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.

翻译：意图预测已成为人机交互与人机协作领域的重要研究方向。任何与人类协同操作、旨在辅助并协调其行动与人类伙伴保持一致的人工系统，若能预先推断人类当前的意图，都将从中获益。为避免用户明确表达目标所带来的认知负担，这种推断主要依赖被视为当前行为指示性线索的行为特征。已有研究证实，眼睛运动对任务执行过程中的各个步骤具有高度预测性，因此可作为意图识别中早期且可靠的行为线索。本篇综述旨在建立视觉运动控制心理学领域的见解与基于目光的意图识别在技术领域（尤其是遥操作和辅助机器人系统）相关应用之间的关联。从意图、眼睛运动与行为之间关系的认知原理出发，探讨了人机交互中利用眼动追踪和基于目光的模型进行意图识别的应用，涵盖了主流方法及其多样化应用场景。最后，特别关注了设计此类系统时需纳入考量的重要人因问题及当前局限性。