Video tutorials, Courses, Materials and Programs

There comes a time when you need to program the robot to "follow a line, but if another sensor detects something you would like to stop, do some work, and then continue following the line". This is applicable to competition robots as it is applicable to real-life robots. 

There comes the State Machine Pattern. An advanced and very powerful concept that allows you to easily implement complex robot behaviours with a simple, well-organized, extensible, bug-free program where the robot could be in 1,2, 10 or 100 states and you will still be able to manage the complexity of the world around the robot.    

The course introduces students to the programming language Python. We use LEGO Mindstorms EV3 Robots. Python is a popular programming language. It could be used for introducing students to programming, for academic studies, for developing machine learning algorithms and as a general-purpose language. 

During the course, students learn how to read and how to develop Python programs. They use an Integrated Development Environment called Visual Studio Code. Robots are programmed to perform interesting and funny tasks like "bringing you water". The level ends with competition on a playing field with boxes.

In the second level of Python for EV3 robots, students learn in-depth the touch sensor. The sensor is used as an input device for manual control of machines, as well as a sensor for autonomous robots. In a pair of lessons, students build a control panel for the grabber and the movement of a crane. Programming wise, students learn how to fork code with "if-else" constructions, how to create conditional and forever loops with "while" and how to negate conditions with "not" operator. In the end of the lesson, robots can detect obstacles and avoid them, so that they traverse a simple labyrinth.

This course is designed for students, mentors and teachers that are completely new to LEGO Mindstorms EV3 robots and would like to start using them to learn, in classes or at competitions. It is quite different from previously built resources at FLLCasts because it makes no assumption on any previous knowledge and tries to introduce everything step-by-step.