Developing The Bottom-up Attentional System of A Social Robot

This paper describes the development of a 3- stage signalling framework to trigger a social robot's bottom- up reactive behavior inspired by a biological model. In the first stage, low-level firing of stimuli due to external sources is constructed through perception grounding. This is followed by a saliency classifier which fires-up high level salient signals that require attention and are used to trigger the robot's reactive behavior. The whole framework evolves primarily on the knowledge ontology that defines the characteristics of the social robot and the querying mechanism that correlates the perceived stimuli with the ontology to trigger the reactive behavior. We evaluated the performance of our system with timing metrics and we achieved good results for our application.