Novel Evolutionary Computing Algorithms for Robot Calibration

Xin Luo; Zhibin Li; Long Jin; Shuai Li

doi:10.1007/978-981-99-5766-8_6

Novel Evolutionary Computing Algorithms for Robot Calibration

Xin Luo^*, Zhibin Li, Long Jin, Shuai Li

^*Corresponding author for this work

BA56 Cognitive production industry

Research output: Chapter in Book/Report/Conference proceeding › Chapter or book article › Scientific › peer-review

Abstract

This chapter discusses an improved covariance matrix adaptation evolution strategy and a quadratic interpolated beetle antennae search algorithm for robot calibration. Firstly, Section 6.1 introduces the research motivation for robot calibration. In Sect. 6.2, we present the learning rule of an extended Kalman filter, an improved covariance matrix adaptive evolution strategy and a quadratic interpolated beetle antennae search algorithm. In addition, Section 6.3 provides the experiments for the developed novel evolutionary computing algorithms. And finally, Section 6.4. concludes this chapter.

Original language	English
Title of host publication	Robot Control and Calibration
Subtitle of host publication	Innovative Control Schemes and Calibration Algorithms
Place of Publication	Singapore
Publisher	Springer
Pages	91-109
ISBN (Electronic)	978-981-99-5766-8
ISBN (Print)	978-981-99-5765-1
DOIs	https://doi.org/10.1007/978-981-99-5766-8_6
Publication status	Published - 2023
MoE publication type	A3 Part of a book or another research book

Publication series

Series	SpringerBriefs in Computer Science
Volume	Part F1465
ISSN	2191-5768

Keywords

Extended Kalman filter
Improved covariance matrix adaptation evolution strategy
Noise
Quadratic interpolated beetle antennae search algorithm
RobotCali

Access to Document

10.1007/978-981-99-5766-8_6

Cite this

@inbook{e72f2938571a40abbf2fde2282ff52a9,

title = "Novel Evolutionary Computing Algorithms for Robot Calibration",

abstract = "This chapter discusses an improved covariance matrix adaptation evolution strategy and a quadratic interpolated beetle antennae search algorithm for robot calibration. Firstly, Section 6.1 introduces the research motivation for robot calibration. In Sect. 6.2, we present the learning rule of an extended Kalman filter, an improved covariance matrix adaptive evolution strategy and a quadratic interpolated beetle antennae search algorithm. In addition, Section 6.3 provides the experiments for the developed novel evolutionary computing algorithms. And finally, Section 6.4. concludes this chapter.",

keywords = "Extended Kalman filter, Improved covariance matrix adaptation evolution strategy, Noise, Quadratic interpolated beetle antennae search algorithm, RobotCali",

author = "Xin Luo and Zhibin Li and Long Jin and Shuai Li",

note = "Shuai Li on externaali",

year = "2023",

doi = "10.1007/978-981-99-5766-8_6",

language = "English",

isbn = "978-981-99-5765-1",

series = "SpringerBriefs in Computer Science",

publisher = "Springer",

pages = "91--109",

booktitle = "Robot Control and Calibration",

address = "Germany",

}

Novel Evolutionary Computing Algorithms for Robot Calibration. / Luo, Xin; Li, Zhibin; Jin, Long et al.
Robot Control and Calibration: Innovative Control Schemes and Calibration Algorithms. Singapore: Springer, 2023. p. 91-109 (SpringerBriefs in Computer Science, Vol. Part F1465).

Research output: Chapter in Book/Report/Conference proceeding › Chapter or book article › Scientific › peer-review

TY - CHAP

T1 - Novel Evolutionary Computing Algorithms for Robot Calibration

AU - Luo, Xin

AU - Li, Zhibin

AU - Jin, Long

AU - Li, Shuai

N1 - Shuai Li on externaali

PY - 2023

Y1 - 2023

N2 - This chapter discusses an improved covariance matrix adaptation evolution strategy and a quadratic interpolated beetle antennae search algorithm for robot calibration. Firstly, Section 6.1 introduces the research motivation for robot calibration. In Sect. 6.2, we present the learning rule of an extended Kalman filter, an improved covariance matrix adaptive evolution strategy and a quadratic interpolated beetle antennae search algorithm. In addition, Section 6.3 provides the experiments for the developed novel evolutionary computing algorithms. And finally, Section 6.4. concludes this chapter.

AB - This chapter discusses an improved covariance matrix adaptation evolution strategy and a quadratic interpolated beetle antennae search algorithm for robot calibration. Firstly, Section 6.1 introduces the research motivation for robot calibration. In Sect. 6.2, we present the learning rule of an extended Kalman filter, an improved covariance matrix adaptive evolution strategy and a quadratic interpolated beetle antennae search algorithm. In addition, Section 6.3 provides the experiments for the developed novel evolutionary computing algorithms. And finally, Section 6.4. concludes this chapter.

KW - Extended Kalman filter

KW - Improved covariance matrix adaptation evolution strategy

KW - Noise

KW - Quadratic interpolated beetle antennae search algorithm

KW - RobotCali

UR - http://www.scopus.com/inward/record.url?scp=85172720795&partnerID=8YFLogxK

U2 - 10.1007/978-981-99-5766-8_6

DO - 10.1007/978-981-99-5766-8_6

M3 - Chapter or book article

AN - SCOPUS:85172720795

SN - 978-981-99-5765-1

T3 - SpringerBriefs in Computer Science

SP - 91

EP - 109

BT - Robot Control and Calibration

PB - Springer

CY - Singapore

ER -

Novel Evolutionary Computing Algorithms for Robot Calibration

Abstract

Publication series

Keywords

Access to Document

Other files and links

Fingerprint

Robot Control and Calibration: Innovative Control Schemes and Calibration Algorithms

Cite this