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