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Automatic Calibration of the Adaptive 3D Scanner-Based Robot Welding System.
Arko, Peter; Jezersek, Matija.
Affiliation
  • Arko P; Yaskawa Slovenija, Ribnica, Slovenia.
  • Jezersek M; Laboratory for Laser Techniques, Faculty of Mechanical Engineering, University of Ljubljana, Ljubljana, Slovenia.
Front Robot AI ; 9: 876717, 2022.
Article de En | MEDLINE | ID: mdl-35685620
ABSTRACT
An advanced automatic calibration procedure and its versatile usage in the context of the adaptive robot welding technology are presented. The 3D scanner-based robot welding system calibration is composed of the measurement of the reference plate and numerical optimization of the hand-eye and intrinsic parameters by minimizing the deviation between the measured and reference plate. The measurements of the reference plate are acquired from various robot poses (typically 15). The shape features of the reference plate are then detected, and finally, the calculation of hand-eye and intrinsic parameters is performed using Powell's optimization algorithm, where the merit function presents an average deviation between the measured and reference geometry. Validation experiments show appropriate system accuracy which is better than 0.06 mm perpendicular to the scanning direction. This calibration procedure's important features are complete automation and fast execution times (approximately 90 s). This enables its implementation into a regular daily robot self-maintenance and monitoring plan. The universal use of such a robot welding system is demonstrated in multi-layer heavy-duty welding of thick pipes on cast machined hollow parts and in precise laser welding of thin sheet metal parts.
Mots clés

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Type d'étude: Prognostic_studies Langue: En Journal: Front Robot AI Année: 2022 Type de document: Article Pays d'affiliation: Slovénie

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Type d'étude: Prognostic_studies Langue: En Journal: Front Robot AI Année: 2022 Type de document: Article Pays d'affiliation: Slovénie