Using Robot Skills for Flexible Reprogramming of Pick Operations in Industrial Scenarios
Andersen, Rasmus S. ; Nalpantidis, Lazaros ; Krüger, Volker LU
; Madsen, Ole
and Moeslund, Thomas B.
(2014)
9th International Conference on Computer Vision Theory and Applications, VISAPP 2014
3.
- Abstract
- 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... (More)
- 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. (Less)
- Abstract (Swedish)
- Traditional robots used in manufacturing are very efficient for solving specific tasks that are repeated manytimes. The robots are, however, difficult to (re-)configure and (re-)program. This can often only be done byexpert robotic programmers, computer vision experts, etc., and it requires additionally lots of time. In thispaper we present and use a skill based framework for robotic programming. In this framework, we develop aflexible pick skill, that can easily be reprogrammed to solve new specific tasks, even by non-experts. Usingthe pick skill, a robot can detect rotational symmetric objects on tabletops and pick them up in a user-specifiedmanner. The programming itself is primarily done through kinesthetic teaching. We show that the... (More)
- Traditional robots used in manufacturing are very efficient for solving specific tasks that are repeated manytimes. The robots are, however, difficult to (re-)configure and (re-)program. This can often only be done byexpert robotic programmers, computer vision experts, etc., and it requires additionally lots of time. In thispaper we present and use a skill based framework for robotic programming. In this framework, we develop aflexible pick skill, that can easily be reprogrammed to solve new specific tasks, even by non-experts. Usingthe pick skill, a robot can detect rotational symmetric objects on tabletops and pick them up in a user-specifiedmanner. The programming itself is primarily done through kinesthetic teaching. We show that the skillhas robustness towards the location and shape of the object to pick, and that objects from a real industrialproduction line can be handled. Also, preliminary tests indicate that non-expert users can learn to use the skillafter only a short introduction. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/c09a60d5-4686-4db9-b78b-98a48a03eb0c
- author
- Andersen, Rasmus S.
; Nalpantidis, Lazaros
; Krüger, Volker
LU
; Madsen, Ole
and Moeslund, Thomas B.
- publishing date
- 2014
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Robot vision, robotic skills, industrial robots, tabletop object detector.
- host publication
- 2014 International Conference on Computer Vision Theory and Applications (VISAPP)
- volume
- 3
- pages
- 8 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 9th International Conference on Computer Vision Theory and Applications, VISAPP 2014
- conference location
- Lisbon, Portugal
- conference dates
- 2014-01-05 - 2014-01-08
- external identifiers
-
- scopus:84906903771
- ISBN
- 978-9-8975-8133-5
- project
- Robotics and Semantic Systems
- language
- English
- LU publication?
- no
- id
- c09a60d5-4686-4db9-b78b-98a48a03eb0c
- alternative location
- https://ieeexplore.ieee.org/document/7295147/
- date added to LUP
- 2019-05-16 21:30:38
- date last changed
- 2022-02-15 19:18:49
@inproceedings{c09a60d5-4686-4db9-b78b-98a48a03eb0c,
abstract = {{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.}},
author = {{Andersen, Rasmus S. and Nalpantidis, Lazaros and Krüger, Volker and Madsen, Ole and Moeslund, Thomas B.}},
booktitle = {{2014 International Conference on Computer Vision Theory and Applications (VISAPP)}},
isbn = {{978-9-8975-8133-5}},
keywords = {{Robot vision; robotic skills; industrial robots; tabletop object detector.}},
language = {{eng}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{Using Robot Skills for Flexible Reprogramming of Pick Operations in Industrial Scenarios}},
url = {{https://ieeexplore.ieee.org/document/7295147/}},
volume = {{3}},
year = {{2014}},
}