NVIDIA JetBot: Jetson Nano Vision-Controlled AI Robot

Jetson Nano “JetBot” machine learning robot review and demo. Includes hardware, software, Jupyter Lab notebooks for executing Python code, collision detection examples, and some introduction to training a neural network model.
The JetBot shown was supplied for review by NVIDIA, but this is not a sponsored video. If you are interested in getting a JetBot, I would strongly recommend starting on its NVIDIA web pages here: developer.nvid...
The JetBot Wiki, which contains all of the information required to build, setup and run vision recognition and machine learning on a JetBot, is here: github.com/NVI...
There is also info on full JetBot kits here: www.nvidia.com...
My previous review of the NVIDIA Jetson Nano SBC is here:
• NVIDIA Jetson Nano
And my “Jetson Nano: Vision Recognition Neural Network Demo” video is here:
• Jetson Nano: Vision Re...
I also have an introduction to AI video here:
• Explaining AI
More videos on single board computers and broader computing topics can be found on the ExplainingComputers channel: / explainingcomputers
You may also like my other channel, ExplainingTheFuture, at: / explainingthefuture
#JetBot #JetsonNano #NVIDIA #ExplainingComputers

[@johncnorris]

nVidia: "It just works!" Explaining Computers: "After extensive assembly and configuration it does."

[@ExplainingComputers]

So true. NVIDIA were very helpful during production of this video, but production lasted longer than on many other videos. :)

[@jasontiscione1741]

​@@ExplainingComputers Probably starting when you first plug it in and Ubuntu thinks you have a black and white TV

[@bosstroll9019]

If Mr. Scissors found a way to mate with it and breed, they would rule Earth by Thursday

[@VeryUsMumblings]

1st choice: Ruke the world. 2nd choice: make lots of unboxing videos!

[@brianm6337]

Meh- they can have the earth. Kids will be a bunch of little cut-ups, though.

[@brianm6337]

@b gg Explaining Computers does. ;D

[@cinnabarsonar2072]

Gives a whole new meaning to the term "hardware porn" I'll grab my coat.

[@digitalghosts4599]

Jetson nano is a ridiculously powerful platform for the price. I'm using it for high speed machine vision to monitor manufacturing process in real time and this beauty can record 200fps in 720p and it can easily process 100 frames per second with a simple detection algorithm. We are living in the future. 10 years ago this would be a huge challenge even for a desktop PC not to mention that there was nothing in place to capture such high frame rates in real time and process them simultaneously.

[@ExplainingComputers]

Great feedback, thanks for sharing. I share your appreciation of the Jetson Nano -- it is a really great board.

[@travelstories7530]

how do u make that simple detection algorithm is is based on those green square u defined in the algorithm?

[@hussainbharmal5998]

How is it going on, after 3 years? Have you been using it to date in other applicationa too?

[@JohnK68]

Actually it's not powerful at all. A nvidia tegra T210 with a GM20B GPU it's a toy. Also the OS on the board is way to heavy for the system.

[@NataLia-yb6vm]

Now I no longer need a Tesla for self driving car. I can make my own haha

[@chriholt]

All I can say is "Wow!" Very impressive hardware and software package!

[@michelfilion5482]

Amazing...If anything, AI shows us how we take for granted our own complex cognitive abilities.

[@maxvaistuk5493]

www.3dmaxprinter.com/shop/do-it-youself/rc-robot-car-with-ultrasonic-sensor-for-education-robotics-robotic-car/

[@gpalmerify]

This video helped me appreciate my Subaru's "Eyesight" system even more. Thank you Chris.

[@willyarma_uk]

This is very cool! Now can you program it to search for a rabbit?

[@iluvrgb]

Back again with another interesting video. The Nvidia Jetson Nano is interesting

[@AnthonyCook78]

What a waste of time!

[@chadwick2629]

@@AnthonyCook78 How?

[@cinnabarsonar2072]

For some reason I want to try and turn this into a glorified cat toy.

[@BlenderRookie]

Wow, I wanna play with that. Plus the commands seem rather intuitive. The commands kinda remind me of that old graphics program called Logo Writer.

