Error recovery in wearable robotic Co-Grasping: the role of human-led correction

These results indicate that trust in faulty automation can be repaired and that enabling users to assume control over system actuation in response to such faults can prevent errors from negatively affecting overall device function. Facilitating human-led dynamic changes in human and robot role allocation through this Co-Grasping device lays a promising foundation for unique human-robot interactions that promote high performance and where trust can recover quickly, despite existing challenges in developing perfect automated systems.

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Publication Details

Journal
Frontiers in Robotics and AI
Published
2025-10-09
DOI
https://doi.org/10.3389/frobt.2025.1598296
Citations
1
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
1.21
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article

Error recovery in wearable robotic Co-Grasping: the role of human-led correction

Hannah S. Stuart, Wilson Torres, Erin Y. Chang
1 citations
Frontiers in Robotics and AI
Robot Manipulation and Learning
1.21
article

Error recovery in wearable robotic Co-Grasping: the role of human-led correction

Hannah S. Stuart, Wilson Torres, Erin Y. Chang
article en
1 citations

Abstract

These results indicate that trust in faulty automation can be repaired and that enabling users to assume control over system actuation in response to such faults can prevent errors from negatively affecting overall device function. Facilitating human-led dynamic changes in human and robot role allocation through this Co-Grasping device lays a promising foundation for unique human-robot interactions that promote high performance and where trust can recover quickly, despite existing challenges in developing perfect automated systems.

Frontiers in Robotics and AIVol. 12
University of California, Berkeley (US)
Openalex Percentile: Top 16%
Robot Manipulation and Learning
1.21
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