首页|Xinjiang University Details Findings in Robotics (An Active Olfaction Approach U sing Deep Reinforcement Learning for Indoor Attenuation Odor Source Localization )
Xinjiang University Details Findings in Robotics (An Active Olfaction Approach U sing Deep Reinforcement Learning for Indoor Attenuation Odor Source Localization )
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
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.
UrumqiPeople’s Republic of ChinaAsiaAlgorithmsCybersecurityEmerging TechnologiesMachine LearningReinforcem ent LearningRobotRoboticsXinjiang University
NETL
NSTL
