收集80人装配任务中眼动与动作数据，助力人机协作效率与安全提升。
GAIPAT -Dataset on Human Gaze and Actions for Intent Prediction in Assembly Tasks
- 通过头戴与远距离眼动仪，在坐/站姿下采集装配任务中的眼动与动作
- 覆盖约80名参与者，涵盖不同姿势与眼动设备的多模态数据
- 适用于人机协作、注意力建模及工业场景下的意图预测研究
该数据集旨在深入理解人类在协同机器人共用工作环境中，动作与眼动之间的耦合关系，以显著提升人机交互的效率与安全性。更广泛而言，通过将眼动模式与物理动作关联，该数据集为装配任务中的认知过程与注意力动态提供了宝贵洞察。数据集包含约80名参与者在模拟工业装配任务中产生的眼动与动作数据。任务通过受控场景进行，参与者操作教育类积木。眼动数据采用两种不同的眼动追踪系统（头戴式与远程式）采集，实验在坐姿和站姿两种位置下完成。
原文摘要 · Abstract (English)
The primary objective of the dataset is to provide a better understanding of the coupling between human actions and gaze in a shared working environment with a cobot, with the aim of signifcantly enhancing the effciency and safety of humancobot interactions. More broadly, by linking gaze patterns with physical actions, the dataset offers valuable insights into cognitive processes and attention dynamics in the context of assembly tasks. The proposed dataset contains gaze and action data from approximately 80 participants, recorded during simulated industrial assembly tasks. The tasks were simulated using controlled scenarios in which participants manipulated educational building blocks. Gaze data was collected using two different eye-tracking setups -head-mounted and remote-while participants worked in two positions: sitting and standing.
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