首页|Findings from Huazhong University of Science and Technology Yields New Data on R obotics (Cme-epc: a Coarse-mechanism Embedded Error Prediction and Compensation Framework for Robot Multi-condition Tasks)
Findings from Huazhong University of Science and Technology Yields New Data on R obotics (Cme-epc: a Coarse-mechanism Embedded Error Prediction and Compensation Framework for Robot Multi-condition Tasks)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on Robotics are disc ussed in a new report. According to news reporting originating from Wuhan, Peopl e's Republic of China, by NewsRx correspondents, research stated, "While industr ial robots are widely used in various fields owing to their large workspace and high flexibility, significant errors constrain their application in high-precisi on scenarios. Though there have been notable achievements in mechanism modeling for different working conditions, they are complex, work-dependent, and difficul t to apply conveniently to multiple operating conditions." Our news editors obtained a quote from the research from the Huazhong University of Science and Technology, "Therefore, a coarse-mechanism embedded error predic tion and compensation (CME-EPC) framework for robot multi-condition tasks is pro posed, combining knowledge-rich coarse mechanism models and intelligent algorith ms. These modules are proposed in CME-EPC, including coarse mechanism embedded s imulation domain construction, active learning-based labeling of few-shots, and clusteringguided balanced domain adaptation transfer learning. These modules pe rform jointly to achieve accurate prediction and reliable compensation of errors . The proposed framework is experimentally validated in four tasks under three c onditions, achieving superior performance compared to the other six methods with a conventional coarse-mechanism model and 10 % of the labeled sam ples."
WuhanPeople's Republic of ChinaAsiaEmerging TechnologiesMachine LearningRobotRoboticsHuazhong University o f Science and Technology
NETL
NSTL
