| Group |
2016-21 |
Status |
completed |
| Title |
Hybrid BCI and Tactile Sensor Strategy for Controlling a UAV |
| Supervisor |
Dr. Luis Rodrigues |
| Description |
Controlling a drone solely with a Brain Computer Interface (BCI) has been proven to be a
challenge on its own. Maintaining a valid brain signal for steady motion is difficult due
to external distractions and noise. BCI interface allows an operator to map a particular
brain signal with a command to control a UAV. Making a discrete movement can be
simple since the operator only needs to generate one brain signal at a time. However, in
the case of combining multiple movements at once, the operator has to produce multiple
brain signals simultaneously.
We propose a fusion of sensors to facilitate the control of a drone. By
using not only a BCI but also a wearable bracelet sensor we can “lock” a desirable brain
signal with a simple sensor interaction. The idea is that an operator no longer needs to
keep generating a particular steady brain signal to maintain a given steady motion but is
free to generate different signals to create more complex motions.
For facilitating the pilot decision-making a software application for visualizing the brain
signal, the tactile sensor signal, and the fusion of the two signals will be created making all this information accessible to the pilot |
| Student Requirement |
Control systems, signal processing, programming |
| Tools |
Matlab/Simulink, BCI device, quadrotor UAV, autopilot, battery chargers,microcontroller. |
| Number of Students |
5 |
| Students |
Ahn,Jin Bee Cianciarelli,Katherine Feller,Nicolas Raymond Nguyen,Tu Reutskyy,Illya
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