In FLL the work of getting a robot to do what you want is often difficult. It takes longer than we might first expect. We are used to seeing videos of robots that work. What we don’t see is what goes on behind the scenes, the long hours of trying again and again to get it to work.

So after many attempts, hopefully we do see our plan work. This is a time for celebration! It is very encouraging to see a robot carry out what you have envisioned. The bad news is that you aren’t really done yet… (sorry). You won’t really know if you are done until you have a feel for how reliable your solution is. Just because it works one time doesn’t mean it will work every time. You know, you’ve been there… The robot does what it was supposed to do, so you call someone over to see it. You do the same thing again and… it doesn’t work!?! And you say, ” It did work, really!! Let me try it again…. “

The way we measure the reliability of our robot is to do repeatability testing. We run the robot ten times in a row, counting how many times it worked. We write this number as a decimal or percent. The team should determine what is an acceptable score. It does take more work (aka more time) to get the repeatability score higher.

You might be wondering if the extra work of raising your repeatability is worth it. Let’s say you want to go for all 400 points, but by doing so you spread yourself a little thin. Your repeatability scores for most runs are 7 out of 10, (or 0.7). When you multiply the possible score by the repeatability score, your answer is your *average* score. On average, your score would be 285, even though you were trying for 400.

What if we were to drop the lowest scoring run, and spend our time instead on raising the repeatability of the other runs? Our possible score might be reduced, but on average, our actual score goes up when our repeatability increases. A higher score is achieved, even though we aren’t going for all the points. See the chart below.

A spreadsheet application, such as Excel, is meant for What If analysis. Creating a table like this could be a good exercise for team members. Formulas in the “average score” and “total” cells will allow you to input different repeatability scores to see how it affects your average score.

Going for a high repeatability is really like striving for excellence. The examples above show that hard work is compensated with a better score. Excellence is also rewarded in another way too. The more repeatable your robot, the less you will have to rescue it, right? If you don’t rescue your robot, you get to keep the penalty points. In Body Forward there are 8 pieces worth 5 points each, for a total of 40 points. We could think of these points as an Excellence Bonus.

So is repeatability in FLL important?? I think so.