In the Arms of a Robot: Designing Autonomous Hugging Robots with Intra-Hug Gestures
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In the Arms of a Robot : Designing Autonomous Hugging Robots with Intra-Hug Gestures. / Block, Alexis E.; Seifi, Hasti; Hilliges, Otmar; Gassert, Roger; Kuchenbecker, Katherine J.
In: ACM Transactions on Human-Robot Interaction, Vol. 12, No. 2, 3526110, 2023.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - In the Arms of a Robot
T2 - Designing Autonomous Hugging Robots with Intra-Hug Gestures
AU - Block, Alexis E.
AU - Seifi, Hasti
AU - Hilliges, Otmar
AU - Gassert, Roger
AU - Kuchenbecker, Katherine J.
N1 - Funding Information: This work was partially supported by the Max Planck ETH Center for Learning Systems and the IEEE RAS Technical Committee on Haptics Funding Information: This work was partially supported by the Max Planck ETH Center for Learning Systems and the IEEE RAS Technical Committee on Haptics. Publisher Copyright: © 2023 Copyright held by the owner/author(s).
PY - 2023
Y1 - 2023
N2 - Hugs are complex affective interactions that often include gestures like squeezes. We present six new guidelines for designing interactive hugging robots, which we validate through two studies with our custom robot. To achieve autonomy, we investigated robot responses to four human intra-hug gestures: holding, rubbing, patting, and squeezing. A Total of 32 users each exchanged and rated 16 hugs with an experimenter-controlled HuggieBot 2.0. The robot's inflated torso's microphone and pressure sensor collected data of the subjects' demonstrations that were used to develop a perceptual algorithm that classifies user actions with 88% accuracy. Users enjoyed robot squeezes, regardless of their performed action, they valued variety in the robot response, and they appreciated robot-initiated intra-hug gestures. From average user ratings, we created a probabilistic behavior algorithm that chooses robot responses in real time. We implemented improvements to the robot platform to create HuggieBot 3.0 and then validated its gesture perception system and behavior algorithm with 16 users. The robot's responses and proactive gestures were greatly enjoyed. Users found the robot more natural, enjoyable, and intelligent in the last phase of the experiment than in the first. After the study, they felt more understood by the robot and thought robots were nicer to hug.
AB - Hugs are complex affective interactions that often include gestures like squeezes. We present six new guidelines for designing interactive hugging robots, which we validate through two studies with our custom robot. To achieve autonomy, we investigated robot responses to four human intra-hug gestures: holding, rubbing, patting, and squeezing. A Total of 32 users each exchanged and rated 16 hugs with an experimenter-controlled HuggieBot 2.0. The robot's inflated torso's microphone and pressure sensor collected data of the subjects' demonstrations that were used to develop a perceptual algorithm that classifies user actions with 88% accuracy. Users enjoyed robot squeezes, regardless of their performed action, they valued variety in the robot response, and they appreciated robot-initiated intra-hug gestures. From average user ratings, we created a probabilistic behavior algorithm that chooses robot responses in real time. We implemented improvements to the robot platform to create HuggieBot 3.0 and then validated its gesture perception system and behavior algorithm with 16 users. The robot's responses and proactive gestures were greatly enjoyed. Users found the robot more natural, enjoyable, and intelligent in the last phase of the experiment than in the first. After the study, they felt more understood by the robot and thought robots were nicer to hug.
KW - Additional Key Words and PhrasesSocial-physical human-robot interaction
KW - behavioral algorithm
KW - haptic sensing
KW - user study
U2 - 10.1145/3526110
DO - 10.1145/3526110
M3 - Journal article
AN - SCOPUS:85164244102
VL - 12
JO - ACM Transactions on Human-Robot Interaction
JF - ACM Transactions on Human-Robot Interaction
SN - 2573-9522
IS - 2
M1 - 3526110
ER -
ID: 373668579