Robotics & Machine Learning Daily News2024,Issue(Sep.11) :27-28.

Findings on Robotics and Machine Learning Reported by Investigators at North Chi na University of Technology (Improved Multiverse Optimizer-based Anti-saturation Model Free Adaptive Control and Its Application To Manipulator Grasping Systems)

Robotics & Machine Learning Daily News2024,Issue(Sep.11) :27-28.

Findings on Robotics and Machine Learning Reported by Investigators at North Chi na University of Technology (Improved Multiverse Optimizer-based Anti-saturation Model Free Adaptive Control and Its Application To Manipulator Grasping Systems)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Investigators discuss new findings in Robotics an d Machine Learning. According to news originating from Beijing, People’s Republi c of China, by NewsRx correspondents, research stated, “To address the stable gr asping control issue in manipulator grasping systems, this manuscript proposes a n improved multiverse optimizer-based anti-saturation model-free adaptive contro l (IMVO-AS-MFAC) algorithm. Initially, the manuscript converts the manipulator g rasping system into an equivalent data model through dynamic linearization techn iques.”

Key words

Beijing/People’s Republic of China/Asia/Robotics and Machine Learning/Algorithms/Mathematics/North China University of Technology

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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