This video tutorial contains the final 2 programs for moving straight with a LEGO Mindstorms EV3 robot. The first program is for proportional compensation that just keeps the robot orientation straight, while the second program is for Integral compensation that returns the robot to the straight line when the robot makes a mistake.
This is one of the last tutorials in the LEGO Education SPIKE Prime programming for Competitions course and it demonstrates what we've all been waiting for - how to reach a mission model from base in a reliable and consistent way when the mission model is on the other end of the field. Naturally what we use are all the different concepts that we've learned in the course and the tutorial is more advanced than the other so if anything is not clear take a look also at the different tutorials an concepts in the course.
This is the first video tutorial from the LEGO Education SPIKE Prime programming course in which we use a sensor, and we've selected to use the motion sensor. The Motion sensor allows us to detect how the robot turns in a 3-dimensional space-time continuum, or, to put it simply, we use it to move straight with the robot. That's it. We want to move straight - we use a sensor, and the Motion Sensor is a good choice.
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.
On the topic of following lines with a robot there is a way to make the robot follow the line a little more precisely. This method is called "Multi-states" program. Or at least we call it like this. In this tutorial you will see how we program 5 state for the robot line following program. This could be particularly important with FIRST LEGO League competitions where we must build consistent and reliable robots.
With this 10 runs we demonstrate the consistency and reliability that could be achieved with a LEGO Education SPIKE Prime robot and a 2-states simple line following algorithm. It is not bad. Still there are some things you should consider when using this program and one of the things is the use of the timers
In this video tutorial we demonstrate the classic algorithm for following a line with robots. It is widely used in FIRST LEGO League competition and could be applied to LEGO Education SPIKE Prime and to other robots also. The algorithm follows a line by moving to the left and to the right and trying to stay at the edge of a black line.
We use a sensor so the robot must be reliable and accurate right? Wrong. The robot is not reliable and accurate only because we use sensors and that's really important during FIRST LEGO League competition. There is a reason for this and in this tutorial we demonstrate and explain how the robot behaves with a basic use of the Motion Sensor to move straight. As a result you will learn why is it important not to stop at this stage and to go to the next level with more advance use of sensors.
The first part of making the robot move straight is to keep it oriented straight. While it moves it could make an error and turn slightly to the right and then the program should turn in back to the left to make its orientation straight. In this video tutorial, we would discuss how to implement a program to keep the robot orientation straight even when we are pushing or pulling it to either side and in the same time it has different wheels.
This robot has a color sensor and this sensor is used for following lines. Additional Mindstorms EV3 sensors could be place on the robot, like a Gyro sensor or a second Color sensor.
You are not using sensors?! You are positioning the mindstorms robot only by moving forward, backwards and rotating it. That`s one of the BIGGEST mistakes teams make on the FIRST LEGO League competitions. In this video we are showing a robot with chains and how imprecise are the results are when you are not using sensors.
The integral part "remembers" the errors that the robot has made in the past and we can compensate for those errors. This will make the robot return back to the line that we would like to keep it aligned.
It's inevitable. While following this gapped line we would reach a gap. The robot must somehow understand that there is a gap and must make a decision on what to do. For detecting the gap we use the Rotation Sensor. Not the most popular, but very convenient in many cases. Check out the video.
We should multiply the error by a certain number and then add it to the steering of the LEGO Mindstorms Steering block. In this way, by changing the coefficient we change how much/fast should the proportional part influence the steering of the robot.
In this video tutorial, we would do a few experiments with the coefficients for the Integral compensation. There are actually two coefficients - "c" and "b"
In the previous part of the video lesson we showed how imprecise a chain LEGO Mindstorms robot could be if its positioning does not rely on sensors, but only on the use of move block. In this tutorial we will show the same thing, but using robot on tires.
We keep the robot orientation straight while moving, but when we stop the robot could be in a different orientation. This applies for both using the Mindstorms Gyro Sensor when moving straight or the Mindstorms Color sensor when following a line. In this video tutorial, we will do a few examples of when an how this could happen.
This is the final run for our World Robotics Olympiad (WRO) 2015 Elementary Challenge Robot. In "dives", detects the color of the pearl and then counts the number of Ping-Pong balls to release.
In this video tutorial we demonstrate the use of the motion sensor and how it could be use to turn precisely to 90 degrees. We demonstrate some of the caveats of the sensor and how sometimes it does not work as expected. Like you set the robot to turn until the sensors detects 90 degrees and at the end the robot is not at exactly 90 degrees.
Let's record the values of the Gyro Sensor while the robot is moving and is trying to keep its orientation straight. This is an interesting experiment and we will have to use file access to write the values to a file.
Showing the same run, but from a different angle. This allows you to see more of the way we sensors work and how exactly the robot positions itself.
This video tutorial is about understanding the "magic". In this video tutorial, we would conduct an experiment and will look at how exactly does the integral part of the PID algorithm compensate for the error that the LEGO Mindstorms EV3 robot makes.
Sometimes when we are working with sensors it is important that the time between two consecutive samples is the same. This will make each sample equally important and independent of how much time it took to take it. In this video tutorial, we would use the EV3-G timer block to make a "WaitForTick" program where the time between each sample of the EV3 Gyro takes exactly 0.02 seconds.
In this tutorial, we would implement a program that finds the minimum and maximum value detected by the sensor and stores this two values in an array.
Many times we just upload blocks and leave it up to you to use it. In this tutorial, I would like to show you how to use the implemented blocks. How to import them into the EV3-G software. How to see them in the palette. How to drag and drop them to build a working program.
After we take each sample, we perform calculations and these calculations could take different time. It is important to know how much time does it take to perform the calculations. In this video tutorial, we would data log the time and plot the data.
"Array initialization" is the first step in every program that involves Arrays. This applies to most programming languages and for EV3-G it is a must.
In this tutorial, we would show you how to initialize the array and how to extract this logic in a new block