TY - GEN
T1 - Joint Action, Adaptation, and Entrainment in Human-Robot Interaction
AU - Fourie, Christopher
AU - Figueroa, Nadia
AU - Shah, Julie
AU - Bienkiewicz, Marta
AU - Bardy, Benoit
AU - Burdet, Etienne
AU - Singamaneni, Phani Teja
AU - Alami, Rachid
AU - Curioni, Arianna
AU - Knoblich, Gunther
AU - Johal, Wafa
AU - Sternad, Dagmar
AU - Jung, Malte
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Research in joint action focuses on the psychological, neurological, and physical mechanisms by which humans collabo-rate with other agents, and overlaps with several domains related to human-robot interaction. The development of artificial systems that can support or emulate the requisite aspects of joint action could lead to improved human-robot team performance as well as improvements in subjective metrics (e.g., trust). This workshop highlights theoretical and technical considerations about human-robot joint action and real-time adaptation, with a particular focus on socio-motor entrainment, showing how the emulation of psychological mechanisms (e.g., emotion, intention signaling, mirroring) can lead to improved performance. We will invite speakers with backgrounds in robotics, neuroscience and psychol-ogy, as well as speakers with a focus in adjacent works, such as in human-robot coordinated dance, alignment, or synchronization. We will call for papers that utilize the theory of joint-action in an interactive human-robot context. We will also call for position papers on the application of the theory of joint action to robotics, with a heavy focus on psychological mechanisms that could potentially be emulated or adapted to a human-robot context. Participants will have the opportunity to brainstorm considerations and techniques that would be applicable to joint action inspired works through breakout sessions with the aim to lead to new and improved collaborations across fields.
AB - Research in joint action focuses on the psychological, neurological, and physical mechanisms by which humans collabo-rate with other agents, and overlaps with several domains related to human-robot interaction. The development of artificial systems that can support or emulate the requisite aspects of joint action could lead to improved human-robot team performance as well as improvements in subjective metrics (e.g., trust). This workshop highlights theoretical and technical considerations about human-robot joint action and real-time adaptation, with a particular focus on socio-motor entrainment, showing how the emulation of psychological mechanisms (e.g., emotion, intention signaling, mirroring) can lead to improved performance. We will invite speakers with backgrounds in robotics, neuroscience and psychol-ogy, as well as speakers with a focus in adjacent works, such as in human-robot coordinated dance, alignment, or synchronization. We will call for papers that utilize the theory of joint-action in an interactive human-robot context. We will also call for position papers on the application of the theory of joint action to robotics, with a heavy focus on psychological mechanisms that could potentially be emulated or adapted to a human-robot context. Participants will have the opportunity to brainstorm considerations and techniques that would be applicable to joint action inspired works through breakout sessions with the aim to lead to new and improved collaborations across fields.
KW - adaptation
KW - entrainment
KW - human-robot interaction
KW - joint action
UR - http://www.scopus.com/inward/record.url?scp=85140783392&partnerID=8YFLogxK
U2 - 10.1109/HRI53351.2022.9889564
DO - 10.1109/HRI53351.2022.9889564
M3 - Conference contribution
AN - SCOPUS:85140783392
T3 - ACM/IEEE International Conference on Human-Robot Interaction
SP - 1250
EP - 1253
BT - HRI 2022 - Proceedings of the 2022 ACM/IEEE International Conference on Human-Robot Interaction
PB - IEEE Computer Society
T2 - 17th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2022
Y2 - 7 March 2022 through 10 March 2022
ER -