Test Methods and Metrics for Effective HRI in Real-World Human-Robot Teams

被引:2
|
作者
Marvel, Jeremy A. [1 ]
Bagchi, Shelly [1 ]
Zimmerman, Megan [1 ]
Aksu, Murat [1 ]
Antonishek, Brian [1 ]
Wang, Yue [2 ]
Mead, Ross [3 ]
Fong, Terry [4 ]
Ben Amor, Heni [5 ]
机构
[1] NIST, Gaithersburg, MD 20899 USA
[2] Clemson Univ, Clemson, SC USA
[3] Semio AI Inc, Los Angeles, CA USA
[4] NASA, Mountain View, CA USA
[5] Arizona State Univ, Tempe, AZ USA
来源
HRI'20: COMPANION OF THE 2020 ACM/IEEE INTERNATIONAL CONFERENCE ON HUMAN-ROBOT INTERACTION | 2020年
关键词
performance metrics; test methods; metrology; repeatability; reproducibility; replicability;
D O I
10.1145/3371382.3374845
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
This second annual, full-day workshop aims to explore the metrology necessary for repeatably and independently assessing the performance of robotic systems in real-world human-robot interaction (HRI) scenarios. This workshop continues the motion toward bridging the gaps between the theory and applications of HRI, enabling reproducible studies in HRI, and accelerating the adoption of cutting edge technologies as the industry state-of-practice. The second annual workshop, 'Test Methods and Metrics for Effective HRI', seeks to identify test methods and metrics for the holistic assessment and assurance of HRI performance in practical applications. The focus is on identifying the key performance indicators of seemingly disparate sectors, and to foster the community based on the principles of transparency, repeatability and reproducibility, and establishing trust. The goal is to aid in the advancement of HRI technologies through the development of experimental design, test methods, and metrics for assessing HRI and interface designs.
引用
收藏
页码:652 / 653
页数:2
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