Robotics & Machine Learning Daily News2024,Issue(Jun.28) :14-15.

Study Data from University of South Carolina Update Knowledge of Robotics (Plann ing To Chronicle: Optimal Policies for Narrative Observation of Unpredictable Ev ents)

南卡罗来纳大学的研究数据更新机器人知识(计划编年史:不可预测事件叙事观察的最佳策略)

Robotics & Machine Learning Daily News2024,Issue(Jun.28) :14-15.

Study Data from University of South Carolina Update Knowledge of Robotics (Plann ing To Chronicle: Optimal Policies for Narrative Observation of Unpredictable Ev ents)

南卡罗来纳大学的研究数据更新机器人知识(计划编年史:不可预测事件叙事观察的最佳策略)

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摘要

由一名新闻记者兼机器人与机器学习每日新闻的工作人员新闻编辑-一项关于机器人的新研究现在可以获得。根据NewsRx记者在南卡罗来纳州哥伦比亚的新闻报道,Resea Rch说:“一类重要的应用需要机器人仔细检查、监视或记录不确定的时间扩展过程的演变。这种情况导致了一系列有趣的主动感知问题,这些问题可以被描述为规划问题,其中机器人在看到的东西上受到限制,因此必须,选择关注什么。这项研究的财政支持来自国家科学基金会(NSF)。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – A new study on Robotics is now available. Accordi ng to news reporting from Columbia, South Carolina, by NewsRx journalists, resea rch stated, “One important class of applications entails a robot scrutinizing, m onitoring, or recording the evolution of an uncertain time-extended process. Thi s sort of situation leads to an interesting family of active perception problems that can be cast as planning problems in which the robot is limited in what it sees and must, thus, choose what to pay attention to.” Financial support for this research came from National Science Foundation (NSF).

Key words

Columbia/South Carolina/United States/North and Central America/Algorithms/Emerging Technologies/Machine Learning/Robot/Robotics/University of South Carolina

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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