Robotics & Machine Learning Daily News2024,Issue(Mar.19) :48-48.DOI:10.1016/j.jmapro.2023.12.055

Investigators at Huazhong University of Science and Technology Report Findings i n Robotics (Grain Shape-protrusion-based Modeling and Analysis of Material Remov al In Robotic Belt Grinding)

Robotics & Machine Learning Daily News2024,Issue(Mar.19) :48-48.DOI:10.1016/j.jmapro.2023.12.055

Investigators at Huazhong University of Science and Technology Report Findings i n Robotics (Grain Shape-protrusion-based Modeling and Analysis of Material Remov al In Robotic Belt Grinding)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ro botics. According to news originating from Wuhan, People’s Republic of China, by NewsRx correspondents, research stated, “The accurate prediction of material re moval (MR) remains a persistent challenge in the field of robotic belt grinding, particularly with the consideration of the stochastic nature of abrasive grains . Starting from the characteristics that abrasive grains with different shapes p articipate in grinding, this work presents a novel MR model that extends from mi croscopic grain-workpiece interaction to macroscopic wheel-curved surface contac t.”

Key words

Wuhan/People’s Republic of China/Asia/Emerging Technologies/Machine Learning/Robotics/Robots/Huazhong University of Science and Technology

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
参考文献量61
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