About this video

This course takes a practical, hands-on approach to teach you all about Model Predictive Control. MPC is crucial for solving a wide range of robotics as well as non-robotics problems. To enhance your learning experience, the author has created a simulator that will allow you to code an entire Model Predictive Controller and see the results of your work in real time. The objective of this course is to help you implement MPC in code and understand the MPC logic intuitively.

All the code and supporting files for this course are available here: https://github.com/PacktPublishing/Autonomous-Robots-Model-Predictive-Control

Publication date:
April 2020
3 hours 49 minutes

About the Author

  • Daniel Stang

    Daniel Stang is a robotics software engineer who holds a master’s degree in mechanical engineering, which he earned for his research in control system design for automotive applications. In his first job out of school, he was responsible for designing motion controllers and stabilization systems for military tank turrets. Daniel has previously written robotic software for a startup based out of Toronto, Canada, and currently writes software for autonomous vehicles in California.

    Browse publications by this author

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