@@GaryMcKinnonUFO yes, in the first run it memorises the maze, calculates the fastest way via an algorithm and than runs it, multiple attempts with removing dust from the wheels that is collected from the maze ground. actually saves .5 seconds with is significant with a runtime of 3.594 seconds
At first I wasn't sure what the point was cuz the speed of the first run of a robot in a maze will always be relatively random. Then I started realizing that whenever it retraced any straightaways it had already gone through, it went faster cuz it knew it could go faster. Turned out this was more of a mapping precision coding type of competition. Pretty awesome to watch.
@@doyourownresearch7297 it's smart, and something that happens in real life too, you would want to avoid crossing lots of roads when runnings or rough terrain.
I think I've done something similar in when I attended Ai and machine learning classes, I think that in the first pass the mouse does a basic search for the target (it can be as basic as a breath first search or a deep first search, provided you handle cycles in the latter case) a more refined way could be using some heuristics in the first pass (I'm a bit rusty on that but I clearly remember that there are some strategies that can statically improve efficiency in the first pass). Once the first pass has been done, you have in memory a graph which will certainly include the starting and the ending node, hence provided that you have constructed well that representation, it become as easy as performing any shortest path algorithm of your liking (like Dijkstra's). It's entertaining show to watch a physical thing do the job, but from a computer science point of view these are the basics.
@@alasuisi It is impossible to use any heuristics in the first pass because you don't know where the goal is. The interesting part of the problem is traveling the shortest distance while path-planning at the same time, as algorithms such as BFS can make your mouse jump have to keep moving across the map. A DFS would work better, but there might be a better algorithm that that.
@@jonathanyang1423 I was assuming that the position of the goal was k known, clearly if that's not the case then you cannot use an heuristic, but also, from the perspective of the agent, there is also no certainty that the solution set is finite, hence a dfs may theoretically never terminate. If we assume that since you can see that the maze is finite and that you are allowed to do informed search, then you can use A* for example with an heuristic as your choice like Euclidean distance or Manhattan distance, also if I remember correctly A* with a constant heuristic basically reverts to BFS
@@alasuisi Yes, DFS may not terminate, which may be a problem. Another problem is that it may not even give the optimal solution. Btw A* with 0 heuristic is Uniform Cost Search (although I guess its the same thing as BFS in this situation). However, A* may not be the best algorithm to use, as it still jumps around a lot (as in you maybe expand one node than another node that is a lot farther away).
That's the way I drive ALWAYS I wish more people understood this simple mathematics fact That's why delivery companies in the US always take right hand turns
It's the same as going for a run and avoiding crossing busy roads but the ability to decide which is more efficient with minimal to no testing is amazing
HINT: For greater dramatic impact, show the times AFTER the mouse finishes. This blew my mind, but it would’ve been even better if I didn’t know the second run would only take 4 seconds. Amazing!
I was still pretty amazed but I agree. My mind would have been blown instead. It’s amazing this little thing can path find and map out it’s surroundings. I’m wondering why it sometimes will go back to the start instead of spinning around celebrating its win. Maybe it’s just randomized.
@@luridftwgaming8983 It crashed or the wheels lost traction, probably by picking up some dust. This bot is really really light, and keeping its wheels from spinning is tough. It probably uses wheel input to tell where it actually moved, so once it slips, it loses its bearings.
@@luridftwgaming8983 Its because when it is spinning around, it is because it lost its 'footing.' It isn't celebrating, it is stuck. It only weighs a few grams, even a little bit of dust will make it spin out, that's why he's rolling the wheels with sticky tape between runs.
@@michaelblair5146 I could certainly be wrong, but my guess is that this task is not preformed using any machine learning (also known as statistical learning) algorithms, but instead uses mapping, positioning, control and error correction, and shortest path algorithms which have been well tuned for the particular hardware.
@@HummusPvm If you think that this machine(mouse) learns something new and explore maze to find solution using some maze algorithms, yes you are right. If you think that this mouse is using any algorithm from AI branch called 'Machine Learning' then, you are wrong.
The mechanical precision of this mouse is outstanding. The wheels alignment must have been absolutely spot on as well as the servos calibration. I have an ancient Heathkit Hero Jr robot from the early 80's and despite my best efforts absolutely refuses to go in a straight line :) We've come a looong way since...
He checked and readjusted the wheels but its more likely they readjusted the wheel so often they did it quickly out of efficiency rather than rushing/nervous
There's def an IMU in there and probably encoders on the wheels + other sensors for precise odometry. There's no way it's staying that lined up with the course just by counting on no slippage on the wheels.
Servos have been superseded by DC motors with accelerators/gyros now that the latter are miniaturized e.g. MPU6050. Dust on the wheels reducing traction is a big problem, hence the cleaning between each run.
