Inspiration
I wrote my college application essays on Boston Dynamics. When I saw Spot, I was a little kid again with a bright mind and an innocent smile. However, I didn't know what I wanted to build exactly, until I noticed the infinite supply of QR Codes around me!
What it does
Spot utilizes a graph search algorithm to find a QR code in its environment. On detection, Spot gallops the entire distance (depth-perception) to the target. If Spot overcommited and got too close to the target, it flees the scene as a dog usually would!
How we built it
I used Merklebot's abstraction and frameworks to run my code on Spot. I utilized a depth-perception algorithm that estimates how far an object is in the environment. The robot would search for the QR code, and once it found it, it would dash at the qr code. If it lost the target, it would commence search again. Search is based on DFS for simplicty. However, it can easily be changed to a more sophisticated algorithm, such as A*, for instance.
Challenges we ran into
It is a difficult task to get the search to work. Additionally, it's very tedious to get live data from the robot for analytics and debugging. Managing Spot necessitated high-quality code, so the robot doesn't damage anything, which was a strenuous task.
Accomplishments that we're proud of
I actually worked with Spot and did something!!!!!
What we learned
Murphy's Law exists for a reason. I should be better at estimating the breadth of projects.
What's next for Untitled
Add a particle filtering sampling algorithm that listens on the microphone, and can detect where targets might be based on a sound they exhibit. This can be incorporated in an A* algorithm as its heuristic. Play hide-and-seek!
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