  Intention prediction has become a relevant field of research in Human-Machine
and Human-Robot Interaction. Indeed, any artificial system (co)-operating with
and along humans, designed to assist and coordinate its actions with a human
partner, would benefit from first inferring the human's current intention. To
spare the user the cognitive burden of explicitly uttering their goals, this
inference relies mostly on behavioral cues deemed indicative of the current
action. It has been long known that eye movements are highly anticipatory of
the single steps unfolding during a task, hence they can serve as a very early
and reliable behavioural cue for intention recognition. This review aims to
draw a line between insights in the psychological literature on visuomotor
control and relevant applications of gaze-based intention recognition in
technical domains, with a focus on teleoperated and assistive robotic systems.
Starting from the cognitive principles underlying the relationship between
intentions, eye movements, and action, the use of eye tracking and gaze-based
models for intent recognition in Human-Robot Interaction is considered, with
prevalent methodologies and their diverse applications. Finally, special
consideration is given to relevant human factors issues and current limitations
to be factored in when designing such systems.