This is actually the easiest part. Just keep a map of where you have been and use eg. the left hand rule: place the left hand on the wall and then just follow the path with your left hand always touching the wall thereby mapping all the walls. If you figure out, that in the area you have already explored there are no more uncharted areas, go back to the last position which has the possibility of leading into already uncharted territory and continue from there. Finding a way through this map to the goal actually is also not that hard. There are various algorithms to do that: find a way in a cellular arrangment, where path from one cell to one or more of the surrounding cell is blocked. (eg. Djikstra, eg. Lee algorithm) What impresses me is, that his algorithm actually takes the dynamics of the mouse into account (acceleration, deceleration) and that the mouse figured out that it can travel the diagonal at full speed. One of the hardest parts is actually to make sure, the mouse runs in a straight line at all times no matter if one of the wheels slips or not. Also it is hard to make it turn exactly the correct angle in order to be perfectly aligned for the next leg at full speed.
@@JonatasAdoM That is because within an algorithm you can control everything. While at the "interface" to the real world, this is not doable. You cannot control if the surface is perfectly level, if there are some dust particles on the floor, wheels have diameter tolerances, motors do not respond in exactly the same way to the voltage, optical sensors have to deal with stray light and so on and so on. You can imagine programming as "creating a perfect world". All things behave exactly as you designed them and how you programmed them. Of course there are programming errors, no doubt. Sometimes one started with the wrong idea and figures out that the idea does not work. That happens. No doubt about it. But still: A computer does EXACTLY what you tell him to do. If he doesn't, then the recipe you used was faulty, but there are no outside effects giving you troubles. Real physical world is different.
@@kallewirsch2263 That only works for simply connected mazes though. Are all the mazes closed in this comp? There are other algorithms for mazes that are not simply connected though, of course.
We all time traveled forward in time from 2011 into 2016 and then in 2019. In fact, we're all time travelling right now. On top of time travelling micromouse can do a maze in less than 4 seconds after second try.
Did you notice the fact that '2016' is part of the maze? ;) (the diagonal route is obviously intentionally put there by the designers of the maze to test for a mouse's ability to deal with that as well instead of only thinking in 'straight' blocks and lines)
@@falshion1837 actually is a fusion of computer science, physics and engineering. The really fast ones are not just aerodynamic the also have suction fans to hold them to the floor so they can decelerate and turn faster. It’s all about having the mouse that can determine how to get to the centre and back the quickest.
I drew this maze in a pygame pathfinding program I made last year and almost found the exact same path the mouse used. My A* heuristic doesn't consider a cost for turns or allow for diagonal travel and I had to block a shorter path along the right side of the maze (from video's perspective) to get (almost) the mouse's path (it cut the diagonal short by going up in the middle of the maze). The shortest path isn't always the fastest path!
As Sam Vaknin said they did studies in 2007 how badly the affect of social media is.... it was bad in 2007....said some people work with computers better than with humans....This video shows it...... and he said today they dont do these studies of mental health because, he thinks the Google advertissing etc... so they dont care.
Robotics is starting to move and progress faster and faster! I can't wait to see what the future holds for these programs that help the robot to 'learn things.'
As a former software engineer, I am curious why they don't run a 'mapping' run by using the Rule of Rights when navigating a maze. That is, you always follow the right-hand wall, as it will always lead to the goal; and then continue mapping the rest of the perimeter by continuing past the goal still applying the Rule of RIghts, then map to the inner section(s). I am imagining the mapping process would be slower, hence why they use the methods they do? Fascinating to see how it maps, even though it feels 'random', there is clearly a process for data collection, and an algorithm for mapping routes as new wall data is mapped and an 'as many straight lines as possible' final path determination. EDIT: I just realized that the goal could be a 'floating' space not connected to any other wall(s). This changes my inquiry.
It depends on the competition rules. For example, the IEEE 2020 rules stated, "The destination square will be positioned so that a wall-hugging mouse will NOT be able to find it."
Key tip! If you put the video on full screen then hold your phone right. You will see 2016 on the board. Or if you just look you can see it right there.
While it was searching the first time, I thought I would try my hand at figuring out what route it would take, and I was pleasantly surprised that I was right!
At first I was really confused why it was stupidly making successive turns that put it back where it was, but then after awhile I realised it was mapping out the entire field before making runs to the goal.
First time around, the hunter-seeker will slowly learn its environment, until it is familiar with every nook and cranny. Then it goes into hiding until the Muad'Dib comes home. It will only spring into action, with furious speed, once he is at his most unaware. But Muad'Dib is omniprescient, and can see a thousand possible futures unfold at once, so in the last second, he pulls away from the poisonous dart, while he reaches out with his strong fingers to snap it in half with a soft and dry crack.
