Reference : Human Error Identification in Programming by Demonstration of Compliant Motion Roboti...

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Mechanical engineering
	To cite this reference:	http://hdl.handle.net/10993/7636

Title :	Human Error Identification in Programming by Demonstration of Compliant Motion Robotic Tasks
Language :	English
Author, co-author :	Jasim, Ibrahim [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
	Plapper, Peter [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
Publication date :	Jul-2013
Main document title :	2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2013), Hyderabad 7-10 July 2013
Peer reviewed :	Yes
On invitation :	No
Audience :	International
Event name :	2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2013)
Event date :	07-07-2013 to 10-07-2013
Event place (city) :	Hyderabad, India
Event country :	India
Keywords :	[en] Compliant motion robots ; Fuzzy clustering ; Gravitational search ; Outlier detection ; Programming by Demonstration (PbD)
Abstract :	[en] In this paper, we suggest a scheme for error identification in human skills transfer when using the Programming by Demonstration (PbD) in adding a set of skills from a human operator to the force- controlled robotic tasks. Such errors in human skills transfer is majorly caused from the difficulty of properly synchronizing the human and machine responses. Based on the captured Cartesian forces and torques signals of the manipulated object, we present an approach of identifying the errors stemmed from human wrong skills transfer in a PbD process. The scheme is composed of using the Gravitational Search- Fuzzy Clustering Algorithm (GS-FSA) in finding the centroid of the captured forces and torques signals for each Contact Formation (CF). Then using a distance- based outlier identification approach along with the centroid of each signal, the human errors can be identified in the framework of data outlier identification. In order to validate the approach, a test stand, composed of a KUKA Light Weight Robot manipulating a rigid cube object, is built. The manipulated object is assumed to interact with an environment composed of three orthogonal planes. Error identification for two case studies will be considered and other cases can be dealt with in a similar manner. From the experimental results, excellent human error identification is shown when using the suggested approach.
Name of the research project :	R-AGR-0071 > PROBE > 01/01/2013 - 31/12/2015 > PLAPPER Peter
Target :	Researchers ; Professionals ; Students ; General public
Permalink :	http://hdl.handle.net/10993/7636
FnR project :	FnR ; FNR2955286 > Ibrahim Jasim > > Self-adaptive Fuzzy Control for Robotic Peg-in-Hole Assembly Process > 01/05/2012 > 30/04/2016 > 2012

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