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Hands-Free Physical Human-Robot Interaction and Testing for Navigating a Virtual Ballbot
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  • Seung Yun Song ,
  • Nadja Marin ,
  • Chenzhang Xiao ,
  • Ryu Okubo ,
  • Joao Ramos ,
  • Elizabeth Hsiao-Wecksler
Seung Yun Song
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Nadja Marin
The University of Illinois at Urbana-Champaign, The University of Illinois at Urbana-Champaign

Corresponding Author:[email protected]

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Chenzhang Xiao
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Ryu Okubo
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Joao Ramos
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Elizabeth Hsiao-Wecksler
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Abstract

This is a submitted (IEEE RO-MAN 2023) draft of a paper on the testing of a hands-free human-robot interaction for navigating a ballbot in a virtual environment. In this study, able-bodied users and manual wheelchair users controlled a virtual ballbot using a hands-free (HF) lean-to-steer control concept that uses torso motions. A custom sensor system (i.e., Torso-dynamics Estimation System (TES)) was utilized to measure and convert the dynamics of the rider’s torso motions into commands to provide HF control of the robot. A simulation study was conducted to explore the efficacy of the HF controller compared to a traditional joystick (JS) controller, and whether there were differences in performance by manual wheelchair users (mWCUs), who may have reduced torso function, compared to able-bodied users (ABUs). Twenty test subjects (10 mWCUs + 10 ABUs) used the subject-specific adjusted TES while wearing a virtual reality headset and were asked to navigate a virtual human rider on the ballbot through obstacle courses replicating seven indoor environment zones.