deal with nonlinear models and complex constraints used in a wide spectrum of applications, including autonomous driving, robotics, and traffic control. Withthe proliferation of autonomous systems, such as self-driving cars, mobile robots, and unmanned air vehicles, safety plays a crucial role in ensuring their widespread adoption. This book considers the integration of safety guarantees into the operation of such systems including typical safety requirements that involve collision avoidance, technological system limitations, and bounds on real-time executions. Adaptive approaches for safety are also proposed for time-varying execution bounds and noisy dynamics. In addition, this book: Presents all aspects of safe autonomy including the theoretical development, solution of specific problems, and analysis and resolution of feasibility guarantees; Discusses how the Control Barrier Function (CBF) approach can be used for most autonomous systems and proposes safety guarantees for systems with unknown dynamics using novel event-driven approaches; Establishes the basic concepts, definitions, and algorithms required to understand the CBF approach, making it easy to comprehend and apply in practice.
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Introduction to Autonomy and Safety -- Control Barrier Functions -- High Order Control Barrier Functions -- Feasibility Guarantees for CBFs -- Adaptive CBFs -- Safety Guarantees for Systems with Unknown Dynamics -- Applications to Traffic Networks -- Applications to Robotics -- Conclusions and Future Directions.

This book presents the concept of Control Barrier Function (CBF), which captures the evolution of safety requirements during the execution of a system and can be used to enforce safety. Safety is formalized using an emerging state-of-the-art approach based on CBFs, and many illustrative examples from autonomous driving, traffic control, and robot control are provided. Safety is central to autonomous systems since they are intended to operate with minimal or no human supervision, and a single failure could result in catastrophic results. The authors discuss how safety can be guaranteed via both theoretical and application perspectives. This presented method is computationally efficient and can be easily implemented in real-time systems that require high-frequency reactive control. In addition, the CBF approach can easily deal with nonlinear models and complex constraints used in a wide spectrum of applications, including autonomous driving, robotics, and traffic control. Withthe proliferation of autonomous systems, such as self-driving cars, mobile robots, and unmanned air vehicles, safety plays a crucial role in ensuring their widespread adoption. This book considers the integration of safety guarantees into the operation of such systems including typical safety requirements that involve collision avoidance, technological system limitations, and bounds on real-time executions. Adaptive approaches for safety are also proposed for time-varying execution bounds and noisy dynamics. In addition, this book: Presents all aspects of safe autonomy including the theoretical development, solution of specific problems, and analysis and resolution of feasibility guarantees; Discusses how the Control Barrier Function (CBF) approach can be used for most autonomous systems and proposes safety guarantees for systems with unknown dynamics using novel event-driven approaches; Establishes the basic concepts, definitions, and algorithms required to understand the CBF approach, making it easy to comprehend and apply in practice.

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