DocumentCode :
1788731
Title :
A comparison of learning-by-demonstration methods for force-based robot skills
Author :
Kramberger, Aljaz
Author_Institution :
Dept. of Autom., Biocybernetics & Robot., Jozef Stefan Inst., Ljubljana, Slovenia
fYear :
2014
fDate :
3-5 Sept. 2014
Firstpage :
1
Lastpage :
6
Abstract :
Conventional programming techniques for robotic operations in unstructured environments are not suitable for human-like robot executions. In this paper we present a comparison of three different learning-by-demonstration techniques. A force-based representation of the learned data is presented and analyzed. The action to verify the experimental results can be related to Peg-in-Hole action. The results show which method is the most suitable to use for the specified task.
Keywords :
control engineering computing; force feedback; human-robot interaction; humanoid robots; force feedback; force-based representation; force-based robot skills; human-like robot executions; learning-by-demonstration methods; peg-in-hole action; Education; Force; Haptic interfaces; Robot kinematics; Robot sensing systems; Trajectory; Learning-by-demonstration; Peg-in-Hole; force feedback; robot skills;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics in Alpe-Adria-Danube Region (RAAD), 2014 23rd International Conference on
Conference_Location :
Smolenice
Print_ISBN :
978-1-4799-6797-1
Type :
conf
DOI :
10.1109/RAAD.2014.7002256
Filename :
7002256
Link To Document :
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