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Gesture-Based Extraction of Robot Skill Parameters for Intuitive Robot Programming

Pedersen, Mikkel Rath and Krüger, Volker LU orcid (2015) In Journal of Intelligent and Robotic Systems: Theory and Applications 80. p.149-163
Abstract
Despite a lot of research in the field, only very little experience exists with Teaching by Demonstration (TbD) in actual industrial use cases. In the factory of the future, it is necessary to rapidly reprogram flexible mobile manipulators to perform new tasks, when the need arises, for which a working system capable of TbD would be ideal. Contrary to current TbD approaches, that generally aim to recognize both action and where it is applied, we propose a division of labor, where the operator manually specifies the action the robot should perform, while gestures are used for specifying the relevant action parameter (e.g. on which object to apply the action). Using this two-step method has the advantages that there is no uncertainty of... (More)
Despite a lot of research in the field, only very little experience exists with Teaching by Demonstration (TbD) in actual industrial use cases. In the factory of the future, it is necessary to rapidly reprogram flexible mobile manipulators to perform new tasks, when the need arises, for which a working system capable of TbD would be ideal. Contrary to current TbD approaches, that generally aim to recognize both action and where it is applied, we propose a division of labor, where the operator manually specifies the action the robot should perform, while gestures are used for specifying the relevant action parameter (e.g. on which object to apply the action). Using this two-step method has the advantages that there is no uncertainty of which action the robot will perform, it takes into account that the environment changes, so objects do not need to be at predefined locations, and the parameter specification is possible even for inexperienced users. Experiments with 24 people in 3 different environments verify that it is indeed intuitive, even for a robotics novice, to program a mobile manipulator using this method. (Less)
Abstract (Swedish)
Despite a lot of research in the field, only very little experience exists with Teaching by Demonstration (TbD) in actual industrial use cases. In the factory of the future, it is necessary to rapidly reprogram flexible mobile manipulators to perform new tasks, when the need arises, for which a working system capable of TbD would be ideal. Contrary to current TbD approaches, that generally aim to recognize both action and where it is applied, we propose a division of labor, where the operator manually specifies the action the robot should perform, while gestures are used for specifying the relevant action parameter (e.g. on which object to apply the action). Using this two-step method has the advantages that there is no uncertainty of... (More)
Despite a lot of research in the field, only very little experience exists with Teaching by Demonstration (TbD) in actual industrial use cases. In the factory of the future, it is necessary to rapidly reprogram flexible mobile manipulators to perform new tasks, when the need arises, for which a working system capable of TbD would be ideal. Contrary to current TbD approaches, that generally aim to recognize both action and where it is applied, we propose a division of labor, where the operator manually specifies the action the robot should perform, while gestures are used for specifying the relevant action parameter (e.g. on which object to apply the action). Using this two-step method has the advantages that there is no uncertainty of which action the robot will perform, it takes into account that the environment changes, so objects do not need to be at predefined locations, and the parameter specification is possible even for inexperienced users. Experiments with 24 people in 3 different environments verify that it is indeed intuitive, even for a robotics novice, to program a mobile manipulator using this method. (Less)
Please use this url to cite or link to this publication:
author
and
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Industrial robots, Gesture recognition, Teaching by Demonstration, robot skills
in
Journal of Intelligent and Robotic Systems: Theory and Applications
volume
80
pages
15 pages
publisher
Springer
external identifiers
  • scopus:84953348846
ISSN
0921-0296
DOI
10.1007/s10846-015-0219-x
language
English
LU publication?
no
id
7c6567b6-c76c-4352-98f8-b0609f8805a6
date added to LUP
2019-05-16 21:24:28
date last changed
2022-03-10 03:27:02
@article{7c6567b6-c76c-4352-98f8-b0609f8805a6,
  abstract     = {{Despite a lot of research in the field, only very little experience exists with Teaching by Demonstration (TbD) in actual industrial use cases. In the factory of the future, it is necessary to rapidly reprogram flexible mobile manipulators to perform new tasks, when the need arises, for which a working system capable of TbD would be ideal. Contrary to current TbD approaches, that generally aim to recognize both action and where it is applied, we propose a division of labor, where the operator manually specifies the action the robot should perform, while gestures are used for specifying the relevant action parameter (e.g. on which object to apply the action). Using this two-step method has the advantages that there is no uncertainty of which action the robot will perform, it takes into account that the environment changes, so objects do not need to be at predefined locations, and the parameter specification is possible even for inexperienced users. Experiments with 24 people in 3 different environments verify that it is indeed intuitive, even for a robotics novice, to program a mobile manipulator using this method.}},
  author       = {{Pedersen, Mikkel Rath and Krüger, Volker}},
  issn         = {{0921-0296}},
  keywords     = {{Industrial robots; Gesture recognition; Teaching by Demonstration; robot skills}},
  language     = {{eng}},
  pages        = {{149--163}},
  publisher    = {{Springer}},
  series       = {{Journal of Intelligent and Robotic Systems: Theory and Applications}},
  title        = {{Gesture-Based Extraction of Robot Skill Parameters for Intuitive Robot Programming}},
  url          = {{http://dx.doi.org/10.1007/s10846-015-0219-x}},
  doi          = {{10.1007/s10846-015-0219-x}},
  volume       = {{80}},
  year         = {{2015}},
}