Hi guys, Matlab scripts and the technical report used in this tutorial can be found here: www.patreon.com/user?u=80399744 www.steppeschool.com/products/communities/steppeschool-miscellaneous
Hi mate, really appreciate for your valuable content. It is really helpful to understand the concept and the flow is just superb! One thing to add, in the line: velocity = linspace(0.0,0.1,num_samples); if you would inverse(transpose) that definition the plot at the end would be more sensible which has actual and encoder plots. Prediction step looks incorrect because you create the velocity_encoder matrix as 300x300 instead of 300x1. Thanks again for this valuable post!
Hi guys,
Matlab scripts and the technical report used in this tutorial can be found here:
www.patreon.com/user?u=80399744
www.steppeschool.com/products/communities/steppeschool-miscellaneous
Thank you! The concepts are explained neatly, and the video is one of the best-structured ones I have watched on Kalman Filters!
Great way of teaching. Carry on brother.
Hi mate, really appreciate for your valuable content. It is really helpful to understand the concept and the flow is just superb!
One thing to add, in the line:
velocity = linspace(0.0,0.1,num_samples);
if you would inverse(transpose) that definition the plot at the end would be more sensible which has actual and encoder plots. Prediction step looks incorrect because you create the velocity_encoder matrix as 300x300 instead of 300x1. Thanks again for this valuable post!
Great to hear!
Cool channel
thanks😀