Video tutorials

The LEGO Mindstorms EV3 set comes with two LARGE motors. But even though these motors look almost the same they are not quite the same. There are always some differences in their behaviour. If you have more than two motors, because you bought them or you won them somewhere at a competition, it is worth doing an experiment to find which pair of motors works best. 

The robot can move with different speed by applying different power to the motors. It will most of the time make smaller deviations when it moves slower. But you can't just move with a power of 10 all the time. This is a way too slow especially for competitions like FIRST LEGO League or World Robot Olympiad. In this video tutorial I would like to discuss the balance between motor power and robot movement error, how does the battery influence the power of the robot and to conduct an EV3-G experiment that will record the values of the Gyro Sensor along with the current power. 

Tasks for the Gyro sensor that you can use in STEM classes, while preparing for a competition or just to explore how the sensor works.

Continuing with the Proportional algorithm for following lines. Smooth and stable this is the first part of the PID.

Let's explain the problem of just waiting for the Gyro sensor to detect an angle and think of why the robotics systems work like that.

Last part of the series. The final touch of the program makes sure that it works and is following the line with the LEGO Mindstorms EV3 Color Sensor in a smooth and fast way. 

This video lesson is a revised version of Episode #1. Matt Gipson requested it in a comment. Using the EV3-G software we have developed a very simple program for following a line with two LEGO MINDSTORMS color/light sensors.

In this tutorial we introduce the basic algorithm for following a line with one sensor and review the algorithm for quickly followwing a black line with one sensor, implementing both with the Mindstorms EV3 robotics kit.

The Gyro sensor can be positioned horizontally, vertically or at a random angle. Have you ever wonder what does the gyro detect when it is positioned vertically. This is the subject of this video tutorial for the LEGO Mindstorms EV3 Gyro Sensor.

Every time we start the robot we want to start from the same place, not only in terms of where we are on the field but also in terms of how are the motors rotate. The motors have an internal sensor for detecting the rotation. Because of this they know how rotated they are. It is a very good practice to always reset the motors before we start a competition run especially at FIRST LEGO League or World Robot Olympiad competitions

In this 10 out of 10 tutorials we do 10 runs that demonstrated how consistent and reliable it is to stop at the second intersection. This is useful as it is one of the main ways to figure out how to position yourself on the field.

In this video tutorial we take a next step in programming reliable and consistent robots and this is to learn how to stop at a second intersection. We need this because most of the time when we want to reach a mission model on a robotics competition field, the model will be located away from us and we must use all kind of technique to reach it. In this tutorial - we stop at a second intersection.

On of the most precise ways to position on the FIRST LEGO League and other competition fields is to follow and align and in this tutorial we demonstrate exactly this - how consistent and reliable this method is to reach specific mission models. In this way you know that every time you will be at the right place, which is great.

In this video tutorial we demonstrate a really important concept for FIRST LEGO League competitions - you position the robot on the field with depending on timers and rotations. The issue with moving the robot for 10 seconds and then stopping is that every time it is in a different location. Same for rotations. The wheels will slip, the battery will change, something will happen and the robot will not be in the same place every time. This is not consistent and reliable.

In this video tutorial we show how you can build robots that position on the field consistently and reliably by following and line and then aligning to a line. We also demonstrate the concept of "double align" which is quite powerful and even if there were some mistakes they will be handled.

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. 

We extract the Proportional Line Following algorithm into a new block with parameters. This allows us to experiment with the Threshold, Constant Speed and Relaxation Coefficient. You can now easily use the block in you other programs without having to implement it. 

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.

When aligning backward the robot is still very consistent. It does not matter the direction in which we align. What you will learn from this tutorial is what is the consistency and reliability of the robot that you could expect.

Instead of aligning forward as in the previous tutorial we felt there is a need to demonstrate how we could align backward when moving with the robot. This is not a rare case. The attachments of the robot are generally at the front of the robot and especially during FIRST LEGO League competitions the robot must move backward very often. It is helpful to have in your toolbox the ability to align backward with the robot.

This video tutorial demonstrates again the consistency of the program for aligning to a line. We run it ten time. We the robot is always coming from the left it is always arriving at the same position. When it is coming from the right it is always arriving at the same position.

The reason why you would want to watch this tutorial is because it demonstrates one of the most reliable ways to know where you are on the field and to accomplish missions successfully and this is aligning to a line. In the tutorial you will also see how a parallel program is developed and who parallel programs could be used in a meaningful way.

In this video tutorial we run the robot for 10 times and we demonstrate the consistency of the robot behavior with our advanced algorithm for smooth line following. What you will get from it is an understanding and demonstration of what can you expect from the robot.

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 10 out of 10 tutorial we demonstrate the accuracy of the robot when we use acceleration in its movements. The robot has not sensors attached to it and it is not making use of it's internal sensors. The goal of the tutorial is to give you the understanding and to make a demonstration of how difficult it is to consistently reach a mission model without the use of sensor even when we use acceleration.

Use the color sensor to count the lines and stop on the third line. We do not use the wait block for this.

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.