First attempt: When Mickey goes shopping in the mall with Minnie The rest of the attempts: Mickey when Minnie calls him and said she was alone in the house
@@GeorgeTsiros I have nothing against dfs, but it is too plain and overly expensive for no particular reason. This is exactly why Dijkstra's algorithm (in its straightforward implementation) is mostly just a technical insight in today's engineering practices (likely A*) and is rarely used even in the most basic of games. And this kind of algorithm is pretty advanced compared to any dfs or bfs. These kinds of devices have very little processing power, and I'm guessing that the virtuosity of this competition lies in the software hacks, to massively speed them up, and not in the hardware. The most expensive and tricky parts of these algorithms are typically the solvers for minimum spanning trees and/or maintaining priority queues, and then having a flexible and reliable heuristics all of which is practically science in itself. Then again, I'm only speculating based on what little I know about all of this.
@@milanstevic8424 compared to the scale of time these devices operate on, any kind of sophisticated algorithm would not provide benefits. Consider even the fastest speed it moves nodes. 10 squares per second? Even on a 10MHz uC having 1 mil instructions available to toy with for one new square is luxury... and i'm pretty sure they're not using some decade old AVR like i'm used to. Bought a $10 dev board the other day... half a meg flash, 128k ram, 100 MHz and onboard DMA? Holy crap. Too bad i can't program it... too complicated and top complex. Anyway. Seriously though, my comment was mostly humorous. Of course they'd use a more sophisticated algorithm..., why not?
The interesting part is that it mapped the maze and learned. At first I thought it was just doing a simple if, than, else loop to navigate, but it found the optimal route and applied it. Once it knew the best way to go, it was little surprise that it could do it that way with scary speed and precision. Impressive, for sure. The implications of actively learning microrobotics are kind of mind boggling. If that little mouse communicated with a little drone, it could find the optimal route through the maze before it even moved at all.
Exactly. It is what the mouse has to do in a first run - learn. You may check out the rules of the contest at www.micromouseonline.com . If the mouse knows the maze in advance that would be algorythm so called "wave propagation" Lee's algo maze route finder (which was actually computed basis known facts abt maze and used on a final speed run in this video). I was surprized that mouse seems to be using Moore neighborhood (i.e. learning 8 directions) because running diagonal at the end. Programming mouse behaviour is actually not a big problem, almost same as tracing pc cards
so, let me know if I understood this corect. First, the electronic mouse is crusing through the maze in order to analize the path of the maze and doing this is "learning" the architecture of the maze... after that the idea is to complete the maze as quick as possible using what he was "learning" from previous atempts... ?
@@akj7 LEDs are tiny. micro controller can also be very small. guess is battery, motor, and sensors probably take up the majority of the actual real estate. even the battery doesn't have to last THAT long.
@@akj7 They can fit much more and in even smaller spaces. Quite easily too, it's just expensive to make. There are terabyte micro SD cards, and mechanical motors you can't see with you naked eyes. They just cost millions. These robots are actually quite large.
It wasn't malfunctioning it's just how micromouse works. The first run the robot maps the maze, then the subsequent runs it gets to do them as fast as it can. Out of all the runs your fastest time is the one recorded.
What are the hardware requirements?? And what is the algorithm used in this particular project?? I know that backtracking was used same as mice in Maze but I need the algorithm
![Микромышиные бега - самая быстрая гонка по лабиринту [Veritasium]](http://i.ytimg.com/vi/9vS9AKm-Bek/mqdefault.jpg)
I have to admit, when it did the second run, and calculated that it could do a straight diagonal run, I was truly surprised.
Yes impressive. Is all the computing power on-board ?
@@GaryMcKinnonUFO yes, in the first run it memorises the maze, calculates the fastest way via an algorithm and than runs it, multiple attempts with removing dust from the wheels that is collected from the maze ground. actually saves .5 seconds with is significant with a runtime of 3.594 seconds
To be fair, the robot doesn't know it's on a uniform grid, it would be fine in a curvy maze.
I was surprised when it moved
@@index7787 how would you know that?
At first I wasn't sure what the point was cuz the speed of the first run of a robot in a maze will always be relatively random. Then I started realizing that whenever it retraced any straightaways it had already gone through, it went faster cuz it knew it could go faster. Turned out this was more of a mapping precision coding type of competition. Pretty awesome to watch.
Easy maze
On the maze board it says 2016. At the bottom of the video it says 2011-08-02. i don't understand from these events. Whats up with that.
@@emindegertekin2047 it’s our fault not to adjust the time setting of the camera 😅.
I like how it’s optimizing for longest straight segments because of the acceleration it’s doing on straight paths
It’s so interesting to see the acceleration
@@doyourownresearch7297 it's smart, and something that happens in real life too, you would want to avoid crossing lots of roads when runnings or rough terrain.
@@ProcuredHat I think he’s scared for his grandkids safety tho
@@greekstreek370 every second you aren't running, it's optimizing its algorithms to hunt you down faster
all hail the algorithm. Nobody searched for this, but we all needed it.
I did search
he searched for it
@Lemon Pasta she searched for it
be careful tho, we aren't too many clicks away from the melted mouse trap genocide videos...
And now I'm watching them all.
At the start: Oh, this is pretty cool.
The second run: Holy crap!
I think I've done something similar in when I attended Ai and machine learning classes, I think that in the first pass the mouse does a basic search for the target (it can be as basic as a breath first search or a deep first search, provided you handle cycles in the latter case) a more refined way could be using some heuristics in the first pass (I'm a bit rusty on that but I clearly remember that there are some strategies that can statically improve efficiency in the first pass). Once the first pass has been done, you have in memory a graph which will certainly include the starting and the ending node, hence provided that you have constructed well that representation, it become as easy as performing any shortest path algorithm of your liking (like Dijkstra's). It's entertaining show to watch a physical thing do the job, but from a computer science point of view these are the basics.
@@alasuisi It is impossible to use any heuristics in the first pass because you don't know where the goal is. The interesting part of the problem is traveling the shortest distance while path-planning at the same time, as algorithms such as BFS can make your mouse jump have to keep moving across the map. A DFS would work better, but there might be a better algorithm that that.
@@jonathanyang1423 I was assuming that the position of the goal was k known, clearly if that's not the case then you cannot use an heuristic, but also, from the perspective of the agent, there is also no certainty that the solution set is finite, hence a dfs may theoretically never terminate. If we assume that since you can see that the maze is finite and that you are allowed to do informed search, then you can use A* for example with an heuristic as your choice like Euclidean distance or Manhattan distance, also if I remember correctly A* with a constant heuristic basically reverts to BFS
@@alasuisi Yes, DFS may not terminate, which may be a problem. Another problem is that it may not even give the optimal solution. Btw A* with 0 heuristic is Uniform Cost Search (although I guess its the same thing as BFS in this situation). However, A* may not be the best algorithm to use, as it still jumps around a lot (as in you maybe expand one node than another node that is a lot farther away).
Jonathan Yang he should have used a calabi-yao distributed formulation graph to increase the number of f cycles
1900s: Build a better mouse trap
2010s: Build a better mouse
Lol, yep
2020s: Bow down to our Robot Mouse masters
2020: Build a better captcha
@@insertstupidserialnumberhe2727"Ïm not a robot mouse"
2200: better build
First Run : Going to work
Second Run : When She's home alone
😂🤣🤣🤣
For those who thought it was a victory spin on the 2nd run, you were all wrong. It simply tried to return to it's starting location but failed.
is that true?
Yep, it spun and gave up
no no little robot mouse was happy
you’re wrong period
how do you know it was not a victory spin :P
It's impressive that it chooses a longer route with straighter lines so as to optimize TIME instead of DISTANCE.
That's the way I drive ALWAYS
I wish more people understood this simple mathematics fact
That's why delivery companies in the US always take right hand turns
yeah the turns are deceleration points, I play a lot of steep.
This is one of the basic principles, you want to minimize the number of changes of directions. His route had the fewest changes.
It's the same as going for a run and avoiding crossing busy roads but the ability to decide which is more efficient with minimal to no testing is amazing
I think the route is also shortest
HINT: For greater dramatic impact, show the times AFTER the mouse finishes. This blew my mind, but it would’ve been even better if I didn’t know the second run would only take 4 seconds. Amazing!
totally agree!
I was still pretty amazed but I agree. My mind would have been blown instead. It’s amazing this little thing can path find and map out it’s surroundings.
I’m wondering why it sometimes will go back to the start instead of spinning around celebrating its win. Maybe it’s just randomized.
@@luridftwgaming8983 It crashed or the wheels lost traction, probably by picking up some dust. This bot is really really light, and keeping its wheels from spinning is tough. It probably uses wheel input to tell where it actually moved, so once it slips, it loses its bearings.
@@luridftwgaming8983 Its because when it is spinning around, it is because it lost its 'footing.' It isn't celebrating, it is stuck. It only weighs a few grams, even a little bit of dust will make it spin out, that's why he's rolling the wheels with sticky tape between runs.
Electric Rune Games hahaha. Ok 👍, here I was thinking he added some personality to it.
Awesome engineering and even better coding, very impressive
@@michaelblair5146 Machine learning algorithms is something you code
@@michaelblair5146 I could certainly be wrong, but my guess is that this task is not preformed using any machine learning (also known as statistical learning) algorithms, but instead uses mapping, positioning, control and error correction, and shortest path algorithms which have been well tuned for the particular hardware.
@@recurrenTopology yeah, this is just mapping the maze and finding the optimal path (which we have known algorithms for)
no, it is not Machine Learning... it is simple maze algorihtms
@@HummusPvm
If you think that this machine(mouse) learns something new and explore maze to find solution using some maze algorithms, yes you are right.
If you think that this mouse is using any algorithm from AI branch called 'Machine Learning' then, you are wrong.
The mechanical precision of this mouse is outstanding. The wheels alignment must have been absolutely spot on as well as the servos calibration. I have an ancient Heathkit Hero Jr robot from the early 80's and despite my best efforts absolutely refuses to go in a straight line :) We've come a looong way since...
He checked and readjusted the wheels but its more likely they readjusted the wheel so often they did it quickly out of efficiency rather than rushing/nervous
There's def an IMU in there and probably encoders on the wheels + other sensors for precise odometry.
There's no way it's staying that lined up with the course just by counting on no slippage on the wheels.
Servos have been superseded by DC motors with accelerators/gyros now that the latter are miniaturized e.g. MPU6050. Dust on the wheels reducing traction is a big problem, hence the cleaning between each run.
it is self calibrating, so it adjusts its path from the walls. It never touches them but measures the distance.
*no one:*
*youtube algorithm :* 2016 Taiwan Halfsize micromouse First Prize Kojimouse 11, Hirokazu Kojima
shut up normie
the thing is.. this isnt even from 2016 when Begnizu Yakawen won the competition! this is 2011 bullshit.. 3.95 second win? garbage
@@TheCelestis it says 2016 built into the maze
@@TheCelestis F
fuck off with your shitty meme
Oh shit, when little dude hit that crispy diagonal, made me spit coffee. You will forever live in our hearts, little robot mouse.
The second run was crazy, and it kept on learning and improving afterwards.
My vacuuming robot used to sweep the whole floor like the first run, but recently it has learned to take shortcuts too.
I have absolutely no idea what I just watched, but it was neat. Also, it took me 5 minutes to see that "2016" is in the maze.
No, it's from the future... *"9102"*
yea but on the bottom left of the frame you have the date of the footadge and it's 2011 ??
@@timtomachard1471 I see 2016
@@horror7927 lul its not in the maze but actually the bottom left corner of the entire video :D
+James Boyer Ah,thanks for pointing it out! :D
11:59 AM
4/22/2019
Happy Easter Monday!
One minute away from PM! :O
*me:* I'll sleep early today
*brain: "Oh! A 2016 Taiwan micromouse contest! LET'S WATCH!!"*
Exactly. 😂
Me every time
0:00-0:47 my girl in grocery store
4:49-4:54 thats me in grocery store
Man you made my day!!! LOL!!!
Feby u are a QM!
Beli rokok doang abistu pulang
@@mikolabima7317 ketengan pula😂
here's some timestamps:
0:28 - 1:33 First Try
1:34 - 4:08 Going back to Start
4:44 - 4:54 2nd Try
4:55 *SPIN*
5:48 - 5:55 3rd Try
6:58 - 7:05 4th Try
7:50 - 7:58 5th Try
That is very cool! I am impressed with the entire "learning/performing/mechanical/drive" aspects of what I just witnessed. Congratulations!
The way it turns around 180 degrees is so clean...so perfect...its almost soothing.
the way it curves and turns so perfectly. it’s magnificent
Second run was awesome. It even did a victory spin at the end like it has a mind of its own.
Its not victory spin its the mouse failed the runback start point
@@sat4.20 it was obviously a victory dance
I wish they didn't display the time before they even do the second run. Knowing that it's just aboot to do it in 4 seconds takes away the surprise
When you don't realize the time is for the run about to happen:
i.ytimg.com/vi/EpdLJIvUiAI/hqdefault.jpg
@@cybrzero7558 He... he did? Maybe re-read his comment.
I like how you didn't understand what he said and then proceeded to link the worst cropped meme ever produced by a human.
I honestly thought it was a typo
@@cybrzero7558 obviously he did realize the time was for the next run, else he wouldn't have been so disappointed in the first place genius.
If I hadn't seen it I simply wouldn't believe it. Absolutely AMAZING. I'd love to see that little Mouse up close.
Omg, these look so much fun to make. I think I have a new hobby. Looks like a silverfish with those awesome smooth turns!
Why is this actually one of the coolest things I’ve seen in a long time.
It mapped almost the whole maze in the first run. Impressive.
This is actually the easiest part.
Just keep a map of where you have been and use eg. the left hand rule: place the left hand on the wall and then just follow the path with your left hand always touching the wall thereby mapping all the walls.
If you figure out, that in the area you have already explored there are no more uncharted areas, go back to the last position which has the possibility of leading into already uncharted territory and continue from there.
Finding a way through this map to the goal actually is also not that hard. There are various algorithms to do that: find a way in a cellular arrangment, where path from one cell to one or more of the surrounding cell is blocked. (eg. Djikstra, eg. Lee algorithm)
What impresses me is, that his algorithm actually takes the dynamics of the mouse into account (acceleration, deceleration) and that the mouse figured out that it can travel the diagonal at full speed.
One of the hardest parts is actually to make sure, the mouse runs in a straight line at all times no matter if one of the wheels slips or not. Also it is hard to make it turn exactly the correct angle in order to be perfectly aligned for the next leg at full speed.
@@kallewirsch2263 So the harder part is actually the one that looks the easiest? interesting.
@@JonatasAdoM
That is because within an algorithm you can control everything.
While at the "interface" to the real world, this is not doable. You cannot control if the surface is perfectly level, if there are some dust particles on the floor, wheels have diameter tolerances, motors do not respond in exactly the same way to the voltage, optical sensors have to deal with stray light and so on and so on.
