TY - GEN
T1 - Real Time Object Detection in Digital Twin with Point-Cloud Perception for a Robotic Manufacturing Station
AU - Zhang, Quan
AU - Li, Yuhan
AU - Lim, Enggee
AU - Sun, Jie
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The present work aims to develop a digital twin system for a small-scale robot workstation for intelligent manufacturing, based on ROS and Unity 3D. Such digital twin system can be used to remotely visualize, monitor and control the manufacturing process, which is of great significance in the development of industrial automation and intelligent manufacturing. In the present work, the system is preliminarily developed for a pick-and-place task. To extend this framework enabling it to be more intelligent, we have considered integrating, in our framework, the 3D vision perception system with deep learning based vision algorithms, especially for perception of complex objects. The purpose is primarily for real time monitoring of dynamic manufacturing processes such as detecting moving workpiece, 3D formation of complex workpieces in 3D printing, etc., the data of which cannot be obtained from controllers of manufacturing stations. The 3D vision system and the developed algorithm are based on point cloud perception.
AB - The present work aims to develop a digital twin system for a small-scale robot workstation for intelligent manufacturing, based on ROS and Unity 3D. Such digital twin system can be used to remotely visualize, monitor and control the manufacturing process, which is of great significance in the development of industrial automation and intelligent manufacturing. In the present work, the system is preliminarily developed for a pick-and-place task. To extend this framework enabling it to be more intelligent, we have considered integrating, in our framework, the 3D vision perception system with deep learning based vision algorithms, especially for perception of complex objects. The purpose is primarily for real time monitoring of dynamic manufacturing processes such as detecting moving workpiece, 3D formation of complex workpieces in 3D printing, etc., the data of which cannot be obtained from controllers of manufacturing stations. The 3D vision system and the developed algorithm are based on point cloud perception.
KW - 3D vision
KW - deep learning
KW - digital twin
KW - intelligent manufacturing
KW - point clouds
UR - http://www.scopus.com/inward/record.url?scp=85141164407&partnerID=8YFLogxK
U2 - 10.1109/ICAC55051.2022.9911148
DO - 10.1109/ICAC55051.2022.9911148
M3 - Conference Proceeding
AN - SCOPUS:85141164407
T3 - 2022 27th International Conference on Automation and Computing: Smart Systems and Manufacturing, ICAC 2022
BT - 2022 27th International Conference on Automation and Computing
A2 - Yang, Chenguang
A2 - Xu, Yuchun
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 27th International Conference on Automation and Computing, ICAC 2022
Y2 - 1 September 2022 through 3 September 2022
ER -