algorithms – survival of the fittest

I’ve been volunteering with a FIRST robotics high school team as a programming mentor. Due to a “series of unfortunate events”, we didn’t get to test our logic to drive straight in autonomous mode until the night the robot went into the crate.

We wound up using an interesting approach. First we brainstormed options and prioritized them. If the programmers got the robot early, we would test in that order. Alas, we did not get the robot early. We got it for 45 minutes about an hour before packing time.

Since it takes time to load code changes to the robot, we parallelized as much as possible. The students had time to test the competing approaches before we got our turn with the robot. So we tried them all by flipping a switch and then tuned the most promising one. It was a great use of time and available resources. And we wound up with an approach that wasn’t in our initial brainstorm.

The lesson applies to us all. Be aware of your primary constraint; in this case time; and optimize to that. Punch card programmers certainly knew this and optimized per run at the machine.

I was very impressed. Good luck in the regional competition team 694!

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