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Projects - Neurobots



An Autonomous Robotic Assistant for Drinking

Stroke and neurodegenerative diseases, among a range of other neurologic disorders, can cause chronic paralysis. Patients suffering from paralysis may remain unable to achieve even basic everyday tasks such as liquid intake. Currently, there is a great interest in developing robotic assistants controlled via brain-machine interfaces (BMIs) to restore the ability to perform such tasks. This paper describes an autonomous robotic assistant for liquid intake. The components of the system include autonomous online detection both of the cup to be grasped and of the mouth of the user. It plans motions of the robot arm under the constraints that the cup stays upright while moving towards the mouth and that the cup stays in direct contact with the user's mouth while the robot tilts it during the drinking phase. To achieve this, our system also includes a technique for online estimation of the location of the user's mouth even under partial occlusions by the cup or robot arm. We tested our system in a real environment and in a shared-control setting using frequency-specific modulations recorded by electroencephalography (EEG) from the brain of the user. Our experiments demonstrate that our BMI-controlled robotic system enables a reliable liquid intake. We believe that our approach can easily be extended to other useful tasks including food intake and object manipulation.

Paper

Sebastian Schröer, Ingo Killmann, Barbara Frank, Martin Völker, Lukas Fiederer, Tonio Ball, and Wolfram Burgard
An Autonomous Robotic Assistant for Drinking, accepted at ICRA 15

Video

 
The video shows one trial of our system together with the processed data. The video on the bottom left displays the robot's view and indicates the detected cup and mouth of the user. The small video on the bottom right displays the EEG data. Furthermore, whenever a user command - in our case imagination of a finger tapping movement - is decoded, the orange ball moves to the right.
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