摘要
由一名新闻记者兼机器人与机器学习每日新闻编辑-调查人员讨论机器人学的新发现。根据NewsRx Cor的受访者来自新加坡的新闻报道，研究表明：“本文提出了一种基于概率密度的机器人操作器工作空间学习-演示(LfD)方法，该方法命名为概率信息运动原语(PRIMP)，它描述了末端执行器轨迹在包括位置和方向的6-D WOR空间中的概率分布。”这项研究的财政支持来自新加坡国立大学初创公司。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in Robotics. According to news originating from Singapore, Singapore, by NewsRx cor respondents, research stated, “This article proposes a Learning-from- Demonstrati on (LfD) method using probability densities on the workspaces of robot manipulat ors. The method, named PRobabilistically-Informed Motion Primitives (PRIMP), lea rns the probability distribution of the end effector trajectories in the 6-D wor kspace that includes both positions and orientations.” Financial support for this research came from NUS Startup.
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