When interacting in socially-relevant applications, robots are expected to engage with humans while displaying attentional behaviours that resemble those of their interlocutors; as a matter of fact, they are supposed to be able to assess intentionality and to be, themselves, intentional agents.
Several solutions have been proposed for providing social robots with the ability of engaging in joint attention, the ability to share attention with another agent towards the same object or event, one of the most primal of social interactions. However, they have yet to appropriately capture some of the most crucial skills involved, such as the multisensory nature of active perception and attention, its inherent uncertainty, or the processes responsible for the emergence of an intentional stance. Consequently, social robots have only been able to instil a sense of intentionality and reciprocity for very specific and constrained social scenarios.
We therefore propose to research an integrated probabilistic framework to deal with the endogenous and exogenous coordinated control of stimulus-driven and goal-directed multisensory attention within the context of social interaction.
Designing a full-fledged artificial attention system: