Particle Filter - 5 Minutes with Cyrill

The particle filter explained in 5 minutes
Series: 5 Minutes with Cyrill
Cyrill Stachniss, 2020
Credits:
Video by Cyrill Stachniss
Intro music by The Brothers Records

[@testme2026]

Love it, please please keep the 5 min explanation. amazing

[@drillsargentadog]

Beautiful explanation and great idea for a series. I had looked at several papers and strongly thought this is what was going on, but all of them overcomplicated the basic idea.

[@ricojia7322]

Like the vibe! Cool vid!

[@rhushabh1]

Thank you for an easy explanation

[@marcomarco8084]

perfect thank you for the video :)

[@roy1660]

Please discuss feedback particle filter

[@tenminutetokyo2643]

Thanks for not shouting.

[@alonbegin8044]

so it basically depend on an obscure model to define it's weights . what if the model is wrong..?
can it update the model logic, given maybe we want certain reward?

[@nayabrasul]

If model is wrong, filter will not converge (It means your estimation has very very low certainty or confidence).

[@CyrillStachniss]

Correct, if you use a wrong observation model, you cannot expect your filter to converge to the right solution.

[@zuhair95]

@@CyrillStachniss
Thanks.
So,Is the Pose graph algorithm (Least squares ...) not care about the observation model ?

[@treystewartspacegirl6504]

Anough said.

[@weirdsciencetv4999]

This sounds a lot like particle swarm optimization, other than the weighting factor.

[@CyrillStachniss]

Not really, it is a proper recursive Bayes’ Filter

[@weirdsciencetv4999]

@@CyrillStachniss i’m just saying it bears resemblance to me. Great lecture!

[@orikaplan5233]

Thanks. I needed that explanation.
One comment - please try to speak more clearly, as some of the words are inaudible