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A Method for Detecting Key Points of Transferring Barrel Valve by Integrating Keypoint R-CNN and MobileNetV3

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成果类型:
期刊论文
作者:
Huang, Canyu;Lei, Zeyong;Li, Linhui;Zhong, Lin;Lei, Jieheng;...
通讯作者:
Lei, ZY
作者机构:
[Huang, Canyu; Wang, Shuiming; Lei, Zeyong; Li, Linhui; Lei, ZY; Zhong, Lin] Univ South China, Sch Mech Engn, Hengyang 421001, Peoples R China.
[Lei, Jieheng] Univ South China, Sch Elect Engn, Hengyang 421001, Peoples R China.
通讯机构:
[Lei, ZY ] U
Univ South China, Sch Mech Engn, Hengyang 421001, Peoples R China.
语种:
英文
关键词:
keypoint detection;keypoint R-CNN;MobileNet V3;attention module;feature pyramid network
期刊:
Electronics
ISSN:
2079-9292
年:
2023
卷:
12
期:
20
基金类别:
Ministry of Science and Technology of the People's Republic of China [2019YFC1907704]
机构署名:
本校为第一且通讯机构
院系归属:
机械工程学院
电气工程学院
摘要:
Industrial robots need to accurately identify the position and rotation angle of the handwheel of chemical raw material barrel valves during the process of opening and closing, in order to avoid interference between the robot gripper and the handwheel. This paper proposes a handwheel keypoint detection algorithm for fast and accurate acquisition of handwheel position and rotation pose. The algorithm is based on the Keypoint R-CNN (Region-based Convolutional Neural Network) keypoint detection model, which integrates the lightweight mobile network MobileNetV3, the Coordinate Attention module, an...

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