Affiliation:
1. Computer Science Department, University of York, York, UK
Abstract
Abstract
Machines, such as mobile robots and delivery drones, incorporate controllers responsible for a task while
handling risk
(e.g. anticipating and mitigating hazards; preventing and alleviating accidents). We refer to machines with this capability as risk-awaremachines.
Risk awareness
includes robustness and resilience and complicates monitoring (i.e., introspection, sensing, prediction), decision making, and control. From an engineering perspective, risk awareness adds a range of dependability requirements to
system assurance
. Such assurance mandates a correct-by-construction approach to controller design, based on mathematical theory.We introduce RiskStructures, an algebraic framework for risk modelling intended to support the design of
safety controllers
for risk-aware machines. Using the concept of a
risk factor
as a modelling primitive, this framework provides facilities to construct, examine, and assure these controllers.We prove desirable algebraic properties of these facilities, and demonstrate their applicability by using them to specify key aspects of safety controllers for risk-aware automated driving and collaborative robots.
Funder
Deutsche Forschungsgemeinschaft
Lloyd's Register Foundation
Publisher
Association for Computing Machinery (ACM)
Subject
Theoretical Computer Science,Software
Cited by
4 articles.
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