Abstract
Ubiquitous robotics augments the capabilities of one or more robots by leveraging ubiquitous computational and/or sen- sorial resources. Augmentation complements and/or enhances the capabilities of one or more robots while such robots can simultaneously serve as intermediaries to ubiquitous services. Electroencephalograms (EEG) are Brain-Computer Interfaces that consist of a series of conductors placed on the scalp. These conductors measure voltage fluctuations in the brain, and using machine learning techniques can be classified and used to command ubiquitous robotic systems. The purpose of our work is to increase the collaboration between humans and surrounding robotic components while fulfilling a certain goal or requirement. We aim to do that by granting humans more precise manipulation, (i.e., brain- driven), over part or all of the involved robotic components. This paper presents our approach on the integration and benefits of an EEG interface within ubiquitous robotic systems.
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