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arXiv Robotics — research abstracts· Qianggang Ding, Xingyao Wang, Rui Feng, Chi Qin, Weijian Lin, Lizhi Ding, Jiankai Tang, Yuntao Wang, Xiangke Liu, Bang Liu·· 1 days agoSignalEditorial score75

OpenZilo: An Open Smart-Ring Platform for Human-Centric Sensing and Interaction with Robots

OpenZilo: An Open Smart-Ring Platform for Human-Centric Sensing and Interaction with Robots

Summary

This research introduces OpenZilo, an open smart-ring platform designed to connect user input to timely physical action in robotics.

Editorial context

The study evaluates an open smart-ring platform integrating multiple sensors to support wearable robot interfaces, reporting task success rates of 90.4% for speech and 88.8% for gestures across 250 trials per modality with five commands, alongside physiological-event-triggered interaction latencies.

Source: arXiv Robotics — research abstracts · Read original article ↗

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What the source reports

Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.

Reported numbers

  • Reported success rate

    90.4%

    Reported trials

    View original evidence
    n, interaction policy, and robot execution. We characterize seven operating modes and evaluate speech and gesture control with 10 participants. Across five commands and 250 trials per modality, speech and gestures achieved task success rates of 90.4% and 88.8%, respectively. Recognition accuracy exceeded task success for both modalities. Gaussian hidden Markov models achieved higher accuracy than a support vector mac
    Open source S3
  • Reported success rate

    88.8%

    Reported trials

    View original evidence
    n, interaction policy, and robot execution. We characterize seven operating modes and evaluate speech and gesture control with 10 participants. Across five commands and 250 trials per modality, speech and gestures achieved task success rates of 90.4% and 88.8%, respectively. Recognition accuracy exceeded task success for both modalities. Gaussian hidden Markov models achieved higher accuracy than a support vector mac
    Open source S3
  • robot notification-receipt-to-arrival time

    11.71

    View original evidence
    hine across three vocabulary sizes, with longer scoring times. Following a shared spoken task start, gesture-based adjustments had shorter median response times than speech. Whole-task success was 70.0% with gestures and 64.0% with speech. We further examine physiological-event-triggered robot interaction using simulated event notifications. Mean notification-receipt-to-arrival times were 11.71 s for the robot and 9.
    Open source S4
  • number of trials per modality

    250 trials

    Reported trials

    View original evidence
    n, interaction policy, and robot execution. We characterize seven operating modes and evaluate speech and gesture control with 10 participants. Across five commands and 250 trials per modality, speech and gestures achieved task success rates of 90.4% and 88.8%, respectively. Recognition accuracy exceeded task success for both modalities. Gaussian hidden Markov models achieved higher accuracy than a support vector mac
    Open source S3
  • paper: not_reported

What remains unknown

Not established in the collected evidence: Environment, Control, Data origin.

Reported performance applies to the described task. It does not establish general autonomy or deployment readiness.

Source excerpts and review record

Automatically extracted; no manual editorial approval recorded.

n, interaction policy, and robot execution. We characterize seven operating modes and evaluate speech and gesture control with 10 participants. Across five commands and 250 trials per modality, speech and gestures achieved task success rates of 90.4% and 88.8%, respectively. Recognition accuracy exceeded task success for both modalities. Gaussian hidden Markov models achieved higher accuracy than a support vector mac

Open source S3

hine across three vocabulary sizes, with longer scoring times. Following a shared spoken task start, gesture-based adjustments had shorter median response times than speech. Whole-task success was 70.0% with gestures and 64.0% with speech. We further examine physiological-event-triggered robot interaction using simulated event notifications. Mean notification-receipt-to-arrival times were 11.71 s for the robot and 9.

Open source S4

Source:arXiv Robotics — research abstracts · arxiv.org

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