TEAMMATE: A Scalable System for Measuring Affect in Human-Machine Teams
- Resource Type
- Conference
- Authors
- Wen, James; Stewart, Amanda; Billinghurst, Mark; Tossel, Chad
- Source
- 2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN) Robot and Human Interactive Communication (RO-MAN), 2018 27th IEEE International Symposium on. :991-996 Aug, 2018
- Subject
- Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Bonding
Legged locomotion
Task analysis
Time measurement
Atmospheric measurements
- Language
- ISSN
- 1944-9437
Strong empathic bonding between members of a team can elevate team performance tremendously but it is not clear how such bonding within human-machine teams may impact upon mission success. Prior work using self-reporting surveys and end-of-task metrics do not capture how such bonding may evolve over time and impact upon task fulfillment. Furthermore, sensor-based measures do not scale easily to facilitate the need to collect substantial data for measuring potentially subtle effects. We introduce TEAMMATE, a system designed to provide insights into the emotional dynamics humans may form for machine teammates that could critically impact upon the design of human machine teams.