The design of model-based robot controllers or simulators requires the use of adequate approaches for selecting the models that fit their functions and intended behavior. In this paper, we propose a methodology based on a test-driven method for designing robot controller simulators that use enzymatic numerical P system models. By applying this methodology, different instances of the model are obtained by tuning different aspects, such as the structure, functions, and parameters of the model based on a set of testing scenarios. Another set of tests is used to validate the model instances obtained. The paper, through the methodology proposed, provides an effective way of combining modeling, simulation, and testing in conjunction with a set of tools associated with them.
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