@5:44 we are using Gaussian Kernel here to calculate similarity measure right? I would like to know whether we need to make the assumption that the measurement noise is Gaussian distributed before we do so? I am looking forward to your reply. Thank you.
Hi, We need a function to smoothly give us a score (calculate a weight) for the points based on their distances (closer: much bigger value, further much smaller value), Gaussian kernel is a good function for this purpose, other functions can be used as well and this function is independent of sensor noise model.
Hi Behnam Asadi, I recently made a particle filter for gps navigation based on your tutorial, but particles wont converge to the right positioning, I think the problem is in adding the noise to the kinematic model and the system model. I wonder if you can help me please.
Just as a constructive criticism, please be a bit more clearer about what you want to say. This was very vague and I could not understand much of what you are trying to explain. Because I know how the PF framework works I could try and correlate what you're saying, but it is very vague. Though, I still do not understand how to translate this to code.
Thanks for your comment, I'm working on a new video series with better animations and better audio quality and scripted text, I will try to reflect all feedbacks and comment in my new videos, cheers.
@@RoboCodeHub It would be of great help if you could also speak just a little bit about the code in your website ros-developer.com/2019/04/10/parcticle-filter-explained-with-python-code-from-scratch/ Thank you once again.
I couldn't follow the resampling step.
Very helpful! Thanks Behnam!
Very informative! Thank you very much indeed!
@5:44 we are using Gaussian Kernel here to calculate similarity measure right? I would like to know whether we need to make the assumption that the measurement noise is Gaussian distributed before we do so? I am looking forward to your reply. Thank you.
Hi, We need a function to smoothly give us a score (calculate a weight) for the points based on their distances (closer: much bigger value, further much smaller value), Gaussian kernel is a good function for this purpose, other functions can be used as well and this function is independent of sensor noise model.
@@RoboCodeHub Thank you so much for your reply.
Thanks for the Awesome Videos ! Please keep it up !
Great video!
Where is the Python code?
First link in the description: ros-developer.com/2019/04/10/parcticle-filter-explained-with-python-code-from-scratch/
Hi Behnam Asadi, I recently made a particle filter for gps navigation based on your tutorial, but particles wont converge to the right positioning, I think the problem is in adding the noise to the kinematic model and the system model. I wonder if you can help me please.
thank you, really helpful!!
Thank you so much.
Just as a constructive criticism, please be a bit more clearer about what you want to say. This was very vague and I could not understand much of what you are trying to explain. Because I know how the PF framework works I could try and correlate what you're saying, but it is very vague. Though, I still do not understand how to translate this to code.
Thanks for your comment, I'm working on a new video series with better animations and better audio quality and scripted text, I will try to reflect all feedbacks and comment in my new videos, cheers.
@@RoboCodeHub Thank you very much. Looking forward to it. :-)
@@RoboCodeHub It would be of great help if you could also speak just a little bit about the code in your website ros-developer.com/2019/04/10/parcticle-filter-explained-with-python-code-from-scratch/
Thank you once again.
@@shrinivasiyengar5799 I will explain codes in the new series as well, thanks again for your feedback,
Nice video.. but where is the code?
Check the video description, ros-developer.com/2019/04/10/parcticle-filter-explained-with-python-code-from-scratch/