[@johnsweda2999]

Instead of having a camera to measure edges wouldn't it be better to have an optic measurement, you could use form a mouse, so it can count how many steps / rotations it's doing and work out the area surface and produce a map. This could be used in conjunction with the camera, I mean a camera doesn't know the area it's patrolling with a counting system it is easier for it to work it out I would have thought

[@ExplainingComputers]

I am sure that you are right that using/adding sensors other than vision would improve matters. :)

[@BharatMohanty]

I like this video sir, very informative..I made a terminal controlled rover but I without microcontroller or SBC ..

[@qzorn4440]

wow very nice project. 🥳 I sure miss the old Heath-Kit days. When it was a turn-key project with everything in a box and a great manual. Need a Teach-Kit company to replace Heath-Kit?

[@ma-burke]

(Blib #6336 in the EC digiverse.) "...to see what it can do. So let's go and take..." _time passes_ _much time passes_ _years in fact_ "... a closer look."

[@stuartg40]

Why does it only turn left?

[@ExplainingComputers]

Only because that's what this sample program that runs this neural net is programmed to do (the neural net reports free or blocked, the code takes this input and applies the "turn left if blocked" rule. I can turn the other way! :)

[@judgeguilty]

It's due to the Zoolander Paradox kzbin.info/www/bejne/e161k6d5jbmgmZY

[@codycast]

b gg na. It would have come with a speaker to call everyone racist, complain the whole time and demand $20/hr to move in circles.

[@marcombo01]

@@ExplainingComputers and could you program it to take the most optimal decision to give it a more natural behavior?

[@NataLia-yb6vm]

It could randomize left or right if they both within "acceptable range" or take the highest value if not that proximate or equal.

[@MegaZiggo]

This is quite interesting. I worked as a Field Engineer for a company call Intelligent Reasoning System Inc. back in 2001/2002. They made capital equipment for installation on an electronics manufacturing line for use in Automated Optical Inspection of PCBs. We used an early form of image training (the founders of the company also wrote the software for the terrain tracking algorithms for the Tomahawk cruise missile and adapted those to this application) with statistical analysis within a set standard deviation. The system worked well and it is very similar to what you demonstrated here with the Jetbot. We would train examples of good images and bad images of electronic components on a PCB and for each false call, we would train that as a bad actor. Over the course of the manufacturing run, the system would become more and more accurate. Good stuff indeed. Keep the good material coming! I am considering getting one of these to teach my daughters not only Python, but machine learning in general...

[@CodyBanks10]

"Something like that" is a buzz phrase I will be using from now on.

[@technicalcreativityandtric687]

Hello UNCLE how are u Your this video is amazing Very very good project thank you

[@0dyss3us51]

Would love to see you expand on this robots capabilities! :D how about a hand that can grab drinks from the fridge? Okay a little ambitious, buuut possible I guess :D

[@Tr3xShad]

Impressive. I was wondering if the nano module can be used on Xavier NX developer kit, as the Nvidia documentation state they share same pin out. Already have the nano module but eyeing the NX development board with it support for M.2 drives support

[@hangaming1978]

Sorry sir, please add subtitle indonesia. Thank you.

[@Osmanity]

Totally mindblowing video! I just wish that Nividia sold pre-assembled JN-AI Robots versions so that we can just focus on building the software and learning more about training a neural network which is for me the main goal. Thanks as always for an interesting video!:0

[@ExplainingComputers]

Since I made this video there are some suppliers selling kits, which makes things somewhat easier. I've added the link to the video description.

[@Osmanity]

@@ExplainingComputers thanks

[@peterjansen4826]

I boycott Nvidia because of their shenanigans (physX via X87, Gameworks, GPP...), I prefer to use AMD-GPU's for something like this.

[@elmong9124]

For the AI ones , google coral and jetson nano offer similar performances, GPU and TPU is perfect for AI work loads , it’s not running from any cloud , it is inferencing(running) the AI itself

[@elmong9124]

I would also want some amd gpu AI stuffs but unfortunately they do not offer any development kit for this kind of workload

[@peterjansen4826]

@@elmong9124 I don't doubt that AMD is working on it with their open software stack. These are very interesting applications.

[@dancingCamels]

Would be interesting to see the least number of training data images it takes to work effectively.

[@stanislavkotzev4157]

7 years later he hasn't changed at all :D just watched the big data video

[@williama29]

I like robots and AI I wouldn't mind having Mr. Scissors as a AI robot

[@Techn0man1ac]

It's alive, it's aliiiive

[@retrorobodog]

cool :):):)

[@didiyontingwi]

Interesting.. I like this product.. Thanks.. Greetings from indonesia..

[@ExplainingComputers]

Greetings back from the UK. :)

[@CRTECHPE1]

nice one. after 5 year, those things can be much easier

[@SlowPCGaming1]

It could make for a neat cat toy. Teach it to perform different stunts or tasks based on which animal it sees under a variety of conditions. Or toddlers, puppies, any small silly creature with curiosity or skittish behavior. Is there a full cover for that bot? I wonder how well it would do on detecting stairs that are carpeted or feature a confusing geometric pattern.

[@ExplainingComputers]

There are lots of JetBot designs now, all for makers to but together and modify. I love the idea of a cat toy! :)

[@statorworksrobotics9838]

Another fantastic video but perhaps it helps to highlight the problems of current AI approaches. Bandwidth and data hungry, non transferable knowledge. Whereas a simple symbol based heuristic solution would probably suffice.

[@smartassist9700]

I am finding sponsors! The used mower I purchased. The brand Company has not produced in 7+ years. However, without asking they shipped me many new parts they had stored for that model mower. I will purchase the remaining 3-4 small items from them. Mower will be better than NEW.

[@bradscott3165]

Jetbot should be named Dale because he only turns left.

[@Bippy55]

This is one of your BEST videos. I'd favor the company creating a kit of parts. Like Heathkit used to. Then you'd know the parts should work after assembly. I'd also like a BEGINNER's PRIMER on programming the neural net robot. But overall, "Bravo!"

[@ExplainingComputers]

There are now kits -- see links in video description! :) Glad you like this video. It is not one of my most popular. :(

[@smartassist9700]

Thank you yet again! THAT IS PART OF MY "KING PROJECT". i want to automate lawn tractor mower to mow lawn using visual and distance sensor for obstacles but program to mow in a pattern. Learning properly to go around objects on eventually both sides to keep mow pattern. One thing I have not figured is to read where grass has been cut verses the next cutting row of taller grass. Unless it uses "mapping" and location to determine the next row. That would make sense. The servo motors for steering and such I have to figure out with experts in that area. There is one company that has pattern mowing already. I am discussing selling "kits" to install on older mowers already purchased. They seem interested. but that will have to wait as I have to many automation things to complete first. Also paint a workshop barn/office. Insulate, run wiring, and interior walls and set up work table, hand tool storage organized on wall. (I am building skeletal arm that requires servo motors camera and nvidia to run it. Helper Arm to pull tools and put them up when finished. I have 4 months to also setup garden, water retention, sensors pumps water lines. This year with no garden I grew the most delicious Pineapples, Lemon grass, tomatoes, and seasoning herbs...playing around. I need some automation interested people to assist with this project. amazing the blue print for automation has grown substantially. I guess it will take 2-3yrs to implement fully. I would prefer that 24hrs a day over any other option to spend time on.

[@Peter_Enis]

Use bluetooth adapters in the corners of the garden as "gps-beacons". Now you can use the mower to print text or pictures in your lawn like a big plotter.....?

[@62shalaka]

Sundays are exciting; I never know what Chris will present to us next. Great as usual!

[@adaemus333]

Good robot. Robot move only straight and turn left. For this hardware its not poor. Again nice video.

[@ExplainingComputers]

The robot can move/turn as required, the code here just says "straight forward or turn left if the neural net reports blocked".

[@MichelMorinMontreal]

I forgot.... I guess you've already had a chance to take a look at the "new kid" from Intel.... up-board.org/upsquared/specifications/

[@ExplainingComputers]

Does look good. :)

[@nustada]

Nature always has at least two cameras "eyes", is there a way to add another camera? Stereoscopic AI would be exponentially more powerful than not. Also feedback sensors for the wheels and preferably shocks to implement AI on terrain?

[@ExplainingComputers]

A second USB camera could potentially be added.

[@irenew6520]

Please can you show a demo where the robot also runs clockwise. Is it possible for you to duplicate the code and adding a flag for switching randomly left or right or better with AI ? Otherwise this official demo looks a bit sufficent, nor than great. THANKS

[@nocturnalnights27]

Metal... ...Gear?!

[@bosstroll9019]

A weapon to surpass Metal Gear

[@八音-m9d]

英伟达确实是好东西就是贵了一些，但是越贵的东西越好吗

[@TheTwick]

Thank you for this video. The definitive test would be to train it to follow the voice command : “Robot, get me a beer!”

[@phildodd9942]

A useful presentation you have given us, pointing out that AI can be other things apart from analysing numbers or text ! In fact you've made us sit up and take notice ! So THAT'S how a self-driving car parks itself ! Thank you for this enlightening demo !

[@CTCTraining1]

I fell happier to know my Tesla is unlikely to fall off the table.

[@fecklarjenkins2549]

Should name it Ricky Bobby thinks it’s a NASCAR and can only turn left LOL

[@nystudiolofiinstrumentalre726]

Hi. Please help me to code 14 servo and 2 dc motor in python and raspberry pi4 .i bought it recently and tried to do but unsucessful i am losing my interest and i dont want

[@ExplainingComputers]

I have a whole series here on "Rapberry Pi Robotics", and another on my "Pi Devastator Robot".

[@GregSilverado]

years from now our robot overlords are going to remember your kindness to one of their little ones.... they will be merciful to you

[@ExplainingComputers]

:)

[@waynerobarge8543]

Thank you for doing this video. I have played with the nano but have not looked at the robot feature. Question: the robot seemed to favor turning in one direction for avoidance most of the time. Is that a random variable - like flipping a coin - or is the robot taking additional information before making the decision which way to turn?

[@ExplainingComputers]

The robot is simply following the rule "if neural net reports blocked, turn left".

[@donaldduck5731]

How with one camera can it assertain depth? This nvidia is so frikin clever, I need one of these robots, if only to realise how ignorant and dumb I am.

[@ExplainingComputers]

It cannot measure depth with one camera. It is using a neural net to pattern match what it can see against what is has learnt a blocked pathway looks like. Which is rather clever! :)

[@Iamnotheretocompete]

i saw a floppy drive!

[@vermontmario]

i like your videos , thank you

[@twmbarlwmstar]

Impressive, I managed to write a simple IA script this week, as in copy it and get it to run, and that was a real first. It didn’t really do anything as such, but I could see the code working and that helped me get my head around things. Really, I struggle with all this and always will but just making some sense of it helped. My 10-year-old son will hopefully do better and having something like a robot will be more meaningful than my naming game. A £100 price point seems about right for this, especially as it should be extensible and it is the code that is what it’s all about, and you need affordable so there's access. Hopefully you can have say a team of 4 kids with one Jetson to build a project. £25 each isn't a complete killer over a year, say £1 a week- even those on very low incomes should be able to support that. To be honest though, I’ll always be a hardware man at heart so the Jetson is a bit lost on me, I’ll only turn it into a Kodi box or games emulator. EDIT: I do wonder what Raspberry will come up with, clearly it won't be Jetson standard as Nvidia are miles ahead on this stuff and have massive budgets. The same for AMD, I just wonder there, they have supposedly invested some money in IoT/Embedded but I think they will be in a very different direction- could be wrong but more 86 64 and industry utility stuff- certainly not self driving cars.

