Autonomous Path Planning

Description

An important aspect for mobile robots or self-driving cars is to plan a path to get from point A to point B. This is true for vacuum cleaning robots like Roomba as well as a self-driving car like Waymo.  In this course we will learn how to plan a path for robots. We will go over 3 algorithms - Breadth First Search, Depth First Search and A star using distance heuristic. We will go over how they work and even implement them. Plus, we will visualize the planner. All of the code is in Python 3 and it is made available via the Resource section.

This course is about learning Path Planning Algorithms used for Navigation by autonomous mobile robots. This is a good entry point to get started with Robotics. This course is designed to be more practical. You will learn the algorithms and then implement them in code. The code in this course is in Python 3. You will have access to all the code through the resource section. You can always implement them in other programming language as well. As mentioned, the course is taught with practicality in mind, so we will also create visualization using matplotlib. This way you can understand the algorithm better and see it work in action.

Learning objectives:

• Learn about path planning concepts such as path and grid maps

• Understand 3 different path planning algorithms

• Implement 3 different path planning algorithms in Python

• Have a working set of planners with visualization

Path planning algorithms covered:

• Breadth First Search

• Depth First Search

• A star using distance heuristic

Programming language used: Python 3

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