Particle Filter Tutorial With MATLAB Part 1: Student Dave

[@VinhA]

Here I am, in 2021, watching this video. The face you draw in the beginning of the video reminds me the corona virus ahahah

[@Pradeep1989]

Your videos are really helpful. A small suggestion : I'm particularly sensitive to the "scratching" noise that the pen makes. I'm sure there are many others with similar "weakness" (LOL). So, if possible, could you do a voice-over after you take the video ? i.e. for future videos.

[@TheScienceguy3000]

that is totally a legit concern man. I'm working on getting some better tech so that I can make the videos more enjoy and accessible. i got a few things on my plate that just wont go away, but i have several codes ready to be made into videos that i'm hoping to get out to you guys very soon! thank you very much for the feedback!

[@zhimoli]

love this guy talking! very illustrating!

[@DarleneDranda]

"Know where you've been to know where you're going" Student Dave. "All things are not linear". Got it.

[@TheScienceguy3000]

@Nii Thanks for the comment, yeaaaaaa, I definitely can get a little carried away sometimes! Consequences of an over-extrovert I'm afraid! :( lol (hmm..new word, overovert?) . I'll definitely try to tighten it all up next time. Make sure to watch the last two videos, as they revisit these idea and might help fill in the gaps. happy hunting Bayesian Ninjas!

[@flamingxombie]

This is absolutely excellent stuff. Thanks for the intuitive explanations.

[@andreagil3428]

Yayyyyy!!! Great video!!! I was desperate looking for a good explanation of particle filter!!! Thanks a lot!!!

[@mdkhan20]

Hello student Dave, very nice way to explain... could you please explain bayesian regression with multiple inputs ? such as sensor 1, and sensor 2 ...etc or any other examples ....

[@TheScienceguy3000]

I have flaming Cheetos stains on my fingers.... how embarrassing :-/

[@HannahLau7]

Thanks :) Helped a lot on my computer vision homework.

[@tanajimalusaray]

Got it :) Got the concept after hundreds of attempts elsewhere !!

[@marceltella3814]

Excellent tutorial, that was very intuitive, easy to follow. Thank you very much!

[@jobrown04]

Do you sample a particle randomly on each iteration when producing a weight, or do you check all of the particles?

[@KARAB1NAS]

Do you know any good book to get started with stochastic filtering and code examples ?

[@saswatibhattacharjee7387]

Thank you sir.I want to use Particle filter for robot localization.I cannot understand how to create Particles? I have a odometer data set consist of forward and angular velocity and sensor data set consist of range and measurement. Now using this two raw data set how do I create paticles?

[@niilaye]

good job student Dave have been following your work, is it possible to use other examples. although your theory is sound, it is hard to follow the characters you use in your examples. I think it will help if you take real data, infer/filter the state and finally predict the next state using Bayes, Kalman/HMM/Particle/ filters side by side.

[@Hultkrantz]

Your funny Dave! Keep up the good work!

[@TheScienceguy3000]

check out my website for contact information! :)

[@rajib901]

Keep it up, Boss!!!!!!!!!!!!!!!! Just awesome!

[@cardosawa]

Your explanations are awesome!! Thanks!!

[@nasenach]

just excellent

[@writedan]

Is z the same as H_{t}?

[@pratyasabhui4747]

Could you kindly provide matlab codes for particle filter?

[@sorouredz]

thank you

[@mathias216thor]

Thanks Steve O

[@hadadvitor]

Awesome videos, thanks a lot!

[@homataha5626]

I love you!

[@ferg]

your a legend!!!

[@romitjivani4367]

PF Start at: 1:00

[@PatoroZo]

I like walli the ironic robot

[@jianzheng9614]

nice nice nice!!!!!!!

[@cozmotf7081]

I am from JNLA

[@spider123666]

is download banned??

[@cagdask]

GPS = Global Positioning System.

[@PolkadOfficial]

Are you still alive?

[@Rpaopat]

goo tutorial BUTT!!!!! a lot of high frequency noise (distortion)!!!!

[@OGCRAR]

hi dave. I am a student in Taiwan. I have some question and may I ask you? can you give me your e-mail or I give you mine?

[@RamoSFTT]

Thank you