[@TheDavidPoole]

Hi Chris, bit late to this party - sorry. Do you think a lidar module would integrate well with this project, a combination of visual and 3d mapping would be quite cool. Plus, on a more robust chassis like the Devastator (?) robot chassis you used on the pi controlled series could be a useful tool for hazardous area searches etc. It would be interesting to see you do a video or two on such a project. And quite educational. Now it's time for me to catch up with the rest of your videos that I've missed. Cheers!

[@Tom_P_242]

I think the better is Jetson RaceCar.... but it's only my own opinion

[@PeteVanDemark]

Fascinating! Nice little robot. Never would have guessed it uses an image library to navigate. Like the table too!

[@ExplainingComputers]

Every ExplainingComputers video where I look at any hardware is shot on that table. :)

[@arthurmoore1379]

@@ExplainingComputers My good man this is way to complicated for mm. Arthur here:

[@ryancoke777]

That roller ball on the bottom reminds me of an old mouse ball. That leads me to a great idea: a Jetson nano controlled mouse using a Bluetooth gamepad. Useless but why not?

[@ExplainingComputers]

I'm sure your idea could be done. :)

[@daviddavidsonn3578]

could you have a sort of robot detecting heat source ? like a heat seeking missile ?

[@egg11kompaniehuhn]

With an IR camera. But please go easy on germany we didnt do anything wrong this time.

[@bowenyang2808]

Am i the only person who thinks it risky to put a autonomous car running an untested model on a TABLE?

[@ExplainingComputers]

It was done with care and caution! :)

[@garyoa1]

Not sure what they are using but roomba has been working like that for 20 years or more.

[@ExplainingComputers]

Using neural nets to learn an area is clearly not new. But doing so with vision recognition at this price point is I think pretty novel.

[@saturno_tv]

Greetings Chris!. Expecting some review about the up-board.

[@ExplainingComputers]

If they send me one . . . :) Their new stuff does look very good: up-board.org/

[@bijanshadnia3620]

I thoroughly enjoy your videos. This one in particular is one of the coolest I've seen on your channel. Thank you for the hard work you do.

[@rolfsinkgraven]

A very interesting video.

[@suvetar]

You could use this to emulate the old Big Trak! (www.wikiwand.com/en/Big_Trak) :D

[@ExplainingComputers]

Nice idea.

[@Sam_Saraguy]

Move aside laser pointer, the cat has a new toy.

[@ronjenkins4257]

I can imagine networked robots of this sort, each perhaps in a different school, racing around a common virtual racetrack or in battling in a common virtual battlefield. In actuality each school's robot would be operating on an agreed upon real physical space (a school gymnasium), but playing on a common virtual space, populated by virtual robots being generated by the physical robots in each location. The winning robots would be the ones with the best-programmed algorithms supplied by the students.

[@lollerich]

Very, very interesting. I finally got at least a general idea of how neural networks are trained. Thank you!

[@ExplainingComputers]

Great to hear this -- that is what I was trying to convey. There is a fair bit of process between gathering the sample data and having a final trained model, but the essence is what you see here.

[@lollerich]

@@ExplainingComputers Thank you. While I did in general understand the purpose of neural networks I was always very hazy on how you would actually train one.

[@iKostanCom]

For some reason your robot never goes to right bottom corner... looks like a bug

[@ExplainingComputers]

A flaw in its training, certainly.

[@spidermcgavenport8767]

Thank you, Mr. Barnatt, Explaining Computers, My jet bot would be using vintage fisher price contrux.

[@spidermcgavenport8767]

Short Circuit S.a.i.n.t robot Johnny 5!

[@RealRobotZer0]

How big was the model that you had to copy to the robot in MB?

[@ExplainingComputers]

As I recall, a few hundred megabytes.

[@thomasottvideos]

Tesla Model 3? We don't need no stinkin' Tesla Model 3. We've got JetBot!!

[@lowiehojas5525]

I was just leisurely watching, but instead I learnt something that I need for my school assignment :D I just learned from your video how to train a data set for visual detection! Thank you so much!!

[@Croaker369]

Shouldn’t it be able to “self learn”, instead of being taught by the user?

[@ExplainingComputers]

Some neural nets self learn. But the vast majority require training with sample data.

