首页|Researchers at Chinese Academy of Sciences Target Robotics (Kalman Filter-based One-shot Sim-to-real Transfer Learning)
Researchers at Chinese Academy of Sciences Target Robotics (Kalman Filter-based One-shot Sim-to-real Transfer Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Fresh data on Robotics are presented in a new report. According to news reportingoriginating from Shenyang, People’s Republic of China, by NewsRx correspondents, research stated, “Deepreinforcementlearning algorithms offer a promising method for industrial robots to tackle unstructured andcomplex scenarios that are difficult to model. However, due to constraints related to equipment lifespanand safety requirements, acquiring a number of samples directly from the physical environment is ofteninfeasible.”
ShenyangPeople’s Republic of ChinaAsiaEmerging TechnologiesMachine LearningNano-robotRoboticsChinese Academy of Sciences
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