Miniaturized, Low Latency, High Accuracy Head Tracking System 2019-20

By

Isaac Grossberg and Joseph Noreen

This project is part of a larger project, an augmented reality style headset to be worn by helicopter pilots to aid them in flight. The idea is to have the wearer be able to move their head while wearing these glasses and not have any issues with vision. Our system works through the usage of implemented sensors, being inertial, gyroscopic, and magnetometer sensors. The inertial, gyroscopic, and magnetic field data is sent to an API and presented visually to the user, but this information can also be used to communicate with the glasses, providing the wearer with high-quality visual assistance during flight.

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Artifacts

Name Description
Electromagnetic Switching PCB This is the PCB design we went with for providing our electromagnets with short bursts of power. As you can see, there is space for a relay to be mounted in the middle.   Download
Sensor to RPi PCB This is the PCB design to allow the mitigation of using a breadboard.   Download
Summary Video Video describing the final system and design.   Link
Google Site The commercial flying industry is constantly evolving to produce more efficient methods of flying, superior navigation systems, and lowered risk of crashes. One of the latest efforts in this arena is the development of augmented reality headsets for pilots. This effort is being undertaken by experienced engineers at Collins Aerospace and the job of prototyping designs has been tasked to our group of undergraduate engineering students at Oregon State University. The scope of this project is the system used for sensing the pilot's head movements. This involves a series of Inertial Measurement Units (IMU) positioned on the pilot's headset that will relay information to a central processor for precise calculation of head positioning. Additionally, external electromagnets will be pulsed in conjunction with magnetometers to confirm absolute head positioning to account for any error in the inertial sensor's measurements over time.   Link
Github Repo Code base for sensor libraries and API.   Link
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