These Jupyter Notebooks are intended to support the learning of basic concepts of mobile robot control via Python coding. They focus on the differential-drive mobile robot.
The notebooks can be used as support material for the Robotics Simulation Labs without the need of installing Webots. They can be useful to understand the fundamentals of the corresponding topic, especially because they allow step-by-step execution and experimentation of the implemented functions.
- Odometry-based Localization for the differential-drive robot
- Implementation of simple robot behaviors for mobile robot control
- Mobile Robot Control with PID for a go-to-goal moving controller
- Dijkstra's Algorithm for Robotic Path Planning
- Digital Image Processing - fundamentals and basic functions
Clone (or download) this repository to your computer and run the Jupyter Notebook cells in a sequence, from top to bottom.
- Python 3.10 or higher
- Jupyter Notebook
- NumPy
- Matplotlib
- OpenCV (for Digital Image Processing)
This project is licensed under the terms of the MIT license.