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 first part we stop at an algorithm that is the base for following lines and explains the basic idea for the proportion. A must watch if you want to understand the robot at its behaviour. At the end the program still wont work so check out Part 2 and Part 3 for the final steps.  

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.

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

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. 

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.

We start a course for following a line with crosses and gaps. This is a challenge that one of the users at FLLCasts.com was trying to accomplish and asked us for advice. We present the whole challenge to you step-by-step. But first, let's also see the whole run of the line following algorithm. With this course, we also do an introduction of using State Machine as a programming pattern.

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. 

Looking at the field we must first think of a strategy of solving this line following problem. There are rules that the robot must follow and these rules should be programmed in the robot. 

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 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. 

Would you like to resolve all the problems with the light/color sensors that you have? And to make all of them work in a predictable, stable way even when using more than one MINDSTORMS colour sensors. 

When using Color sensors it is important to calibrate them depending on the light conditions in your venue. In this way, the calibrated sensor will show values between 0 and 100 independent of the light conditions. But using the default EV3 colour calibration available in the colour sensor block could lead to unpredicted problems that are difficult to track and resolved especially when used with multiple Color sensors. So in this series of tutorial we implement the calibration ourselves discussing the principles of colour sensor calibration.

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"

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.

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.

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 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.