Video tutorials

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.

In this video tutorial we use the LEGO Education SPIKE Prime Motion Sensor to reach a mission model on the field. It's a basic use of the motion sensor that we will extend in the next few tutorials and in the same time we take the opportunity to demonstrate what a MyBlock is and how to develop one. As a result of this video you will learn how to make the program easier to read and maintain by organizing the blocks in the program in special MyBlocks that couple them all together.

Is it better to do fast turns or slow turns? Should you save some time by turning fast or should you be more precise by turning slow. Where is the balance? This video tutorial demonstrates exactly this for LEGO Education SPIKE Prime robot, their motion sensor and an ever occurring question on FIRST LEGO League competition which is how to find the balance and where is the balance.

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.

In this video tutorial we demonstrate the importance of properly shielding and protecting the light/color sensors of your LEGO Mindstorms Robot Inventor robots. These principles generally apply for all kind of robots. The problem is that external light sources from the venue could change the behavior of the robot - like have you ever been to a competition venue where the lighting just makes the robot behave in different ways? - well this tutorial is for you!

This animation demonstrates the principle of aligning to a line with two color sensors and a LEGO Mindstorms Robot Inventor robot. This is a useful concept for FIRST LEGO League competitions where you want to know exactly where you are on the field and to achieve consistent behavior. In the course lesson you will also find a live video tutorial where we enter into more details about aligning. We align the robot to a line by moving both sensors slowly until they both see a black line. When one of them sees the line we move only the other. At the end we return the first sensor back.

In this short animation we demonstrate how the LEGO Mindstorms Robot Inventor Distance sensors could be attached to the robot and then use to stop at distance from a wall. This wall could be the border of the field or another mission model. We need an attachment, we need a sensor and we need the robot. In the live video in the lesson we enter into more details and explanations of how the sensor is used. Programs for the distance sensor are provided in the lesson and in the LEGO Mindstorms Robot Inventor Programming course we enter into more details about how to program the distance sensor

In this video tutorial we discuss probably the most useful principle that we've found for FIRST LEGO League competitions and this is how to align to a line with two color sensors. We use the LEGO Mindstorms Robot Inventor for a quick demonstration of the principle. In the LEGO Mindstorms Robot Inventor Programming course we enter into more details of how exactly we program the sensors. The current tutorial demonstrates the use of such a program and makes clear why this could be very useful and is a must for any well prepared team and wants to achieve a good score on the competition.

In this video tutorial we demonstrate a few ways to use the Distance sensor from the LEGO Mindstorms Robot Inventor on FIRST LEGO League competitions. We don't enter into the details about programming as we do in the LEGO Mindstorms Robot Inventor Programming course, because here we demonstrate the behavior of the robot when the sensor is use and we make the argument that you should always use sensors at FIRST LEGO League competitions

In this video tutorial we try to move forward with a LEGO Mindstorms Robot Inventor robot and we try to keep a straight line using the Motion Sensor. Without entering into the details of the programming we demonstrate what is the behavior of the robot when trying to keep a straight line with the Motion Sensor while we are participating in a FIRST LEGO League competition.

In this video tutorial we demonstrate the behavior of a LEGO Mindstorms Robot Inventor robot when we use the Motion sensor. The Motion sensor was also referred to as Gyro sensor in previous versions of the LEGO Mindstorms Robot. We do not enter into the details of the programming and you can download the programs from the course lesson, but we make a demonstration of how the robot turns to about 95 degrees when we try to turn it to 90 degrees, we explain why and we suggest a way to improve the behavior of the robot.

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. 

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.

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. 

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. 

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 video tutorial, we would do a few experiments with the coefficients for the Integral compensation. There are actually two coefficients - "c" and "b"

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. 

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. 

This is where the confusion really comes. We are keeping the robot orientation straight while the robot moves, but at the end the, robot is not at the fiinal location that we would like it to be. The robot is still about 2-3 centimeters away after moving for about a meter.

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.

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.

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. 

Following the Advanced Sensor Calibration course section, it is time to extract the logic for getting a calibrated value into a new block. This block will have an input and on this input, we give the port number. The block will return the calibrated value for this port number. We've built all the other blocks only because of this almost final video here.