Safety Control for Close Proximity Human‐Robot Collaboration Based on Trust and Danger Assessment

Yueqi An et al.

Human Factors and Ergonomics In Manufacturing2026https://doi.org/10.1002/hfm.70033article
AJG 1
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0.50

What the paper says

With the increasing application of robots in industrial manufacturing, ensuring the safety of robots designed for close‐proximity human‐robot collaboration (HRC) has become paramount. Trust is a critical factor influencing human‐perceived safety and is essential for sustainable HRC. However, the integration of trust‐related influences into safety strategies for close‐proximity HRC remains underexplored. This study aims to investigate safety control mechanisms centered around human trust in robots within close‐proximity HRC environments. Task performance and safety performance are considered as key factors affecting trust, and Bayesian inference is employed for human trust assessment. Additionally, the concept of a danger field (DF) is introduced, and the DF calculation formula is refined to enhance robot danger assessment. Building on trust and danger assessments, a safety control strategy is designed by integrating the relationship between trust and safety. To validate the effectiveness of this strategy, a scenario is constructed in the Virtual Robot Experiment Platform where a digital human and a UR5 robot collaboratively transport goods, and the safety system is subsequently integrated to conduct simulation experiments. The results indicate that the implementation of the safety control strategy leads to a reduction in peak robot joint speed, a significant decrease in the maximum, mean, and variance of danger assessment values, and a rapid response capability to shut down the system under high‐risk conditions. These findings confirm the reliability of the proposed safety control framework.

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https://doi.org/https://doi.org/10.1002/hfm.70033

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@article{yueqi2026,
  title        = {{Safety Control for Close Proximity Human‐Robot Collaboration Based on Trust and Danger Assessment}},
  author       = {Yueqi An et al.},
  journal      = {Human Factors and Ergonomics In Manufacturing},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1002/hfm.70033},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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