Capstone Project

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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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