You can imagine programming as "creating a perfect world". All things behave exactly as you designed them and how you programmed them. Of course there are programming errors, no doubt. Sometimes one started with the wrong idea and figures out that the idea does not work. That happens. No doubt about it. But still: A computer does EXACTLY what you tell him to do. If he doesn't, then the recipe you used was faulty, but there are no outside effects giving you troubles. Real physical world is different.
Isn't this the technology that self driving cars will use to remember paths? Or is it just google maps?
@@kallewirsch2263 That only works for simply connected mazes though. Are all the mazes closed in this comp? There are other algorithms for mazes that are not simply connected though, of course.
*UA-cam:* 2016
*Maze:* 2016
*Timestamp:* 2011
Sure the mouse's technology is impressive, but it's still got nothing on the time traveling camera.
or a misdated camera.
We all time traveled forward in time from 2011 into 2016 and then in 2019. In fact, we're all time travelling right now.
On top of time travelling micromouse can do a maze in less than 4 seconds after second try.
its almost like a camera has an internal clock thats needed to calculate the time
Cal Clove Oh, for f... Can we woosh this guy?
r/woooosh
I AM FROM 1972, WHAT IS THIS SORCERY!
Cool how they incorporate the year 2016 into the design!
Clever programmers. Making a program like this is truly respectable
Indeed, KOJIMA San is respectable for his consistent efforts in making his mouse better and better!
The diagonal route mindblown me
i have finialy got to the end of the internet
Did you notice the fact that '2016' is part of the maze? ;)
(the diagonal route is obviously intentionally put there by the designers of the maze to test for a mouse's ability to deal with that as well instead of only thinking in 'straight' blocks and lines)
The f did I just watch?
You just watch a little robotic mouse run through a maze. That's what. Where you expecting something more? 😅
@@RedWolf777SG From reading other comments, apparently it's a competition of who has the best AI mouse robot?
@@falshion1837 actually is a fusion of computer science, physics and engineering. The really fast ones are not just aerodynamic the also have suction fans to hold them to the floor so they can decelerate and turn faster. It’s all about having the mouse that can determine how to get to the centre and back the quickest.
@@daverei1211 That's actually really cool!
@@falshion1837 You watched what will eventually become Skynet. This was Terminator 0.12 beta.
Fantastic how they squeezed all hardware limitations to achieve this. There is a very smart code inside this tiny robot.
It’s indeed very small, less than 5 grams.
Are we sure it's not computered outside? (By wifi, or whatsoever)
I drew this maze in a pygame pathfinding program I made last year and almost found the exact same path the mouse used. My A* heuristic doesn't consider a cost for turns or allow for diagonal travel and I had to block a shorter path along the right side of the maze (from video's perspective) to get (almost) the mouse's path (it cut the diagonal short by going up in the middle of the maze). The shortest path isn't always the fastest path!
I love the fact the mouse did a Little victory spin at the end. 4:55
It crashed...
not sure why i was supposed to watch this. then second run confirmed, yes, i was exactly supposed to watch this.
People like this is why we have the technology we have today. The crazy brilliance of these kinds of people should always be appreciated.
This is the stuff that I imagined I'd be watching on UA-cam and social media when I was a kid not whatever is happening now.
BOOM TETRIS FOR JEFF
and BOOM TETRIS FOR JONAH
bro ur pf and name are so 2012 I like it
made my day XD
i was literally watching that yesterday!
IM DEAD!
2016:No
2017:No
2018:No
2019:YES, IT'S TIME TO PUT IT IN RECOMMENDED
Thanks, UA-cam.
Master knows when you are ready to get into
so original
Lol look at the year first!
2021: what ?
@@tlemsen still showing up in recommend...
I had second thoughts when I thought the guy was brushing his pet mouse lol 🤣
As Sam Vaknin said they did studies in 2007 how badly the affect of social media is.... it was bad in 2007....said some people work with computers better than with humans....This video shows it...... and he said today they dont do these studies of mental health because, he thinks the Google advertissing etc... so they dont care.
It ran so fast, it turned back in time from 2016 to 2011!
Dat spin though, cutest victory celebration evah
Until 04:49 I was feeling sad about this mouse. At the end I feel sad about humanity.
Yep, you surely are a loser.
Yup, we're boned.
Hello dinosaurs here we come.
I agree in part... But, the creation is not superior to the Creator.
@@dronegressive7035 This is your misunderstanding, watch this video & you would know: ua-cam.com/video/Pls_q2aQzHg/v-deo.html
@@Slash27015 This sounds funny but it absolutely true & scary as well.
Robotics is starting to move and progress faster and faster! I can't wait to see what the future holds for these programs that help the robot to 'learn things.'
The mouse evidently appreciated that nice grooming it received after the first try!
If the mouse has watched Japanese television, it is immediately wondering what part of the maze is hiding the predatory lizard.
