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

页码：247 / 248

页数：2

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