Robotics & Machine Learning Daily News2024,Issue(Jun.28) :60-60.

Xinjiang University Details Findings in Robotics (An Active Olfaction Approach U sing Deep Reinforcement Learning for Indoor Attenuation Odor Source Localization )

新疆大学详细介绍了机器人学的研究成果(一种利用深度强化学习进行室内衰减气味源定位的主动嗅觉方法)

Robotics & Machine Learning Daily News2024,Issue(Jun.28) :60-60.

Xinjiang University Details Findings in Robotics (An Active Olfaction Approach U sing Deep Reinforcement Learning for Indoor Attenuation Odor Source Localization )

新疆大学详细介绍了机器人学的研究成果(一种利用深度强化学习进行室内衰减气味源定位的主动嗅觉方法)

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摘要

机器人与机器学习每日新闻的一名新闻记者兼工作人员新闻编辑在一份新的报告中讨论了机器人的研究结果。根据NewsRx记者从乌鲁木齐发来的消息,研究表明:“气味源(如有毒气味源)的定位是环境和人类社会安全的重要任务,传统的机器人定位方法对环境变化敏感,导致动态环境和复杂场景下定位性能下降。”国家自然科学基金(NSFC)、新疆维吾尔自治区自然科学基金。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Research findings on Robotics are discussed in a new report. According to news originating from Urumqi, People’s Republic of Chin a, by NewsRx correspondents, research stated, “The localization of odor sources (e.g., poisonous odor sources) is an important task for the security of the envi ronment and human society. Traditional robot localization methods are sensitive to environmental changes, leading to localization performance degradation in dyn amic environments and complex scenes.” Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Natural Science Foundation of Xinjiang Uygur Autonomous Regi on.

Key words

Urumqi/People’s Republic of China/Asia/Algorithms/Cybersecurity/Emerging Technologies/Machine Learning/Reinforcem ent Learning/Robot/Robotics/Xinjiang University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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