首页|New Robotics Findings from University of Sheffield Outlined (A Deep Learning-enhanced Digital Twin Framework for Improving Safety and Reliability In Human-robot Collaborative Manufacturing)
New Robotics Findings from University of Sheffield Outlined (A Deep Learning-enhanced Digital Twin Framework for Improving Safety and Reliability In Human-robot Collaborative Manufacturing)
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NETL
NSTL
Elsevier
A new study on Robotics is now available. According to news originating from Sheffield, United Kingdom, by NewsRx correspondents, research stated, “In Industry 5.0, Digital Twins bring in flexibility and efficiency for smart manufacturing. Recently, the success of artificial intelligence techniques such as deep learning has led to their adoption in manufacturing and especially in human-robot collaboration.” Financial supporters for this research include Lloyd's Register Foundation, University of York, Engineering & Physical Sciences Research Council (EPSRC), National Science Foundation (NSF), “Towards Turing 2.0”project under the EPSRC, Alan Turing Institute, Research England via the University of Sheffield's Internal Knowledge Exchange Scheme, “Towards Improved Safety and Reliabil-ity of Cobots” project, RKE “Constructing accurate 3D human with deep learning in digital twin environments for safe human-robot collaboration”project.
SheffieldUnited KingdomEuropeEmerging TechnologiesMachine LearningNano-robotRobotRoboticsUniversity of Sheffield
NETL
NSTL
Elsevier
