LEADER 03492nam 2200505 450 001 996550550903316 005 20231013234441.0 010 $a981-9957-66-4 024 7 $a10.1007/978-981-99-5766-8 035 $a(CKB)28305456600041 035 $a(MiAaPQ)EBC30754251 035 $a(Au-PeEL)EBL30754251 035 $a(DE-He213)978-981-99-5766-8 035 $a(PPN)272736341 035 $a(EXLCZ)9928305456600041 100 $a20231013d2023 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aRobot Control and Calibration $eInnovative Control Schemes and Calibration Algorithms /$fXin Luo [and three others] 205 $aFirst edition. 210 1$aSingapore :$cSpringer Nature Singapore Pte Ltd.,$d[2023] 210 4$dİ2023 215 $a1 online resource (132 pages) 225 1 $aSpringerBriefs in Computer Science Series 311 $a9789819957651 320 $aIncludes bibliographical references. 327 $aChapter 1. Introduction -- Chapter 2. A Novel Model Predictive Control Scheme Based on an Improved Newton Algorithm -- Chapter 3. A Novel Recurrent Neural Network for Robot Control -- Chapter 4. A Projected Zeroing Neural Network Model for the Motion Generation and Control -- Chapter 5. A Regularization Ensemble Based on Levenberg?Marquardt Algorithm for Robot Calibration -- Chapter 6. Novel Evolutionary Computing Algorithms for Robot Calibration -- Chapter 7. A Highly Accurate Calibrator Based on a Novel Variable Step-Size Levenberg-Marquardt Algorithm -- Chapter 8. Conclusion and Future Work. 330 $aThis book mainly shows readers how to calibrate and control robots. In this regard, it proposes three control schemes: an error-summation enhanced Newton algorithm for model predictive control; RNN for solving perturbed time-varying underdetermined linear systems; and a new joint-drift-free scheme aided with projected ZNN, which can effectively improve robot control accuracy. Moreover, the book develops four advanced algorithms for robot calibration ? Levenberg-Marquarelt with diversified regularizations; improved covariance matrix adaptive evolution strategy; quadratic interpolated beetle antennae search algorithm; and a novel variable step-size Levenberg-Marquardt algorithm ? which can effectively enhance robot positioning accuracy. In addition, it is exceedingly difficult for experts in other fields to conduct robot arm calibration studies without calibration data. Thus, this book provides a publicly available dataset to assist researchers from other fields in conducting calibration experiments and validating their ideas. The book also discusses six regularization schemes based on its robot error models, i.e., L1, L2, dropout, elastic, log, and swish. Robots? positioning accuracy is significantly improved after calibration. Using the control and calibration methods developed here, readers will be ready to conduct their own research and experiments. 410 0$aSpringerBriefs in computer science. 606 $aRobots$vCalibration 606 $aRobots$xControl systems 615 0$aRobots 615 0$aRobots$xControl systems. 676 $a629.892 700 $aLuo$b Xin$f1963-$01430953 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996550550903316 996 $aRobot Control and Calibration$93571241 997 $aUNISA