Model-based systems engineering (MBSE) is a methodology that exploits system representation during the entire system life-cycle. The use of formal models has gained momentum in robotics engineering over the past few years. Models play a crucial role in robot design; they serve as the basis for achieving holistic properties, such as functional reliability or adaptive resilience, and facilitate the automated production of modules. We propose the use of formal conceptualizations beyond the engineering phase, providing accurate models that can be leveraged at runtime. This paper explores the use of Category Theory, a mathematical framework for describing abstractions, as a formal language to produce such robot models. To showcase its practical application, we present a concrete example based on the Marathon 2 experiment. Here, we illustrate the potential of formalizing systems -- including their recovery mechanisms -- which allows engineers to design more trustworthy autonomous robots. This, in turn, enhances their dependability and performance.
翻译:基于模型的系统工程(MBSE)是一种方法,它利用了整个系统生命周期的系统代表性。过去几年来,正式模型的使用在机器人工程中获得了势头。模型在机器人设计中发挥着关键作用;模型作为实现整体特性的基础,例如功能可靠性或适应性复原力,并促进模块的自动生产。我们提议在工程阶段之后使用正式的概念化,提供可以运行时加以利用的准确模型。本文探讨使用“分类理论”这一描述抽象的数学框架,作为制作此类机器人模型的正式语言。为了展示其实际应用,我们以马拉松2号实验为基础,举了一个具体例子。我们在这里展示了使系统正规化的潜力,包括其恢复机制,使工程师能够设计更可信赖的自主机器人。这反过来又增强了其可靠性和性能。</s>