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Titlebook: Robot Control and Calibration; Innovative Control S Xin Luo,Zhibin Li,Shuai Li Book 2023 The Editor(s) (if applicable) and The Author(s), u

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發(fā)表于 2025-3-21 17:01:42 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Robot Control and Calibration
副標題Innovative Control S
編輯Xin Luo,Zhibin Li,Shuai Li
視頻videohttp://file.papertrans.cn/832/831037/831037.mp4
概述Shows how robot calibration and control technology can achieve high scalability in real industrial applications.Proposes control schemes and calibration algorithms that can effectively improve robot p
叢書名稱SpringerBriefs in Computer Science
圖書封面Titlebook: Robot Control and Calibration; Innovative Control S Xin Luo,Zhibin Li,Shuai Li Book 2023 The Editor(s) (if applicable) and The Author(s), u
描述.This book mainly shows readers how to calibrate and control robots. In this regard, it proposes three control schemes: an error-summation enhanced Newton algorithm for model predictive control; RNN for solving perturbed time-varying underdetermined linear systems; and a new joint-drift-free scheme aided with projected ZNN, which can effectively improve robot control accuracy. Moreover, the book develops four advanced algorithms for robot calibration – Levenberg-Marquarelt with diversified regularizations; improved covariance matrix adaptive evolution strategy; quadratic interpolated beetle antennae search algorithm; and a novel variable step-size Levenberg-Marquardt algorithm – which can effectively enhance robot positioning accuracy...In addition, it is exceedingly difficult for experts in other fields to conduct robot arm calibration studies without calibration data. Thus, this book provides a publicly available dataset to assist researchers from other fields in conductingcalibration experiments and validating their ideas. The book also discusses six regularization schemes based on its robot error models, i.e., L1, L2, dropout, elastic, log, and swish. Robots’ positioning accura
出版日期Book 2023
關(guān)鍵詞Recurrent neural network; Robot kinematic model; Robot control; Robot calibration; Evolutionary computin
版次1
doihttps://doi.org/10.1007/978-981-99-5766-8
isbn_softcover978-981-99-5765-1
isbn_ebook978-981-99-5766-8Series ISSN 2191-5768 Series E-ISSN 2191-5776
issn_series 2191-5768
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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發(fā)表于 2025-3-21 21:11:53 | 只看該作者
A Projected Zeroing Neural Network Model for the Motion Generation and Control,s presented in Sect. .. In Sect. ., we study the feedback-considered scheme of the robot. Neural network design is briefly discussed in Sect. .. The experiments are given in Sect. .. Lastly, the conclusions and future work are concluded in Sect. ..
板凳
發(fā)表于 2025-3-22 03:55:44 | 只看該作者
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發(fā)表于 2025-3-22 15:00:57 | 只看該作者
A Novel Model Predictive Control Scheme Based on an Improved Newton Algorithm,leration norm. The research background of this work is discussed in Sect. ., Sect. . gives the problem description, Sect. . provides the theoretical verifications, the simulation results are presented in Sect. .. Lastly, the conclusions are summarized in Sect. ..
7#
發(fā)表于 2025-3-22 18:43:43 | 只看該作者
A Novel Recurrent Neural Network for Robot Control,apter, a new recurrent neural network (RNN) is proposed to deal with time-varying underdetermined linear systems with disturbances, thereby achieving better control results. The related background of the underdetermined linear system is described in Sect. .. In Sect. ., we introduce the problem desc
8#
發(fā)表于 2025-3-22 23:38:08 | 只看該作者
A Projected Zeroing Neural Network Model for the Motion Generation and Control, for redundant robot control, which achieves high superiority and efficiency. The research background about robot control by zeroing neural networks is presented in Sect. .. In Sect. ., we study the feedback-considered scheme of the robot. Neural network design is briefly discussed in Sect. .. The e
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