Autonomous Robots: Path Planning

Use A* Search (A-star Search) to find a route between any two locations in New York City, just like Google Maps does!

4.85 (87 reviews)

Udemy

platform

English

language

Software Engineering

What you will learn

Enough about A* Search (A-star) and Path Planning to defend it in an interview

General robotics systems knowledge

Python and its usefulness in robotics

Why take this course?

Ever Wondered How Google Maps Calculates the Route To Your Destination? Learn How To Design A Path Planning System of Your Own!

Knowing how to plan a path between your current location and your goal is an essential skill whether its for a self-driving car / autonomous vehicle, a roomba, or even an app like Uber, Waze, or Google Maps.

In this course you won't just learn concepts but will also have a chance to implement, test, and a see the results of your work in real time. For the final project of this course you will need to plan a path between any two locations in New York City. Like Frank Sinatra says, if you can plan a path there, you can plan one anywhere!

With this course, you can level up your knowledge, add an additional skill to your robotics arsenal, and do it all through a program that feels more like a game than it does a class.

This course will teach the A* search algorithm, which is a fundamental robotics algorithm. This algorithm is so fundamental it was even used on the very first mobile robot, Shakey the Robot.

What are you waiting for?

Enroll now and see what you can learn.

Screenshots

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Reviews

Taha

September 2, 2020

It was a splendid experience and an excellent platform for me to learn alot of new things. Really loved the method of teaching and hope to make use of what I learnt.

Saajid

March 9, 2020

The concept of path planning presented in this course is too general and applicable on almost any thing, so if you are a game developer, a mathematician, a physician ... etc. this course is also for your. I wish if the instructor was coding the solutions rather than reading them line by line, and consider the direction of the streets (bidirectional/unidirectional ), or consider the crowdedness of the streets that lead to the destination, or traffic lights, or reported accidents ... etc. but these were all not considered in the presented algorithm. Yet, the instructor is knowledgeable about the subject, and he has a nice style of breaking down the difficult part and present them in a simple way. Anyways, there is always a room for improvement .. and I wish the author keeps updating this course ...

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