We were inspired by the anti-air systems utilized by militaries, and were intrigued by the idea of reproducing a similar system with lower cost components aided by the power of computer vision.
What it does
The targeting system uses OpenCV libraries to detect a balloon, and isolate the coordinates of its center. It then proceeds to pass this information to our control system and then through a predictive algorithm, managed by an Arduino 101. After aiming at its target coordinates it fires the laser, popping the balloon.
How we built it
We built the system using C++, OpenCV, and Arduino. We designed a X/Y aiming system that combines the planar mobility of 2 motors for optimal targeting accuracy.
Challenges we ran into
While building the laser targeting device, we ran into a plethora of hardware issues, most notably due to a lack of compatible components. Additionally we had to overcome the hurdle that was our team's overall lack of experience in working with hardware. Yet dispite of these pitfalls, we managed to demonstrate a proof of concept.
Accomplishments that we're proud of
We are proud of our overcoming the many adversities we faced while trying to build something we all found interesting, and still accomplishing a relatively impressive project.
What we learned
We developed many skills in working with hardware, computer vision, algorithm development, and the incorporation of these diverse components.
What's next for Project Supernova
We believe the next step is to integrate the individual components more effectively, and improve the learning algorithm, so that we can improve the accuracy of the targeting system.
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