Free (Robot) Hugs! An Embracing Multimodal Dataset

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Free (Robot) Hugs! An Embracing Multimodal Dataset

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The human hug process begins with the motivation for the hug, usually stirred emotions; followed by approaching, which can range from awkward to cautious to eager; then arm-opening, and position and pressure choices, eye contact vulnerabilities, timing questions, and so on.
The simple hug actually presents a highly complex series of actions and emotions replete with rich interactive details for artificial intelligence researchers to study.
As the new generation grows up with omnipresent artificial intelligence, scientists believe robots will be expected to assume more nuanced roles in human-robot collaborations.
Currently, there are not many high quality human-robot interaction datasets.
In an attempt to unlock the science behind hugs, a team of researchers from Arizona State University slapped wearable sensors on 33 humans and collected data on their more than 350 huggings with the humanoid remote-controlled robot “Baxter.” The researchers believe the resulting dataset can help autonomous humanoids behave more like people.
To aid in data collection, human participants wore Myo armbands, pressure sensing shoes, and a hat with motion capture markers.
Participants were asked to approach the robot for a hug then return to their starting point.
Researchers used the humans’ armbands to measure acceleration and orientation of the arms, and recorded for example whether the humans contacted the robots at upper forearm, lower forearm or wrist.
During the experiments, some participants called out to the unseen human operator with questions such as “Does the robot hug tightly?” and “What if the robot does not hug me?.” Researchers suggest the participants might have forgotten the robot was not autonomous because its acquired hugging skills were humanlike and the experience “immersive.”
Learning a tender technique like hugging will be important for the robots of the future

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