Overview
- 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 positioning accuracy
- Offers a publicly available dataset to help researchers from other fields conduct calibration experiments
Part of the book series: SpringerBriefs in Computer Science (BRIEFSCOMPUTER)
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Table of contents (8 chapters)
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Front Matter
Keywords
About this book
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 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.
Authors and Affiliations
About the authors
Dr. Xin Luo is a professor with the College of Computer and Information Science, Southwest University. His current research interests include Machine Intelligence, Big Data, and Cloud Computing. He has published over 200 papers (including over 87 IEEE TRANSACTIONS papers, 17 highly cited papers of ESI) in the above areas. His Google Scholar cited is more than 6300, and H-Index is 48. He has 35 authorized national invention patents. He was the Pioneer Hundred Talents Program of Chinese Academy of Sciences in 2016, the Advanced Support of the Pioneer Hundred Talents Program of Chinese Academy of Sciences in 2018, and the National High-Level Talents Special Support Program in 2020. He won the First Prize of Chongqing Natural Science Award (2019, No. 1), the First Prize of Wu Wenjun AI Science and Technology Progress Award (2018, No. 3), and the First Prize of Chongqing Science and Technology Progress Award (2018, No. 2). He serves as an associate editor for the IEEE/CAA Journal of Automatica Sinica and IEEE Transactions on Neural Networks and Learning Systems. He has received the Outstanding Associate Editor Award from IEEE/CAA Journal of Automatica Sinica in 2020.
Dr. Zhibin Li is currently studying for the PhD degree in computer science from Chongqing University of Posts and Telecommunications united training by the Chongqing institute of green and intelligent technology, Chinese academy of sciences, Chongqing, China. His research interests include robot calibration, big data analysis and algorithm design for large-scale data applications. He has published over six SCI/EI papers, including top journals and conferences like IEEE TNNLS, JAS, RAL, and TCASII in the computer field.
Dr. Long Jin joined the School of Information Science and Engineering, Lanzhou University, as a professor of computer science and engineering. He is currently serving as an editor for the Chinese Association for Artificial Intelligence (CAAI) Transactions on Intelligence Technology. His current research interests include neural networks, robotics, optimization, and intelligent computing.
Dr. Shuai Li is an associate professor (Reader) at University of Oulu, Oulu, Finland. His research interests include robot manipulation and impedance control, multi-robot coordination, and articulated robot calibration.
Bibliographic Information
Book Title: Robot Control and Calibration
Book Subtitle: Innovative Control Schemes and Calibration Algorithms
Authors: Xin Luo, Zhibin Li, Long Jin, Shuai Li
Series Title: SpringerBriefs in Computer Science
DOI: https://doi.org/10.1007/978-981-99-5766-8
Publisher: Springer Singapore
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023
Softcover ISBN: 978-981-99-5765-1Published: 26 September 2023
eBook ISBN: 978-981-99-5766-8Published: 25 September 2023
Series ISSN: 2191-5768
Series E-ISSN: 2191-5776
Edition Number: 1
Number of Pages: XI, 125
Number of Illustrations: 1 b/w illustrations
Topics: Robotics, Data Structures and Information Theory, Artificial Intelligence, Robotics and Automation