The Gyro sensor in LEGO Mindstorms EV3 sets is new for the sets and we answer basic questions about its usage. The sensor detect when the whole constructions turns at a particular angle, but there are a number of gotchas in using it.
Implementing the next logic for aligning to the border when we approach the border from the right.
After several questions about the use of the LEGO Mindstorms NXT Light Sensor with the EV3 software, we have decided to go through this problem in this video tutorial and pay special attention to the Raw Sensor Value Block.
Counting lines and stopping on the third is the subject of this video. It is important to know how to do this in order to conduct more than one experiment in STEM classes (if we consider that each line is an experiment)
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.
All worked as expected, up until know because the robot got lost. This happens when we turn right and the line does not continue to the right. Now the robot must somehow understand that it is "lost" and escape.
Now that you have tried and solved a challenge involving a series of instructions, we would like to share a few best practices.
How to control the arm of the push bot using the two triggers on the GamePad of the FTC Push Bot?
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.
This package contains the three blocks used in the advanced calibration section of the FLL course.
The blocks contained are:
With this program you can drive the Truckie or every robot with the same port settings. It is hard to drive with that set up because to have the robot move in the right direction you need to be very precise with the stick. The part of the problem is that this set up uses only one stick to control the movement. You have to chose left or right stick. If you use both it will be a great mess. It is not impossible but it is very hard to do. You probably will never use this stick setting in the VEX competition but practicing this type of setting you will become very precise with the controls and your driving skills will grow a lot. Ones you have master this driving technic you will be more relaxed while you are on the competition.
After you feel satisfied with your driving skills and you have accomplished all the goals you can continue with the competition driving program settings like Truckie - Easy To Drive VEX IQ Program for Modkit.
This program is mainly for controlling Truckie VEX IQ robot.
This is the first, but not the last video tutorial of the course where we reach a specific mission model in a consistent way. We use the Motion sensor and only some basic principles like turning to an angle. If we use the principles in this tutorial and then build an attachment for the mission model we will have a pretty consistent way of accomplishing the FIRST LEGO League mission
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.
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.
