Social robots are increasingly becoming part of our society. In this sense, such robots’ interaction capabilities depend largely on their ability to detect and respond to stimuli in their environment as humans would. This paper describes a bio-inspired exogenous attention-based perception architecture for social robots. Exogenous attention regulates those involuntary attentional processes driven by the salience of perceived stimuli. The architecture incorporates bio-inspired concepts, such as inhibition to return, focus of attention selection and detecting salient stimuli, that have been validated on a real social robot. We have integrated several multimodal mechanisms for recognising salient visual, auditory, and tactile stimuli. Then, the attention architecture’s performance was evaluated by comparing it to a ground truth gathered from interactions of 50 users, obtaining comparable responses in real-time.