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
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;
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
DOI :
10.1109/ETFA.2008.4638401