Uploaded July 2021 | Updated September 2026, 8 hours ago
Free Udemy Course (Motion Planning): udemy.com/course/an-introduction-to-sampling-based-motion-planning-algorithms
Project Code: github.com/Vinayak-D/efficient_MPC/tree/master
Efficient MPC Algorithm: arc.aiaa.org/doi/pdf/10.2514/1.52162?casa_token=FfyVyxsEEYwAAAAA%3AnqlGuDKbibdBNpunkFmSd21fgcE5sunM_cgq3IUDdpNU5BuH6QdtnKAQvCpjFtKMAtoYSJ4a1Tc&
My MPC Paper: ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9282815&casa_token=_ZjJSJCMdbIAAAAA:jqdPZmDU6Bimt2B5SCRTll9oUWtTsl2l7TthOW3wJUKysgYpat88q9Jludqtwv1XztB7V7912Q&tag=1
Python Controls Library: python-control.readthedocs.io/en/0.9.0/intro.html#installation
Anaconda for Python: anaconda.com/products/individual
Hi everyone!
In this video you will learn the basics of MPC and how to put together a quick simulation in Python without using any optimization toolboxes and solvers, so you can learn the process from scratch. Note that if you're using a version of Python which is not 3.7, then you may need to change the syntax. Numpy, scipy and matplotlib will be needed.
The MPC algorithm used will be the efficient MPC algorithm originally developed by P.W. Gibbens and E.D. Medagoda at the University of Sydney. This algorithm is a little less complex than the standard integral action MPC methods, however the underlying concept is identical in all methods of model predictive control.
Thanks for watching!
Sorry for the delay in uploads, as I am moving cities and just graduated from University!
~~My Udemy Courses on Motion Planning / Navigation / Trajectory Planning:
udemy.com/course/autonomous-robots-nonholonomic-motion-planning-algorithms
Buy Coffee: buymeacoffee.com/vdengineering
My Instagram: instagram.com/vinayak_desh
My Website: vinayakd.com
Free Udemy Course (Motion Planning): udemy.com/course/an-introduction-to-sampling-based-motion-planning-algorithms
Project Code: github.com/Vinayak-D/efficient_MPC/tree/master
Efficient MPC Algorithm: arc.aiaa.org/doi/pdf/10.2514/1.52162?casa_token=FfyVyxsEEYwAAAAA%3AnqlGuDKbibdBNpunkFmSd21fgcE5sunM_cgq3IUDdpNU5BuH6QdtnKAQvCpjFtKMAtoYSJ4a1Tc&
My MPC Paper: ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9282815&casa_token=_ZjJSJCMdbIAAAAA:jqdPZmDU6Bimt2B5SCRTll9oUWtTsl2l7TthOW3wJUKysgYpat88q9Jludqtwv1XztB7V7912Q&tag=1
Python Controls Library: python-control.readthedocs.io/en/0.9.0/intro.html#installation
Anaconda for Python: anaconda.com/products/individual
Hi everyone!
In this video you will learn the basics of MPC and how to put together a quick simulation in Python without using any optimization toolboxes and solvers, so you can learn the process from scratch. Note that if you're using a version of Python which is not 3.7, then you may need to change the syntax. Numpy, scipy and matplotlib will be needed.
The MPC algorithm used will be the efficient MPC algorithm originally developed by P.W. Gibbens and E.D. Medagoda at the University of Sydney. This algorithm is a little less complex than the standard integral action MPC methods, however the underlying concept is identical in all methods of model predictive control.
Thanks for watching!
Sorry for the delay in uploads, as I am moving cities and just graduated from University!
~~My Udemy Courses on Motion Planning / Navigation / Trajectory Planning:
udemy.com/course/autonomous-robots-nonholonomic-motion-planning-algorithms
Buy Coffee: buymeacoffee.com/vdengineering
My Instagram: instagram.com/vinayak_desh
My Website: vinayakd.com
