Controlling method of industrial robots based on the electroencephalogram

This paper puts forward a model of the seamless collaboration between human and industrial robot depending on the technology of using the electroencephalogram(EEG) to control the movement of industrial robots. Wavelet packet decomposition is operated on the EEG signals for analysis. EEG signal features that industrial robot motion control needs are extracted as motion control input signals. A database is built for the decomposition of industrial robot movements. In order to prove the theory mentioned above, a system model of human-robot cooperation industrial robot controlled by the EEG signals is set up, which can be used in complex collaborative assembly.

[1]  E Donchin,et al.  The mental prosthesis: assessing the speed of a P300-based brain-computer interface. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[2]  A. Searle,et al.  EEG-based system for rapid on-off switching without prior learning , 1997, Medical and Biological Engineering and Computing.

[3]  Bin He,et al.  A wavelet-based time–frequency analysis approach for classification of motor imagery for brain–computer interface applications , 2005, Journal of neural engineering.

[4]  G Pfurtscheller,et al.  Current trends in Graz Brain-Computer Interface (BCI) research. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[5]  Gabriel Curio,et al.  Brain-computer communication and slow cortical potentials , 2004, IEEE Transactions on Biomedical Engineering.

[6]  G Calhoun,et al.  Brain-computer interfaces based on the steady-state visual-evoked response. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[7]  Clemens Brunner,et al.  Mu rhythm (de)synchronization and EEG single-trial classification of different motor imagery tasks , 2006, NeuroImage.

[8]  E Donchin,et al.  Brain-computer interface technology: a review of the first international meeting. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.