Teachless teach-repeat: Toward Vision-Based Programming of Industrial Robots

Abstract : Modern programming of industrial robots is often based on the teach-repeat paradigm: a human operator places the robot in many key positions, for teaching its task. Then the robot can repeat a path defined by these key positions. This paper proposes a vision-based approach for the automation of the teach stage. The approach relies on a constant autocalibration of the system. Therefore, the only requirement is a precise geometrical description of the part to process. The realism of the approach is demonstrated through the emulation of a glue application process with an industrial robot. Results in terms of precision are very promising.
Type de document :
Communication dans un congrès
IEEE. IEEE International Conference on Robotics and Automation, May 2012, St Paul, Minnesota, United States. 2012
Liste complète des métadonnées

Littérature citée [14 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-00671209
Contributeur : Mathias Perrollaz <>
Soumis le : mercredi 16 mai 2012 - 07:00:08
Dernière modification le : mercredi 11 avril 2018 - 01:54:53
Document(s) archivé(s) le : mercredi 14 décembre 2016 - 06:37:17

Fichier

ICRA2012_teachRepeat_Final.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-00671209, version 1

Citation

Mathias Perrollaz, Sami Khorbotly, Amber Cool, John-David Yoder, Eric Baumgartner. Teachless teach-repeat: Toward Vision-Based Programming of Industrial Robots. IEEE. IEEE International Conference on Robotics and Automation, May 2012, St Paul, Minnesota, United States. 2012. 〈hal-00671209〉

Partager

Métriques

Consultations de la notice

423

Téléchargements de fichiers

387