Towards Real-time Probabilistic Evaluation of Situation Awareness from Human Gaze in Human-Robot Interaction

被引：15
|
作者：
Paletta, Lucas [1 ,3 ]
Dini, Amir [1 ,3 ,4 ]
Murko, Cornelia [1 ,3 ]
Yahyanejad, Saeed [2 ,3 ]
Schwarz, Michael [1 ,3 ]
Lodron, Gerald [1 ,3 ]
Ladstaetter, Stefan [1 ,3 ]
Paar, Gerhard [1 ,3 ]
Velik, Rosemarie [2 ,3 ]
机构：
[1] DIGITAL Inst Informat & Commun Technol, A-8010 Graz, Austria
[2] ROBOT Inst Robot & Mechatron, A-9020 Klagenfurt, Austria
[3] JOANNEUM RES Forsch Gesell MbH, Graz, Austria
[4] Graz Univ Technol, Graz, Austria
来源：
COMPANION OF THE 2017 ACM/IEEE INTERNATIONAL CONFERENCE ON HUMAN-ROBOT INTERACTION (HRI'17) | 2017年
关键词：
Situation awareness; eye tracking; visual attention;
D O I：
10.1145/3029798.3038322
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Human attention processes play a major role for optimization in human-robot interaction (HRI). This work describes a novel methodology to measure situation awareness in real-time from gaze interaction with scene objects of interest using eye tracking glasses and 3D gaze analysis. A probabilistic framework of uncertainty considers coping with measurement errors in eye and position tracking. Comprehensive experiments on HRI were conducted with tasks including handover in a lab based prototypical manufacturing environment. The methodology is proven to predict a standard measure of situation awareness (SAGAT) in real-time and will open new opportunities for human factors based performance optimization in HRI applications.
引用
收藏
页码：247 / 248
页数：2
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