Novel Evolutionary Computing Algorithms for Robot Calibration

Xin Luo, Zhibin Li, Long Jin, Shuai Li

Research output: Chapter in Book/Report/Conference proceedingChapter or book articleScientificpeer-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 languageEnglish
Title of host publicationRobot Control and Calibration
Subtitle of host publicationInnovative Control Schemes and Calibration Algorithms
Place of PublicationSingapore
PublisherSpringer
Pages91-109
ISBN (Electronic)978-981-99-5766-8
ISBN (Print)978-981-99-5765-1
DOIs
Publication statusPublished - 2023
MoE publication typeA3 Part of a book or another research book

Publication series

SeriesSpringerBriefs in Computer Science
VolumePart F1465
ISSN2191-5768

Keywords

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

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