Studies from University of Michigan Have Provided New Data on Robotics (Constrai ning Gaussian Process Implicit Surfaces for Robot Manipulation Via Dataset Refin emen)
Studies from University of Michigan Have Provided New Data on Robotics (Constrai ning Gaussian Process Implicit Surfaces for Robot Manipulation Via Dataset Refin emen)
密歇根大学的研究提供了新的数据机器人学(高斯过程隐式曲面的约束基于数据集重构的机器人操作
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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-机器人的研究发现在一份新的报告中被使用。据新闻报道来自Mic Higan Ann Arbor的报道，由NewsRx记者撰写，研究称，"基于模型的报道"由于未建模的障碍，控制在部分可观察的环境中面临基本挑战。我们提出了一种在线学习和优化方法，以识别和避免在线未观察到的障碍。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Research findings on Robotics are disc ussed in a new report. According to newsreporting originating in Ann Arbor, Mic higan, by NewsRx journalists, research stated, “Model-basedcontrol faces fundam ental challenges in partially-observable environments due to unmodeled obstacles .We propose an online learning and optimization method to identify and avoid un observed obstacles online.”
Key words
Ann Arbor/Michigan/United States/Nort h and Central America/Emerging Technologies/Gaussian Processes/Machine Learni ng/Robot/Robotics/University of Michigan
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