Probablistic Robotics Lab 0: Python Warmup

This lesson module follows up on Lecture 0: Introduction from Dr. Wolfram Burgard's (Albert Ludwig University of Freiburg) Introduction to Mobile Robotics syllabus page. The lab / exercise materials are borrowed heavily from the Lab worksheets on that syllabus page.

Much of the material is also part of the seminal textbook Probabilistic Robotics.

A quick recap of the Probabilistic Robotics course:

• This course teaches probabilistic approaches to sensor modeling, motion modeling, localization, mapping, simultaneous localization and mapping (SLAM), and path planning - all the fundamental disciplines to self-driving, autonomous cars and vehicles.

The purpose of this specific lesson module is to:

1. Get used to Python programming using the Hadabot development environment

2. Get acquainted with a couple of Python coding tools:

   1. The Python NumPy module

   2. The Python matplotlib plotting module

   3. Using Jupyter Notebooks to create interactive Python code

Pre-requisites:

1. Familiarity with NumPy - nothing more than a glorified math library for Python.

   Here's a solid NumPy tutorial (feel free to search 'numpy tutorial' for others).

2. You have done the Hadabot FREE ROS 2 intro lessons.

3. You have the Hadabot Docker ROS 2 software suite installed

Additional materials needed:

1. N/A

Let's get started!