Using Robot Skills for Flexible Reprogramming of Pick Operations in Industrial Scenarios

Publikation: Forskning - peer reviewKonferenceartikel i proceeding

Abstrakt

Traditional robots used in manufacturing are very efficient for solving specific tasks that are repeated many
times. The robots are, however, difficult to (re-)configure and (re-)program. This can often only be done by
expert robotic programmers, computer vision experts, etc., and it requires additionally lots of time. In this
paper we present and use a skill based framework for robotic programming. In this framework, we develop a
flexible pick skill, that can easily be reprogrammed to solve new specific tasks, even by non-experts. Using
the pick skill, a robot can detect rotational symmetric objects on tabletops and pick them up in a user-specified
manner. The programming itself is primarily done through kinesthetic teaching. We show that the skill
has robustness towards the location and shape of the object to pick, and that objects from a real industrial
production line can be handled. Also, preliminary tests indicate that non-expert users can learn to use the skill
after only a short introduction.
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Detaljer

Traditional robots used in manufacturing are very efficient for solving specific tasks that are repeated many
times. The robots are, however, difficult to (re-)configure and (re-)program. This can often only be done by
expert robotic programmers, computer vision experts, etc., and it requires additionally lots of time. In this
paper we present and use a skill based framework for robotic programming. In this framework, we develop a
flexible pick skill, that can easily be reprogrammed to solve new specific tasks, even by non-experts. Using
the pick skill, a robot can detect rotational symmetric objects on tabletops and pick them up in a user-specified
manner. The programming itself is primarily done through kinesthetic teaching. We show that the skill
has robustness towards the location and shape of the object to pick, and that objects from a real industrial
production line can be handled. Also, preliminary tests indicate that non-expert users can learn to use the skill
after only a short introduction.
OriginalsprogEngelsk
TitelVISAPP 2014 - Proceedings of the 9th International Conference on Computer Vision Theory and Applications
Antal sider8
Vol/bind3
UdgiverSCITEPRESS Digital Library
Publikationsdato1 jan. 2014
Sider678-685
ISBN (trykt)978-989758009-3
StatusUdgivet - 1 jan. 2014
Begivenhed - Lisbon, Portugal

Konference

Konference International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
LandPortugal
ByLisbon
Periode05/01/201408/01/2014

    Emneord

  • Robot vision, robotic skills, industrial robots, tabletop object detector.
ID: 145625751