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DevelopmentSoftware EngineeringRobotics

Autonomous Robots: Model Predictive Control

Learn to make a Self-Driving or Autonomous Car follow the speed limit, pull into parking spaces, and avoid obstacles!
Rating: 4.0 out of 54.0 (375 ratings)
2,090 students
Created by Daniel Stang, MSc
Last updated 6/2021
English
English [Auto]

What you'll learn

  • They will learn how to design and implement a Model Predictive Controller for a Self-Driving Car or Autonomous Vehicle.
  • Make an autonomous car follow the speed limit.
  • Make an autonomous vehicle car pull into a parking space.
  • Make a self-driving car avoid an obstacle.

Requirements

  • No requirements! Knowledge of coding or Python will help but not required.

Description

Learn to Program A Self-Driving Car In My Online Course!

In this course you will make an autonomous car drive itself! You will create an algorithm that will give the car the ability to:

  • Follow the speed limit.

  • Pull into parking spaces.

  • Avoid obstacles.

If you love cars (or robots) and want to see if you can code a car that can park, control its speed, and avoid obstacles all on its own… this course is for you.

Whether you have extensive coding knowledge or just an interest in robotics, this course will take your skills to the next level. Most importantly, you’ll have fun throughout the process.

You won’t just learn about the concepts, you will have a chance to actually implement them, test them, and see the results in real time. Learning sticks better when you put it into action, and seeing results is what makes the process so rewarding. With my custom simulator, you can see how your algorithm would work on a real car.

Model Predictive Control is a useful concept to understand for all areas of robotics, but learning about it doesn’t have to be a drag. It also doesn’t have to be impossible to understand. I break down each concept to be fully digestible for every kind of student.

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.

What are you waiting for?

Enroll now and see what you can learn.

Who this course is for:

  • Roboticists looking to add another powerful tool in their robotics arsenal.

Featured review

Abhishek Dhar
Abhishek D.
190 courses
61 reviews
Rating: 5.0 out of 52 years ago
It is almost impossible to imagine that something like "Model-Predictive-Controller" can be explained in such lucid fashion. If you have a knowledge of AI/Deep Neural Network (Especially cost function) then it will help you out immensely to grasp the huge implication and concept of cost function in MPC. The concept is too powerful and instructor is not only knowledgeable but also has tons of experience in this field, which shows up when he illustrates a given problem statement.

Instructor

Daniel Stang, MSc
Robotics Software Engineer
Daniel Stang, MSc
  • 4.2 Instructor Rating
  • 1,408 Reviews
  • 33,731 Students
  • 7 Courses

I have a masters degree in Mechanical Engineering which I earned for my research in control system design for automotive applications. 

My first job out of school I was responsible for designing motion controllers and stabilization systems for military tank turrets.

I previously wrote robotic software for a startup based out of Toronto Canada.

I currently write software for autonomous vehicles in California.

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