DocumentCode
3017511
Title
Gesture recognition using evolution strategy neural network
Author
Hägg, Johan ; Çürüklü, Baran ; Akan, Batu ; Asplund, Lars
Author_Institution
Intell. Sensor Syst., Malardalen Univ., Vasteras
fYear
2008
fDate
15-18 Sept. 2008
Firstpage
245
Lastpage
248
Abstract
A new approach to interact with an industrial robot using hand gestures is presented. System proposed here can learn a first time userpsilas hand gestures rapidly. This improves product usability and acceptability. Artificial neural networks trained with the evolution strategy technique are found to be suited for this problem. The gesture recognition system is an integrated part of a larger project for addressing intelligent human-robot interaction using a novel multi-modal paradigm. The goal of the overall project is to address complexity issues related to robot programming by providing a multi-modal user friendly interacting system that can be used by SMEs.
Keywords
gesture recognition; industrial robots; learning (artificial intelligence); neurocontrollers; ANN training; SME; evolution strategy neural network; hand gesture recognition; industrial robot; intelligent human-robot interaction; multi modal paradigm; product usability; user friendly interacting system; Intelligent sensors; Investments; Manufacturing automation; Manufacturing industries; Manufacturing processes; Neural networks; Orbital robotics; Robot programming; Robotics and automation; Service robots;
fLanguage
English
Publisher
ieee
Conference_Titel
Emerging Technologies and Factory Automation, 2008. ETFA 2008. IEEE International Conference on
Conference_Location
Hamburg
Print_ISBN
978-1-4244-1505-2
Electronic_ISBN
978-1-4244-1506-9
Type
conf
DOI
10.1109/ETFA.2008.4638401
Filename
4638401
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