Robotics & Machine Learning Daily News2024,Issue(Apr.2) :97-97.

Reports Summarize Robotics Study Results from Sun Yat-sen University (Homography -based Visual Servoing of Eye-in-hand Robots With Exact Depth Estimation)

Robotics & Machine Learning Daily News2024,Issue(Apr.2) :97-97.

Reports Summarize Robotics Study Results from Sun Yat-sen University (Homography -based Visual Servoing of Eye-in-hand Robots With Exact Depth Estimation)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on Ro botics. According to news reporting out of Shenzhen, People's Republic of China, by NewsRx editors, research stated, "Visual servoing can effectively control ro bots using visual feedback to improve their intelligence and reliability. For a feature point detected by a monocular camera, the time-varying depth appearing n onlinearly in the Jacobian matrix is difficult to be measured without the prior geometry knowledge of the observed object." Financial supporters for this research include Fundamental Research Funds for th e Central Universities, Sun Yat-sen University, China, Guangdong Provincial Pear l River Talents Program of China. Our news journalists obtained a quote from the research from Sun Yat-sen Univers ity, "Therefore, the depth of the feature point is one of the major uncertain pa rameters in visual servoing. Considering unknown Cartesian feature positions, th is article presents a robot dynamics-based homography-based visual servoing (HBV S) controller for the 3-D pose regulation of eye-in-hand robot arms with monocul ar cameras. The uncertain depth is represented into a linear form of its Cartesi an feature position, and a composite learning law is applied to estimate positio n parameters accurately, resulting in exact depth estimation. Compared to existi ng adaptive HBVS methods, the distinctive feature of the proposed method is that it is a dynamics-based design and guarantees exact depth estimation under a muc h weaker condition termed interval excitation compared to persistent excitation. "

Key words

Shenzhen/People's Republic of China/As ia/Emerging Technologies/Machine Learning/Nano-robot/Robot/Robotics/Sun Ya t-sen University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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