[@mihailvormittag6211]

👍

[@gplayer01]

Excellent review & demo Chris of the Jetson. Interesting to know the amount of pictures you took to train the Jetson. Well done

[@maybehappen4138]

Did you train it with just one edge as an example, or did you need to repeat for each edge?

[@ExplainingComputers]

I trained on all edges, too far away from the edge nearest to the camera!

[@MacPhantom]

Great to see that NVIDIA uses PyTorch!

[@SniperUSMC]

This would be a good project to use to train an autonomous lawn mower. The direction changes need to be in a bit smaller increments so it doesn't just turn too much at once but just a little and retest for obstacle. If all the information can be stored on SanDisk card and saved then the trained brains/program can be moved to a bigger robot and have the "Blades of Death" (lawn mower blades) installed and turned loose safely to mow the lawn.

[@krishnar754]

Collision avoidance is not working on my jetbot. Could not read image from camera is the runtime error appearing. Please help me with this sir. I'm using raspberry pi camera btw.

[@ExplainingComputers]

This sounds like the camera is not working, rather than an issue with collision avoidance with the ML model. Can you see an image from the camera?

[@krishnar754]

@@ExplainingComputers yes sir ! I tried running a command from terminal and it worked perfectly without any issues. But when I run collision avoidance notebook, The line camera =Camera.instance() leads to run time error:could not load image from the camera. Edit: Sir it would be really helpful for me if you help me with this issue sir. Please provide any solution for this issue sir.

[@BlensonPaul]

Lovely. Awesome..

[@pranavraja10]

Awesome video, could you consider making a video on a Raspberry Pi based self driving car, there's a project called Donkey Car

[@ExplainingComputers]

I will take a look.

[@World_Theory]

A while back, I got an Idea… This is how it goes… You have an Artificial Neural Network (ANN), that is having trouble with a task that requires a perception of Time. What is a simple way to give it a perception of time? Answer: Give it memory. What is a simple way to give it memory? Answer: Use data from its sensors, taken at consistent intervals, and give them a “memory slot” in a cache. Use a small number of memory slots for progressively older sensory data samples. Whenever a new sample is added, delete the oldest sample, and shift the contents of all the other slots to the slots representing the sample that is one interval older than them, until the slot representing the newest data sample is empty, so that the most recent sample can occupy that empty slot. Feed the ANN from whatever is in the memory slots, as a separate sensory input. It will then be able to compare old vs new, and perceive changes from as far back as the memory slots go. This will need careful optimization, to avoid overwhelming the memory capacity of the hardware that it's all being run on, and to not require a ridiculous number of “neurons” in the ANN to be dedicated to input. One method of optimization, may be to also perform a resampling operation on saved sensory data, to step it down in size, every time the data is shifted to a new slot, whether immediately after it first enters memory, or if it meets the condition of being past a certain age, so that it loses fidelity, but still exists for reference for much longer within a given memory size constraint. Some care should be given to choosing a good resampling filter. It should probably be a balance between accurate and lightweight for processing. And accuracy brings up another subject: Resampling images while stored in the sRGB color space, is mathematically proven to distorting the overall energy of an image. All camera input should be converted to linearRGB colorspace, if it's going to be subjected to resampling. sRGB is meant to make efficient use of digital memory, for cases where an image is meant to be shown to humans, by matching assigning more importance to ranges of the color spectrum that the human eye is most sensitive to perceives differences in. So sRGB is completely unnecessary for computer vision. Another optimization method is to simply start with a smaller sized resolution for sensory input, or to use a color model other than RGB, such as Lab, where there is one color channel for Lightness, and two color channels for chromatic data. Then, you can aggressively down-sample the chroma channels by a positive whole number. I've mentioned resampling a lot, but I think I should mention that I'm not 100% sure how useful it would be to save processing power overall. I'm quite certain that it will save memory, though.

[@orleydoss3171]

👍

[@enriqueatentar8876]

Robot needed more sense to completely unlock his self Consciousness.

[@ExplainingComputers]

:)

[@MrVein5.0]

wait a second, i got a 1hour ad before this video? wow. interesting stuff but wow.

