Robotics & Machine Learning Daily News2024,Issue(Nov.29) :110-111.

Studies from Southern University of Science and Technology (SUSTech) Update Curr ent Data on Robotics (Efficient Robot Manipulation via Reinforcement Learning wi th Dynamic Movement Primitives-Based Policy)

南方科技大学的研究(SUSTech)更新了机器人学的最新数据(通过基于动态运动原始策略的强化学习实现高效机器人操作)

Robotics & Machine Learning Daily News2024,Issue(Nov.29) :110-111.

Studies from Southern University of Science and Technology (SUSTech) Update Curr ent Data on Robotics (Efficient Robot Manipulation via Reinforcement Learning wi th Dynamic Movement Primitives-Based Policy)

南方科技大学的研究(SUSTech)更新了机器人学的最新数据(通过基于动态运动原始策略的强化学习实现高效机器人操作)

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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-调查人员发布关于机器人的新报道。根据新闻报道来自中华人民共和国深圳,由NewsRx记者报道,研究称,“加固”自主探索最优控制策略的学习(rl)已成为控制策略研究的一个重要课题用动态运动原语(DMPs)开发智能机器人有效地表达机器人轨迹。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on ro botics. According to news reporting originatingfrom Shenzhen, People’s Republic of China, by NewsRx correspondents, research stated, “Reinforcementlearning (R L) that autonomously explores optimal control policies has become a crucial dire ction fordeveloping intelligent robots while Dynamic Movement Primitives (DMPs) serve as a powerful tool forefficiently expressing robot trajectories.”

Key words

Southern University of Science and Techn ology (SUSTech)/Shenzhen/People’s Republic of China/Asia/Emerging Technologi es/Machine Learning/Reinforcement Learning/Robot/Robotics

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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