Video tutorials -

• Gears

In this third video we show some of the tricks in building this Multi-axles mechanism. Things you could learn from an use in your next constructions. 

"What is the light in the room?" - should it even matter. You can use one program for all lighting conditions by calibrating the color/light sensor of the LEGO Mindstorms EV3/NXT robots. 

Part four of the Catapult series is again about loading the catapult automatically but this time using EV3 brick, motor and sensor. We use a gear system with a medium complexity along with a "standard clutch" available in the LEGO Mindstorms EV3 kits. As a result, at the end of the video, the Catapult loads and fires automatically.

Starting with the World Robotics Olympiad 2014 Junior-High challenge we first catch the object on our path. We discuss a good mechanism for catching and lifting balls that can do two movements with one motor. 

In this second video lesson on catapults we improve the stability of the base of the robot. An important feature of the new base is that it is not bending. Use the same principle in all of your constructions to achieve better, stronger robots.

Extend the previously build attachment for the FIRST LEGO League (FLL) Nature's Fury competition so that we can move the Truck and Ambulance up and down. 

Part three of the Catapult series is about loading the catapult automatically. We use a gear system with a medium complexity along with a very interesting "clutch" developed with parts entirely from the LEGO Mindstorms NXT kits. As a result, at the end of the video, the Catapult automatically loads and fires.

Time to lift the robot. The first approach is by using the 40 teeth gear wheels that come with the LEGO Mindstorms EV3 and NXT robotics sets. 

Build a similar mechanism to this one. Similar, but for your robot. This is the task for you. Try, give yourself half and hour or even an hour.

Connect the attachment to the box robot and find the correct number of rotations of the middle motor that would bring the robot up and forward and would attach it to the mission model.

In this video we are solving part of the FIRST LEGO League Senior Solutions challange missions (FLL 2012) using LEGO Mindstorms NXT robots. I make a step by step explanation of each move I make. The goal of this video is to help you with ideas and suggestions on how one should look at the missions.

Vision is still one of the very few fields where a human being could outsmart a computer. Still. Colour/Light sensors are the cornerstones of implementing a smart LEGO Mindstorms robot that could at least partially do "vision". In this video tutorial, we are using the robotics sensor to detect loading and unloading of the catapult.

How great is the great attachment for lifting that we built in this course? How many times can it lift the robot without making an error? How great are your attachments and how could you test them? - the answer is simple. Just try 10 times and they should work at least 9 of them as our attachment is.

Here is our solution for preventing torsion and bending of the LEGO Mindstorms EV3 axles.

How to align the wheels and how much should you push for this solution?

There were a few problems with the 40 teeth gears that we were using. Let's list some of them

The M08. AEROBIC EXERCISE is one of the very common types of mission in FIRST LEGO League robotics competitions. I think this pattern of missions was first introduced with the growing abilities of the participating students that were constantly reaching the maximum number of points. So the competition introduced mission that require a lot of time - 20-30 seconds, are time consuming and are complex. They requires a lot of moves. This here is a video tutorial on how it could be accomplished

In this tutorial, we add another mission to our current program. This mission is - hanging the Gecko from the FIRST LEGO League Animal Allies. 

We calculate the number of rotatios when a gear system is involved. The driving wheel will have to do a number of rotations for the driven wheel to rotate to a desired number of degrees. In our specific case when the driven gear wheel is rotate to about 90 degrees the legs will lift the robot.

This is a teacher's note about the math behind calculating gear ratios with for our lifting attachment. It math model we build in previous tutorials is not exactly correct and here is the explanation why.

The task in this tutorial is to execute the program 10 times and to do it yourself. If you have your attachment then use it. If you have our attachment then use it. But execute the program 10 times and make sure that it works. 

Sometimes the answer that you get by calculating seems not to be right. Is it the calculation that is wrong. Probably it is not the calculation, but something is happening with the robot. 

This is a 10 out of 10 video tutorial that demonstrates the consistency and reliability of the robot that accomplishes the Unlock Cargo Plane mission. The attachment is an active attachment with gear wheels. It has a single lever constructed from 2 beans and we use this attachment to push on the mission model.

Calculate the number of rotations you have to do with the motor to rotate the final small 8 teeth driving gear wheel to 1.25 rotations?

What should you as a teacher know when the students are trying to achieve a program and robot attachment that could reproduce their behaviour 9 out of 10 times. 

If you've done the calculation following the previous tutorials you would arrive at a result of 18.75 rotations. But this is not the correct answer. The calculation is wrong, because the math model that we've built, although kind of obvious, is not correct. When experimenting the correct number of rotations would be 37.5. This is a large difference. Two times larger. Exactly two times large. Something should be happening here - and this thing is "planetary mechanism"

This is a 10 out of 10 tutorial, demonstrating the consistency and reliability of the active attachment for switching the engine in this mission. The power is transferred through a system of gear wheels to a lever at the end. We presume that the robot is already positioned.