[@jasongooden917]

Or buy a Vector

[@srtcsb]

Very cool Chris. Of course it's 'simple', stuff like this starts out simple (you Arduino & Raspberry Pi blinky lights folks will know what I'm talking about... You can learn a lot from blinking those lights! ). Does Nvidia show you (or give access to) the code for this? Like another commenter said, possibly you could modify or extend the code for more functionality. I'd love to build one of these and examine the possibilities. Thanks for another great video Chris.

[@ExplainingComputers]

Hi Steve. And yes, all the code is available to tinker with. And there are various other examples available, like self-driving down a road based on its markings, and following a person/object.

[@arthurdent8091]

Hi Chris. Nice video. I caught the pun EYE instead of I, Robot, nice one. Robot vision will interest me more when I can be inside a self-driven car. Cheers.

[@a.i.3025]

Good ai robo

[@F15HHOOKS]

On a similar note Chris, have you seen the Tesla Autonomy Day presentation on KZbin? The first part details the bespoke chip build used for full self driving that I think you may find interesting.

[@ExplainingComputers]

Again, I will investigate! :)

[@Ruhgtfo]

Pass the butter

[@PsiQ]

11 minutes into the video i think it would be cool if you could print arrows and stick it on boxes and walls and it follows the direction :-) .. left right forward back, turnaround would all be possible.. even like turn 30° left, without any programming. edit: hahaaa! and if @13:45 you put a picture of yourself in with "free" it's gonna run you over if it gets you ;-)

[@ExplainingComputers]

This should be possible. This short video shows a JetBot navigating a road based on the road markings -- and not running over Lego people: kzbin.info/www/bejne/hGipp52Bi9GFqpI

[@michelj.gaudet5048]

This device must've been conceived by either a current or retired NASCAR driver... left turn, go straight, left turn, go straight, left turn, go straight, left turn, left turn, go straight, left turn...... lol😉

[@ExplainingComputers]

It manages some nice, gentle corners in this video: kzbin.info/www/bejne/hGipp52Bi9GFqpI

[@tamaseduard5145]

Thank you sir 🙏 🙏 🙏

[@gregadams558]

robot vacuum

[@NomadicSage]

This was a great video, please do more videos on AI and programming

[@ExplainingComputers]

Thanks. I hope to return to AI, but so far -- and after many attempts -- it has never really taken off on this channel.

[@NomadicSage]

@@ExplainingComputers it's quite different and interesting to see it in action, the experiments that you do in your style of breaking them down into easy to understand components is what always draws me to watch your videos. As well as replicate them with my own configuration.

[@twmbarlwmstar]

@@ExplainingComputers I want EDGE! No seriously, after you teased EDGE I've been reading up on it and looking forward to your planned video, I an see a direct use for EDGE computing in my life more so than IA, despite things like Amazon Dot or what have you. I think IA is a hard sell full stop, because of people like me, I get the concept but I don't get the access- as in I'm a bit thick and just don't get it and don't have the coding skills to get it. It won't go down well but I'm finding some of the MS stuff a bit easier than the Linux stuff- with the proviso I am on about stuff targeted at complete novices. And I'm not making any claims that MS W10 embedded is in anyway better, I just found some of it more accessible to me- probably because you get W10 as a base to build on. And all it is a doorbell that can tell you if it is a bear at the door or it isn't a bear at the door and that's it. There aren't many bears at my door (a few wolves maybe).

[@yunlongsong7618]

fascinating

[@sethrd999]

I have only one question for the platform, what is the runtime with only using one power source?. Good video and overview, I would suggest that anyone looking at doing this, learn the math required first ( if your not upto speed ), then possibly look at OpenCV amongst other tools, I say this because all the ground work is done for you with this platform so what are you really learning technically?.

[@ExplainingComputers]

Runtime depends on the level of motor use, but is certainly many hours. The Jetson Nano itself runs a good 6 to 8 hours (again, depending on what it is doing) on one charge of the pack. I expected to be recharging a lot, and did not need to.