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An Advancing Ensemble with Diversified Algorithms for Robot Arm Calibration

Zhibin Li, Shuai Li, Xin Luo

Year
2022
Citations
2
Access
Open access

Abstract

Recently, industrial robots plays a significant role in intelligent manufacturing. Hence, it is an urgent issue to ensure the robot with the high positioning precision. To address this hot issue, a novel calibration method based on an powerful ensemble with various algorithms is proposed. This paper has two ideas: a) developing eight calibration methods to identify the kinematic parameter errors; 2) establishing an effective ensemble to search calibrated kinematic parameters. Enough experimental results show that this ensemble can achieve: 1) higher calibration accuracy for the robot; 2) model diversity; 3) strong generalization ability.

Keywords

CalibrationGeneralizationRobotComputer scienceRobot calibrationKinematicsEnsemble learningArtificial intelligenceGeneralization errorAlgorithm

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