Video tutorials -

• EV3-G

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. 

In this tutorial we present a way to align your robot to a black line. Go through common difficulties, that the teams face, when they need to align their robot, and provide a solution for them.

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 third robot has the brick and motors placed vertically. This is quite unusual and difficult, but the construction is very powerful because it saves space.

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. 

We list the number of decisions that the robot is making while following the line. Then, we group them and decide on the number of sensors to be used.

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.

In this video lesson I will show you how to follow a black line using just one sensor, but fast enough so that you could use it during any robotics competition without wasting any time.

We follow a line. We start from the Smooth Proportional Line Following program and modify it a little for this program. We follow the line with the middle sensor attached on port 2. 

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 this video tutorial I give a step-by-step explanation of how to implement a block for aligning to a line. The block was first used in lesson 28. Aligning to lines is probably the most powerfull way to know the position of the robot on the FLL Competition field and to be able to execute the missions precisely at 100% of the time.

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.

We've detected the gap. It's time to move over it. This is difficult because we have to detect where the line is after the 0.1 meters gap on the line following field.

Next important state is Turn Right with our robot. This happens when we detect a line on the right. 

Next state in our state machine programming pattern is the "Turn Left" state and the corresponding behaviour.

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. 

We can Turn Right. We can Turn Left. How do we decide which way to go if there are lines both to the left and to the right. Check out the video.