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.

中文翻译：

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RiskStructures：风险感知机器的设计代数

摘要

机器，例如移动机器人和送货无人机，在处理风险（例如预测和减轻危险；预防和减轻事故）的同时包含负责任务的控制器。我们将具有这种能力的机器称为风险感知机器。风险意识包括稳健性和弹性，并使监控（即内省、感知、预测）、决策和控制复杂化。从工程的角度来看，风险意识为系统保证增加了一系列可靠性要求。这种保证要求基于数学理论的控制器设计采用一种构造正确的方法。我们引入了 RiskStructures，一种用于风险建模的代数框架，旨在支持风险感知机器的安全控制器。使用风险因素的概念作为建模原语，该框架提供了构造、检查和确保这些控制器的设施。我们证明了这些设施的理想代数属性，并通过使用它们来指定安全控制器的关键方面来证明它们的适用性具有风险意识的自动驾驶和协作机器人。