To accomplish this, a modified optimization formulation of SR is developed and implemented in combination with a framework for physical model selection. As a proof of concept, several case studies were investigated in the areas of rheology and reaction engineering. The purpose is to illustrate an automated research pipeline deriving interpretable and generalizable models and thereby providing access to physical knowledge from data generated in robotic experiments. Within this big picture, closing the loop of utilizing the obtained physical models in further experimentation and generation of physical knowledge by (automated) interpretation remains for future research, as shown in Figure .