Data-Driven Model of Off-Line Collision Safety Based on Neural Network for Cooperative Robot

Tengfei Cui; Jingshen Zhao; Lixing Jin; Quanbin Lai; Jiale Huan; Ye Tian; Xingguang Duan

doi:10.1109/ROBIO55434.2022.10011869

Data-Driven Model of Off-Line Collision Safety Based on Neural Network for Cooperative Robot

Tengfei Cui, Jingshen Zhao, Lixing Jin, Quanbin Lai, Jiale Huan, Ye Tian, Xingguang Duan^*

^*此作品的通讯作者

机电学院

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

In the application of industrial production, it is crucial for cooperative robots to avoid collision and retain safety. This paper presents an off-line model to assess the level of collision risk based on BP neural network. A detection device was designed to collect the required data composed of force and displacement, while the risk level was assessed according to the relevant standard with collision force and the calculated collision power. The collected data was used for training of neural network and the off-line model is built. The preliminary experiment is carried out, while the performance and the feasible are verified by the results.

源语言	英语
主期刊名	2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022
出版商	Institute of Electrical and Electronics Engineers Inc.
页	481-488
页数	8
ISBN（电子版）	9781665481090
DOI	https://doi.org/10.1109/ROBIO55434.2022.10011869
出版状态	已出版 - 2022
活动	2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022 - Jinghong, 中国期限: 5 12月 2022 → 9 12月 2022

出版系列

姓名	2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

会议

会议	2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022
国家/地区	中国
市	Jinghong
时期	5/12/22 → 9/12/22

访问文件

10.1109/ROBIO55434.2022.10011869

其它文件与链接

链接到 Scopus 的出版物

引用此

Cui, T., Zhao, J., Jin, L., Lai, Q., Huan, J., Tian, Y., & Duan, X. (2022). Data-Driven Model of Off-Line Collision Safety Based on Neural Network for Cooperative Robot. 在 2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022 (页码 481-488). (2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ROBIO55434.2022.10011869

Cui, Tengfei ; Zhao, Jingshen ; Jin, Lixing 等. / Data-Driven Model of Off-Line Collision Safety Based on Neural Network for Cooperative Robot. 2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022. Institute of Electrical and Electronics Engineers Inc., 2022. 页码 481-488 (2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022).

@inproceedings{c481deac89414b3e87ef6a2cd5404072,

title = "Data-Driven Model of Off-Line Collision Safety Based on Neural Network for Cooperative Robot",

abstract = "In the application of industrial production, it is crucial for cooperative robots to avoid collision and retain safety. This paper presents an off-line model to assess the level of collision risk based on BP neural network. A detection device was designed to collect the required data composed of force and displacement, while the risk level was assessed according to the relevant standard with collision force and the calculated collision power. The collected data was used for training of neural network and the off-line model is built. The preliminary experiment is carried out, while the performance and the feasible are verified by the results.",

author = "Tengfei Cui and Jingshen Zhao and Lixing Jin and Quanbin Lai and Jiale Huan and Ye Tian and Xingguang Duan",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022 ; Conference date: 05-12-2022 Through 09-12-2022",

year = "2022",

doi = "10.1109/ROBIO55434.2022.10011869",

language = "English",

series = "2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "481--488",

booktitle = "2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022",

address = "United States",

}

Cui, T, Zhao, J, Jin, L, Lai, Q, Huan, J, Tian, Y & Duan, X 2022, Data-Driven Model of Off-Line Collision Safety Based on Neural Network for Cooperative Robot. 在 2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022. 2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022, Institute of Electrical and Electronics Engineers Inc., 页码 481-488, 2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022, Jinghong, 中国, 5/12/22. https://doi.org/10.1109/ROBIO55434.2022.10011869

Data-Driven Model of Off-Line Collision Safety Based on Neural Network for Cooperative Robot. / Cui, Tengfei; Zhao, Jingshen; Jin, Lixing 等.
2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022. Institute of Electrical and Electronics Engineers Inc., 2022. 页码 481-488 (2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Data-Driven Model of Off-Line Collision Safety Based on Neural Network for Cooperative Robot

AU - Cui, Tengfei

AU - Zhao, Jingshen

AU - Jin, Lixing

AU - Lai, Quanbin

AU - Huan, Jiale

AU - Tian, Ye

AU - Duan, Xingguang

PY - 2022

Y1 - 2022

N2 - In the application of industrial production, it is crucial for cooperative robots to avoid collision and retain safety. This paper presents an off-line model to assess the level of collision risk based on BP neural network. A detection device was designed to collect the required data composed of force and displacement, while the risk level was assessed according to the relevant standard with collision force and the calculated collision power. The collected data was used for training of neural network and the off-line model is built. The preliminary experiment is carried out, while the performance and the feasible are verified by the results.

AB - In the application of industrial production, it is crucial for cooperative robots to avoid collision and retain safety. This paper presents an off-line model to assess the level of collision risk based on BP neural network. A detection device was designed to collect the required data composed of force and displacement, while the risk level was assessed according to the relevant standard with collision force and the calculated collision power. The collected data was used for training of neural network and the off-line model is built. The preliminary experiment is carried out, while the performance and the feasible are verified by the results.

UR - http://www.scopus.com/inward/record.url?scp=85147330196&partnerID=8YFLogxK

U2 - 10.1109/ROBIO55434.2022.10011869

DO - 10.1109/ROBIO55434.2022.10011869

M3 - Conference contribution

AN - SCOPUS:85147330196

T3 - 2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

SP - 481

EP - 488

BT - 2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

Y2 - 5 December 2022 through 9 December 2022

ER -

Cui T, Zhao J, Jin L, Lai Q, Huan J, Tian Y 等. Data-Driven Model of Off-Line Collision Safety Based on Neural Network for Cooperative Robot. 在 2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022. Institute of Electrical and Electronics Engineers Inc. 2022. 页码 481-488. (2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022). doi: 10.1109/ROBIO55434.2022.10011869

Data-Driven Model of Off-Line Collision Safety Based on Neural Network for Cooperative Robot

摘要

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