Findings on Robotics Reported by Investigators at University of Freiburg (The Ar t of Imitation: Learning Long-horizon Manipulation Tasks From Few Demonstrations )

弗赖堡大学研究人员报告的机器人学发现（模仿的艺术：从少数演示中学习长视野操作任务）

Robotics & Machine Learning Daily News2024，Issue(Dec.5) ：30-30.

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Findings on Robotics Reported by Investigators at University of Freiburg (The Ar t of Imitation: Learning Long-horizon Manipulation Tasks From Few Demonstrations )

弗赖堡大学研究人员报告的机器人学发现（模仿的艺术：从少数演示中学习长视野操作任务）

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摘要

由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-一项关于机器人的新研究现已问世。据弗莱堡的新闻报道，德国，由NewsRx记者报道，研究人员称，"任务参数化高斯混合模型(TPGMM)是学习以对象为中心的机器人操作任务的有效示例方法。然而，在野外应用TP-GMM有几个公开的挑战。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – A new study on Robotics is now availab le. According to news reporting from Freiburg,Germany, by NewsRx journalists, r esearch stated, “Task Parametrized Gaussian Mixture Models (TPGMM)are a sample -efficient method for learning object-centric robot manipulation tasks. However, thereare several open challenges to applying TP-GMMs in the wild.”

Key words

Freiburg/Germany/Europe/Emerging Tech nologies/Machine Learning/Robot/Robotics/University of Freiburg

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出版年

2024

Robotics & Machine Learning Daily News

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