The pursuit of a more natural and empathetic human–robot interaction represents one of the key challenges in contemporary social robotics. This thesis presents the design and implementation of an emotional control system for the TIAGo robot, developed as an extension of previously proposed fuzzy‑logic emotional frameworks and carried out under the supervision of a psychologist. The system integrates real-time facial expression recognition with a fuzzy-logic emotional model that dynamically modulates the robot’s navigation parameters. The goal is to enable the robot to exhibit adaptive and lifelike behaviour by adjusting its motion according to the emotions perceived in the user and its own internal affective state.