ICRA 2012 Paper Abstract

Close

Paper TuA210.2

Perrollaz, Mathias (INRIA Grenoble - Rhône-Alpes), Khorbotly, Sami (Ohio Northern University), Cool, Amber (Ohio Northern University), Yoder, John David (Ohio Northern University), Baumgartner, Eric (Ohio Northern University)

Teachless Teach-Repeat: Toward Vision-Based Programming of Industrial Robots

Scheduled for presentation during the Interactive Session "Interactive Session TuA-2" (TuA210), Tuesday, May 15, 2012, 09:00−09:30, Ballroom D

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on June 22, 2018

Keywords Computer Vision for Robotics and Automation, 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 auto- calibration 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.

 

 

Technical Content © IEEE Robotics & Automation Society

This site is protected by copyright and trademark laws under US and International law.
All rights reserved. © 2002-2018 PaperCept, Inc.
Page generated 2018-06-22  21:16:18 PST  Terms of use