TY - GEN
T1 - Proxemic-aware Augmented Reality For Human-Robot Interaction
AU - Liu, Jingyang
AU - Mao, Hongyu
AU - Bard, Joshua
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - This study introduces a novel proxemic-aware augmented reality (AR) system to mitigate information overload in AR-enabled human-robot interaction (HRI). The system leverages human-robot proxemics to automatically adjust what and how much visual content needs to be presented. Therefore, the operator can perceive the relevant data through AR interfaces without being overwhelmed by excessive information exposure. We propose a task-specific model for evaluating human-robot proxemic (HRP), where the system can identify HRP levels based on raw features, such as distance and orientation. Based on HRP levels, we design a set of visual elements for presenting robots' information at various levels of detail. To demonstrate the functionality of the system, we present a series of proof-of-concept applications showing that our system can assist the operator in a wide range of HRI tasks. The user study proves that the proxemic-aware AR system can reduce mental loading, increase visual clarity, and improve interaction efficiency in HRI.
AB - This study introduces a novel proxemic-aware augmented reality (AR) system to mitigate information overload in AR-enabled human-robot interaction (HRI). The system leverages human-robot proxemics to automatically adjust what and how much visual content needs to be presented. Therefore, the operator can perceive the relevant data through AR interfaces without being overwhelmed by excessive information exposure. We propose a task-specific model for evaluating human-robot proxemic (HRP), where the system can identify HRP levels based on raw features, such as distance and orientation. Based on HRP levels, we design a set of visual elements for presenting robots' information at various levels of detail. To demonstrate the functionality of the system, we present a series of proof-of-concept applications showing that our system can assist the operator in a wide range of HRI tasks. The user study proves that the proxemic-aware AR system can reduce mental loading, increase visual clarity, and improve interaction efficiency in HRI.
UR - http://www.scopus.com/inward/record.url?scp=85187019152&partnerID=8YFLogxK
U2 - 10.1109/RO-MAN57019.2023.10309582
DO - 10.1109/RO-MAN57019.2023.10309582
M3 - Conference Proceeding
AN - SCOPUS:85187019152
T3 - IEEE International Workshop on Robot and Human Communication, RO-MAN
SP - 1323
EP - 1330
BT - 2023 32nd IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2023
PB - IEEE Computer Society
T2 - 32nd IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2023
Y2 - 28 August 2023 through 31 August 2023
ER -