I was accidentally watching this at 2x speed and could not believe what I was seeing lol
知識もってませんけどちょこちょこ動くネズミかわいい、あの５分頃の斜め移動すごい！
2:30 am, another day that i swore to go to be early, and ... im watching this.
loved it.
And to think I was impressed with the first run.
The way he tenderly rubs the wheels of the mouse
Oh this is great, I wish they did stuff like this in my city.
Little did I know how intense this is going to get..
374th try, invented time travel.
The last try @ 7:50 is insanely fast. Robots will take over the jobs of the maze rats :-)
epSos.de 7
LOL poor maze rats will be out of business
First it was immigrant mice working for lower wages now it's the robots. When will maze mice catch a break?
As a former software engineer, I am curious why they don't run a 'mapping' run by using the Rule of Rights when navigating a maze. That is, you always follow the right-hand wall, as it will always lead to the goal; and then continue mapping the rest of the perimeter by continuing past the goal still applying the Rule of RIghts, then map to the inner section(s). I am imagining the mapping process would be slower, hence why they use the methods they do? Fascinating to see how it maps, even though it feels 'random', there is clearly a process for data collection, and an algorithm for mapping routes as new wall data is mapped and an 'as many straight lines as possible' final path determination.
EDIT: I just realized that the goal could be a 'floating' space not connected to any other wall(s). This changes my inquiry.
In this case the exit is not an island so the rule of right works, but maybe there is no rule prohibiting island exits.
"this changes my inquiry"
Well then, good day to you, sir
It depends on the competition rules. For example, the IEEE 2020 rules stated, "The destination square will be positioned so that a wall-hugging mouse will NOT be able to find it."
I like how it does a little spin of triumph at the end
4:50
That Diagonal dash was mad fire.
Roses are red
Violets are blue
UA-cam's algorithm
Brought me here too
Thanks for the likes.
Sam Gamer 418 nerd 🤓
reddit brought me here
i looked this video up
according to Neil Tyson violets are violet not blue lol
And human idiocy brought us another "roses are red..." commenter.
Key tip! If you put the video on full screen then hold your phone right. You will see 2016 on the board. Or if you just look you can see it right there.
I've seen those mice on the highways before. They cut 5 lanes in 2 seconds to take an exit.
They are called Asians, Japanese people not included in the bad driving though
4:56 that spin tho!
Anybody noticed the 2016 on the maze itself? It says it there
9102
What has the mouse got? Chip loaded AI and powerful memory, able to learn, analyze then home-in straight to target? This is amazing.
Probably not an AI at that level, it's more likely to be a pathfinding algorithm and some optimization on top
While it was searching the first time, I thought I would try my hand at figuring out what route it would take, and I was pleasantly surprised that I was right!
Did anyone check that roomba for steroids?
Damn that Asian Marketed WD40!
wow, even did a celebratory donut. 😃
Please kiss me!
hahahaha is really god video saludos
Oh yeah! Finally, a sport I can root for!
That diagonal run was completely uncalled for
At first I was really confused why it was stupidly making successive turns that put it back where it was, but then after awhile I realised it was mapping out the entire field before making runs to the goal.
First time around, the hunter-seeker will slowly learn its environment, until it is familiar with every nook and cranny. Then it goes into hiding until the Muad'Dib comes home. It will only spring into action, with furious speed, once he is at his most unaware. But Muad'Dib is omniprescient, and can see a thousand possible futures unfold at once, so in the last second, he pulls away from the poisonous dart, while he reaches out with his strong fingers to snap it in half with a soft and dry crack.
kebman That was the best nerd reference I’ve read online in a while. Well played!
bravo
haha shit im actually reading it rn (Y)
FATHER! THE SLEEPER HAS AWAKENED!
For those in the dark: Dune. Go read it!
this video is years old but no one is talking about how im pretty sure he uses a lint roller to ensure the mouse has optimal traction. that's sick
i like how it scans the whole maze then just speeds up
UA-cam Algorithm brought me here.
But damn I laughed hard and surprised about the diagonal run in second attempt.
It took me 7 minutes to realize the maze makes a 2016 on the bottom left side
Didn't even realize it until I saw this comment, lol
It took me until 2019
or maybe 9102 B)
took me 8 minutes 10 seconds and reading a comment to realize that.
The mouse figured it out 10 seconds in.
How about using a robotic cluster? Drone with image recognition coordinating with the micro mouse?
I did not expect it to take that route, nor go diagonal at warp speed
Cant unsee the 2016 bottom left of maze
mebbe because...it's there on purpose
Can't unsee the maze.
The maze was ahead of its time!
Edit: Okay, I see it says it's the 2016 competition in the title, but the on-screen date is 2011.
@@kaldo8907 Look at the left of maze table. You can see vertically 2016 sign.
The timestamp could be caused by a factory reset camera. It probably represents (time of manufacture + time since activation)
The future is going to be great with minds like these.
