@article{1481180,
      recid = {1481180},
      author = {Luo, Xin. and Li, Zhibin. and Jin, Long, and Li, Shuai,},
      title = {Robot control and calibration : innovative control schemes  and calibration /},
      publisher = {Springer,},
      address = {Singapore :},
      pages = {1 online resource},
      year = {2023},
      abstract = {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 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.},
      url = {http://library.usi.edu/record/1481180},
      doi = {https://doi.org/10.1007/978-981-99-5766-8},
}