Social Interfaces in TeleoperationSocial Human-Robot Interaction has demonstrated that people are very good at understanding social signals from robots. Use of these social signals has improved the interaction experience, and can be used as additional bandwidth to communicate robot state. In this project, we investigate how social signals can be used in teleoperation interfaces to support an opertor by improving their performance and mental state (fatigue, emotions, etc).Project PublicationsBackseat Teleoperator: affective feedback with on-screen agents to influence teleoperationDaniel J. Rea, James E. Young, “Backseat Teleoperator: affective feedback with on-screen agents to influence teleoperation.” The ACM/IEEE International Conference on Human-Robot Interaction (HRI’19). ACM/IEEE. 2019.CollaboratorsDaniel J. ReaAssistant ProfessorJames E.YoungProfessor
Social Interfaces in TeleoperationSocial Human-Robot Interaction has demonstrated that people are very good at understanding social signals from robots. Use of these social signals has improved the interaction experience, and can be used as additional bandwidth to communicate robot state. In this project, we investigate how social signals can be used in teleoperation interfaces to support an opertor by improving their performance and mental state (fatigue, emotions, etc).Project PublicationsBackseat Teleoperator: affective feedback with on-screen agents to influence teleoperationDaniel J. Rea, James E. Young, “Backseat Teleoperator: affective feedback with on-screen agents to influence teleoperation.” The ACM/IEEE International Conference on Human-Robot Interaction (HRI’19). ACM/IEEE. 2019.
Social Interfaces in TeleoperationSocial Human-Robot Interaction has demonstrated that people are very good at understanding social signals from robots. Use of these social signals has improved the interaction experience, and can be used as additional bandwidth to communicate robot state. In this project, we investigate how social signals can be used in teleoperation interfaces to support an opertor by improving their performance and mental state (fatigue, emotions, etc).
Social Human-Robot Interaction has demonstrated that people are very good at understanding social signals from robots. Use of these social signals has improved the interaction experience, and can be used as additional bandwidth to communicate robot state. In this project, we investigate how social signals can be used in teleoperation interfaces to support an opertor by improving their performance and mental state (fatigue, emotions, etc).
Project PublicationsBackseat Teleoperator: affective feedback with on-screen agents to influence teleoperationDaniel J. Rea, James E. Young, “Backseat Teleoperator: affective feedback with on-screen agents to influence teleoperation.” The ACM/IEEE International Conference on Human-Robot Interaction (HRI’19). ACM/IEEE. 2019.
Backseat Teleoperator: affective feedback with on-screen agents to influence t
Stela H. Seo, James E. Young. “What happened while I was away? Leveraging visual transition techniques to convey robot states in multi-robot teleoperation,” International Conference on Social Robotics, November 2021. Springer. Singapore.
Rea, D.J., Seo, S.H. & Young, J.E. Social Robotics for Nonsocial Teleoperation: Leveraging Social Techniques to Impact Teleoperator Performance and Experience. Curr Robot Rep (2020). https://doi.org/10.1007/s43154-020-00020-7
Daniel J. Rea. 2020. Now you’re teleoperating with power: learning from video games to improve teleoperation interfaces. Ph.D. Thesis (2020). University of Manitoba, Winnipeg, Canada.
Daniel J. Rea, James E. Young, "Backseat Teleoperator: affective feedback with on-screen agents to influence teleoperation." The ACM/IEEE International Conference on Human-Robot Interaction (HRI'19). ACM/IEEE. 2019.
