Robotics & Machine Learning Daily News2024,Issue(Jun.7) :171-174.

Patent Issued for Robotic learning of assembly tasks using augmented reality (US PTO 11989843)

使用增强现实的机器人装配任务学习专利(美国专利商标局11989843)

Robotics & Machine Learning Daily News2024,Issue(Jun.7) :171-174.

Patent Issued for Robotic learning of assembly tasks using augmented reality (US PTO 11989843)

使用增强现实的机器人装配任务学习专利(美国专利商标局11989843)

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摘要

Robotics&Machine Learning Daily News的新闻记者兼工作人员新闻编辑-发明者Schoisengeie R,Adrian(维也纳,AT),Zhou,Kai(Wiener Neudorf,AT)于2022年6月22日提交的专利,根据NewsRx记者来自弗吉尼亚州亚历山大市的新闻报道,于2024年5月21日在网上专利号11989843转让给Snap Inc.。(美国加利福尼亚州圣莫尼卡)。新闻编辑从发明者提供的背景信息中获得了以下引文:“通过演示(PbD),可以使用编程来教授机器人新技能。操作员通过物理演示任务来教授机器人:操作员通过一系列顺序配置(例如,位置,抓手,物理物体)手动移动机器人的部件(例如,手臂,抓手,物理物体),演示任务的方向。在物理环境中放置多个传感器以捕获一组顺序配置离子。然而,一些机器人和物理物体可能太大、太重、太脆弱或对操作员来说太危险。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A patent by the inventors Schoisengeie r, Adrian (Vienna, AT), Zhou, Kai (Wiener Neudorf, AT), filed on June 22, 2022, was published online on May 21, 2024, according to news reporting originating fr om Alexandria, Virginia, by NewsRx correspondents. Patent number 11989843 is assigned to Snap Inc. (Santa Monica, California, Unite d States). The following quote was obtained by the news editors from the background informa tion supplied by the inventors: “Robots can be taught new skills using programmi ng by demonstration (PbD). An operator teaches a robot by physically demonstrati ng a task: the operator manually moves components (e.g., arms, gripper, physical objects) of the robot through a set of sequential configurations (e.g., positio n, orientation of the components) to demonstrate the task. Multiple sensors are disposed in the physical environment to capture the set of sequential configurat ions. However, some robots and physical objects can be too large, too heavy, too fragile, or too dangerous for the operator.

Key words

Business/Emerging Technologies/Machine Learning/Nanorobot/Robot/Robotics/Robots/Snap Inc

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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