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Conference Papers Year : 2012

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

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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.
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Dates and versions

hal-00671209 , version 1 (16-05-2012)

Identifiers

  • HAL Id : hal-00671209 , version 1

Cite

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