10:03:21 From  James Newton  to  Everyone:

The thing about traveling by air is the other passengers. They can really make life hell.

10:05:57 From  Steven Kaehler  to  Everyone:

Yah. Those other passengers sure make things crowded!

10:09:05 From  John Jennings  to  Everyone:

RoboKame’s 2nd run of Popcan Challenge https://www.youtube.com/watch?v=FRkc9BOGA3o

Complete recording of Popcan Challenge https://www.youtube.com/watch?v=FRkc9BOGA3o 

10:09:13 From  James Newton  to  Everyone:

VIdeo is here: https://www.youtube.com/watch?v=FRkc9BOGA3o 

and I added a comment with timestamps to each run (I think) and the wrong name.

10:09:30 From  James Newton  to  Everyone:

LOL… sorry ,JJ, posted before I saw your link.

10:10:59 From  John Jennings  to  Everyone:

oops, RoboKame’s 2nd run of Popcan Challenge https://youtu.be/UAPeGdxWZig 

10:11:40 From  John Jennings  to  Everyone:

Facebook Group for Popcan Challenge https://www.facebook.com/groups/PopCanChallenge 

10:13:26 From  James Newton  to  Everyone:

10:14:26 From  James Newton  to  Everyone:

http://techref.massmind.org/techref/method/ai/LinearRegresion.htm 

10:23:10 From  Lloyd Moore  to  Everyone:

10:26:56 From  James Newton  to  Everyone:

I’d love to hear “lessons learned” from the pop can challenge competitors.

10:28:26 From  John Jennings  to  Everyone:

WiFi Analyzer app Android

https://play.google.com/store/apps/details?id=abdelrahman.wifianalyzerpro&hl=en_US&pli=1

10:40:30 From  Nathan Kohagen  to  Everyone:

https://en.wikipedia.org/wiki/Smith_predictor

10:41:46 From  James Newton  to  Everyone:

Thanks for that link Nathan!

10:43:49 From  Nathan Kohagen  to  Everyone:

I saw it used in a proprietary control loop that I can’t share the entire context because of work reasons.

10:44:39 From  Nathan Kohagen  to  Everyone:

That’s used for compensating for delay in loops.

10:46:25 From  Nathan Kohagen  to  Everyone:

Kalman Filters can be used to compensate for erroneous data coming back from sensors.  The different types of Kalman Filters dynamically switch back and forth between the predictive model of your system and the actual sensor data.  They are used a lot for sensor fusion in IMUs / 9-DOF sensors.

10:47:42 From  James Newton  to  Everyone:

KF’s are great.

10:47:59 From  Chas Ihler  to  Everyone:

Reacted to “Kalman Filters can b…” with ❤️

10:48:32 From  James Newton  to  Everyone:

Reacted to “Kalman Filters can…” with ❤️

10:48:40 From  James Newton  to  Everyone:

Reacted to “https://en.wikiped…” with ❤️

10:50:29 From  Nathan Kohagen  to  Everyone:

You’re describing TDD

https://en.wikipedia.org/wiki/Test-driven_development

10:50:32 From  Terry James  to  Everyone:

Replying to “KF’s are great.”

KF?

10:50:51 From  Chas Ihler  to  Everyone:

I have to drop, have a great weekend all!

10:51:49 From  Terry James  to  Everyone:

Replying to “I have to drop, have…”

CYA

10:52:33 From  Nathan Kohagen  to  Everyone:

KF:= Kalman Filter

EKF:= Extended Kalman Filter

10:52:36 From  James Newton  to  Everyone:

Replying to “KF’s are great.”

Kalman Filters

10:54:04 From  James Newton  to  Everyone:

KFC Kalman Filter Chicken

10:54:22 From  Colin Leuthold  to  Everyone:

Reacted to “KFC Kalman Filter Ch…” with 😂

10:57:04 From  Terry James  to  Everyone:

Search on KFC “The Chizza”

10:57:20 From  Terry James  to  Everyone:

https://www.wdsu.com/article/best-of-both-worlds-kfc-combines-fried-chicken-and-pizza-for-the-chizza/8692564

11:04:57 From  Nathan Kohagen  to  Everyone:

https://www.do178.org/

https://en.wikipedia.org/wiki/DO-178B

https://en.wikipedia.org/wiki/DO-178C

11:13:05 From  Bob  to  Everyone:

James,  I found my neural network code.  It is in C++ under the Visual Studio environment, and uses a couple of external packages: math kernel library (MKL), Intel performance primitives (IPP), and rapid JSON.  It isn’t well commented code either.  If you still want it, I can put it on DropBox.

11:14:23 From  James Newton  to  Everyone:

Replying to “James,  I found my…”

Yeah, I’d love it! I’d rather see it on github, but if you are only willing to share it privately, please include an email or something so I can ask for permission to share it under some conditions if I find a way to make use of it in a class?

11:15:39 From  James Newton  to  Everyone:

Is this the right slide?

11:16:00 From  Lloyd Moore  to  Everyone:

Looks ok from my side

11:16:18 From  Bob  to  Everyone:

If you are really looking for a method of doing polynomial curve fitting, the algebraic method is actually faster and more accurate.  Neural networks just approximate the algebraic approach.

11:16:19 From  Lloyd Moore  to  Everyone:

right now is slide 13 of 75 – are yours updating?

11:16:41 From  James Newton  to  Everyone:

I’m still seeing the Vine robots overview, and Charlie is talking about very different things.

11:17:09 From  Lloyd Moore  to  Everyone:

Try disconnecting and reconnecting – sounds like your screen share may have frozen….

11:17:32 From  Lloyd Moore  to  Everyone:

now at slide 14 if that helps

11:17:34 From  Terry James  to  Everyone:

Slide just changed for me.

11:18:02 From  James Newton  to  Everyone:

Ok, that’s better.

11:18:08 From  Lloyd Moore  to  Everyone:

Reacted to “Ok, that’s better.” with 👍

11:18:36 From  Thurman Gillespy  to  Everyone:

Dune Sandworm!

11:24:42 From  Nathan Kohagen  to  Everyone:

Reacted to “Dune Sandworm!” with 👍

11:56:44 From  Bob  to  Everyone:

Here is the DropBox link for the neural network code.  My email is robertphiggins@comcast.net.  I suspect you will need some explanation to get it operating and how it works.

https://www.dropbox.com/scl/fo/wblgjpviwoe5185lrkub6/h?dl=0&rlkey=k7epg821s4dmzfiid6f80096t

12:11:49 From  Scott  to  Everyone:

Did I hear you say “$8” about this motor?  The motors at https://www.pololu.com/search/compare/60  look similar, but are $20

12:12:18 From  Nathan Kohagen  to  Everyone:

Thank you Charlie!

12:13:45 From  Terry James  to  Everyone:

How slow do you want the robot to move?

12:14:33 From  Terry James  to  Everyone:

The air bladder robot should be able to move a lot faster

12:15:41 From  Terry James  to  Everyone:

Like exploring rubble of a collapsed building

12:15:58 From  Terry James  to  Everyone:

Search and rescue robot

12:27:05 From  Charlie Xiao  to  Everyone:

Scott, that looks correct

12:27:27 From  Charlie Xiao  to  Everyone:

You can also find similar but cheaper motors

12:27:30 From  Charlie Xiao  to  Everyone:

on amazon

12:27:31 From  Charlie Xiao  to  Everyone:

12:27:39 From  Terry James  to  Everyone:

Thank you again.