The domination of the white man is over. Asians will take over the worlds' technology
@@burgerking220 Even if it's true, please don't frame it as a competition. You will generate unnecessary animosity. That only hurts everyone.
Now think for a minute if such precision and speed will be WEAPONIZED, what it can do...
@@digimaks has been done long time ago ... more faster, more accurate
love how they added the year this was filmed on the maze.
Ikr I can’t believe they filmed this in 9102
First attempt: When Mickey goes shopping in the mall with Minnie
The rest of the attempts: Mickey when Minnie calls him and said she was alone in the house
That is some powerful algorithm in action.
given that the maze is static, of standard dimensions, and can be investigated ahead of time, it's probably A*.
but could be a D* variant as well.
TBH the hardware here is much more impressive than the software (well, the maze solving bit, the mapping out bit is not exactly trivial)
@@milanstevic8424 what, dfs too plain for you? :P
@@GeorgeTsiros I have nothing against dfs, but it is too plain and overly expensive for no particular reason. This is exactly why Dijkstra's algorithm (in its straightforward implementation) is mostly just a technical insight in today's engineering practices (likely A*) and is rarely used even in the most basic of games. And this kind of algorithm is pretty advanced compared to any dfs or bfs. These kinds of devices have very little processing power, and I'm guessing that the virtuosity of this competition lies in the software hacks, to massively speed them up, and not in the hardware. The most expensive and tricky parts of these algorithms are typically the solvers for minimum spanning trees and/or maintaining priority queues, and then having a flexible and reliable heuristics all of which is practically science in itself.
Then again, I'm only speculating based on what little I know about all of this.
@@milanstevic8424 compared to the scale of time these devices operate on, any kind of sophisticated algorithm would not provide benefits. Consider even the fastest speed it moves nodes. 10 squares per second? Even on a 10MHz uC having 1 mil instructions available to toy with for one new square is luxury... and i'm pretty sure they're not using some decade old AVR like i'm used to. Bought a $10 dev board the other day... half a meg flash, 128k ram, 100 MHz and onboard DMA? Holy crap. Too bad i can't program it... too complicated and top complex. Anyway. Seriously though, my comment was mostly humorous. Of course they'd use a more sophisticated algorithm..., why not?
The interesting part is that it mapped the maze and learned. At first I thought it was just doing a simple if, than, else loop to navigate, but it found the optimal route and applied it. Once it knew the best way to go, it was little surprise that it could do it that way with scary speed and precision. Impressive, for sure. The implications of actively learning microrobotics are kind of mind boggling. If that little mouse communicated with a little drone, it could find the optimal route through the maze before it even moved at all.
Exactly. It is what the mouse has to do in a first run - learn. You may check out the rules of the contest at www.micromouseonline.com . If the mouse knows the maze in advance that would be algorythm so called "wave propagation" Lee's algo maze route finder (which was actually computed basis known facts abt maze and used on a final speed run in this video). I was surprized that mouse seems to be using Moore neighborhood (i.e. learning 8 directions) because running diagonal at the end. Programming mouse behaviour is actually not a big problem, almost same as tracing pc cards
Sabadão, 2020 e eu aqui, vendo micromouse..
so, let me know if I understood this corect. First, the electronic mouse is crusing through the maze in order to analize the path of the maze and doing this is "learning" the architecture of the maze... after that the idea is to complete the maze as quick as possible using what he was "learning" from previous atempts... ?
Kojima is a genius
Does it connect to external computing and memory? or does all workings has to be internal?
Mice must be 100% self-contained, no external controls, computation, etc are allowed.
@@christophertstone How can they contain a microcontroller, led, and battery in such small objects?
@@akj7 LEDs are tiny. micro controller can also be very small. guess is battery, motor, and sensors probably take up the majority of the actual real estate. even the battery doesn't have to last THAT long.
@@shnatko Can you recommand me some schematics or some kind of build project for this?
@@akj7
They can fit much more and in even smaller spaces. Quite easily too, it's just expensive to make. There are terabyte micro SD cards, and mechanical motors you can't see with you naked eyes. They just cost millions. These robots are actually quite large.
Maybe it's the most exciting video on UA-cam.
That was great, now I'm off to Slot car racing European Championship Finals, Helsinki
It's easy without the ghosts running after you..
4 years later
This was in my recommended videos 😂 now I feel like buying a hamster
Hamsters can not do this, they get lost around a pole.
After he showed the mouse some compassion and brushed it for a second. It had no problem.
Oh wow, I couldn't beat it with my eyes.
I didnt know there is this kind of competition before
The speed they travel when you finally see one in your home 😜😜😜
4:06 "ok this sh** is malfunctioning....bring it back to clean the dust off, blow it and reprogram!!"
It wasn't malfunctioning it's just how micromouse works. The first run the robot maps the maze, then the subsequent runs it gets to do them as fast as it can. Out of all the runs your fastest time is the one recorded.
What are the hardware requirements?? And what is the algorithm used in this particular project?? I know that backtracking was used same as mice in Maze but I need the algorithm