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）是一种在整个系统生命周期中利用系统表示的方法论。近年来，形式化模型在机器人工程中的应用日益受到重视。模型在机器人设计中发挥着关键作用：它们既是实现功能可靠性、自适应韧性等整体特性的基础，也促进了模块的自动化生产。我们提出在工程阶段之外采用形式化概念化方法，提供可在运行时利用的精确模型。本文探索将范畴论（一种描述抽象概念的数学框架）作为形式化语言来生成此类机器人模型。为展示其实际应用，我们以Marathon 2实验为例进行具体说明。通过该案例，我们阐释了形式化系统（包括其恢复机制）的潜力——这使工程师能够设计更可信的自主机器人，进而提升其可靠性与性能。