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# 10 runs on line follow with multiple states algorithm for Color Sensor from LEGO Education SPIKE Prime ProPreview

In this video tutorial we follow a line 10 consecutive times. In this way we demonstrate whats the consistency that you could expect from the robot when following a line with a multi-states algorithm.

• #1936
• 30 Jun 2022
• 3:12

## How to use this tutorial?

Download the program and check how your robot behaves. Is it more or less consistent. This will help you set the expectations of what you can expect from the robot and will generally be much more fun.

### English

In this video tutorial we will do a ten out of ten runs on how to follow a line with a multi-state program. We use LEGO Education SPIKE Prime. Let's see how it works. Ten runs. How consistent is the robot? We follow the line, we take the turn and this is where we stop. These are 10 seconds for our robot. Let's try again. We'll do ten of those "follow the line".

So it's almost at the same place.

10 seconds. A lot of turns. There could be a lot of slips and wheels - they could slip on the map. But at the end we arrived at almost the same place. Here we are at exactly a different place. The point here, and what I'm trying to emphasize on is that if we just rely on the timer to follow the line, it might not be the best idea because when we rely on time, the robot could arrive at different places. We should always rely on something else, like another event that could happen. For example, we detect a different line with the other sensor and in this way we say we are at the exact location. It's not that we've waited some time and we hope we are there. We specifically wait for events to occur. Let's do a couple of more of those. Start, follow third right here on the left turn. We kind of get to the same place, but just relying on the timer. And in some of the next tutorials we'll demonstrate how you can wait for another event to occur. How you can, for example, stop when you detect the second black line. And this way you know exactly where you are on the field, which is priceless, because that's what's difficult on the competition. It's difficult to know with your robot where you are on the field. If you can figure this out, the rest is quite easy. So how can we know where we are on the field? Again, turn,