Abnormal behavior monitoring based method for safe human-robot collaboration

被引：0
|
作者：
Zhu D. [1 ,2 ,3 ]
Li Z. [1 ,2 ]
Wu Z. [1 ,2 ]
机构：
[1] Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang
[2] Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang
[3] University of Chinese Academy of Sciences, Beijing
来源：
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2022年 / 28卷 / 12期
关键词：
artificial potential field; collision avoidance; human-robot collaboration; minimum distance; motion planning;
D O I：
10.13196/j.cims.2022.12.003
中图分类号：
学科分类号：
摘要：
To ensure the efficient and safe process of human-robot collaboration tasks, a safe human-robot collaboration method based on abnormal behavior monitoring was proposed. The human motion feature model was constructed based on 3D skeleton features of human body, and the motion feature data were de-anomaly and filtered. The standard operating behavior was learned iteratively from the human demonstration and was combined with the minimum human-robot distance to identify and classify the abnormal behavior online. Based on the artificial potential field algorithm, a collision avoidance motion planning was performed for the robot under the abnormal behavior to prevent dangerous human-robot collision. The proposed method was validated by part sorting and human-robot collaborative gluing tasks, and the experimental results showed that the method could effectively ensure the safety of the human-robot collaborative process by accurately monitoring abnormal behaviors. © 2022 CIMS. All rights reserved.
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页码：3737 / 3746
页数：9
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