I'd like to see another set of motors added to the other side and he can invite other programmers to challenge his programming. Add in more camera angles and hi-speed replays and you've got something.
@@BuLLGotcha So we need a ball that's the same size and with a similar surface that's hollow enough to contain an accelerometer and all it's gubbins. It must not be bouncy and must be shock resistant. sounds kinda hard
With such projects across the internet the "getting there" part is usually pretty boring, so I often just skip to the good part of the presentation of the finished thing. But you've made the problem solving part as interesting as the final demo which made this video overall interesting to watch. Well done!
Bro if this shit doesn't blow up like your last. . . Man, that first seven seconds had me already hooked. It's not enough that you're building a robot, but you gotta pull off feats of skill like *that?* Man, my jaw dropped. Glad I subbed back then. Alsp holy crap the flexing with that blind shot. You're nuts.
you could train neural networks by continually pitting them against each other on your real foosball table. you could then eventually (after a long time) and up with a neural network that is very good at irl foosball
Ideally you'd be able to model the game in software so it didn't need to physically play each game for training. It would be interesting to see how well training on a simplistic model translated to playing in the real world. Hopefully well enough to work as pre training, which could be fine tuned with real games. It would speed up the overall training time significantly.
@@JscWilson Human players can currently beat the robot cause they have a better intuition of the real physics. So a NN would definitively need to learn this. A physics simulation would need to be very accurate to do the training in order to be better than the hand written software.
@@salia2897 "Intuition of the real physics" isn’t the only factor. Foosball is dynamic-another critical factor is how quickly a player or robot can receive input, make decisions, and act upon them. As an extreme example, imagine a robot capable of perfect predictions but taking an hour to process them. Another robot with faster reaction times, but less accurate predictions, could score a goal before the slower robot could respond. More accurate predictions are obviously better (all else being equal), but the robot doesn't need to have a better "Intuition of the real physics" to beat a human. That is why I said it would be interesting to see how realistic the model would need to be to be useful. One approach could involve initial training on a simpler and faster model, followed by fine-tuning on a more realistic yet slower model. Such a strategy might outperform dedicating the entire training time solely to the realistic model - but again, the question is how accurate do the models need to be?
@@jessewilson3571 It does not need a better one. But it does need one that is good enough to do the required maneuvers that humans can do. And doing that can only be learned from a physics model that is good enough and that will already be quite complicated.
@@salia2897 With a quick Google search, you can find a number of examples of foosball-playing neural networks that have been trained using simulations. This includes a few public GitHub repositories with Unity models that aren't very complex. So, training on simulations can definitely be done with models that aren't extremely complex.
Nice job on this! I designed built one of these as well for Oklahoma State University, on ours I trained a neural network to control the rod actuators. Additionally a core objective of ours was to make it the same footprint as an actual foosball table because the previous version had the side mounted actuators like yours and was extremely large!
You're one of my favorite youtubers and you only have two videos! I think it's partially because you have a very similar style to another of my favorites, Stuff Made Here. You made a few (maybe unintentional, but probably not?) references to some of his jokes (only have to do it once, magic wand, etc.) which just makes it better! I can't wait to follow your path to (hopefully) success as an engineering youtuber!
Dude, first of all this is amazing, you are obviously a true fooser and finally built a foosball simulation worth playing... This is big. I'm so excited. I sent this to all my foos friends... Just the idea that I could zone out and practice solo is a game changer in itself. Tagging on to the end of your video here... I think with tweaks you've already realized that you have the ability to really fine-tune this thing to be unbeatable, But what's the fun in that? Chess against the computer is fun I'm sure, but as with the game of chess, the joy of foosball is really defined by the interactions between two players. I feel like you've might not be seeing the obvious next step: making a whole second control setup on the other side and allowing two people to play online against each other on a physical table. I have an idea here, and I'm going to send you a DM.
First off, I am in complete awe of what you did, from start to finish the meticulous detail is amazing. Second, this has been shared by many online foos groups so expect some praise and compliments from the foos community from all over. Third, how did you account for the recoil needed to straighten out those rollovers? Seeing those snake shots at that speed gave me nightmares of the one time I played Brandon Munoz and his insane speed. Also, and not to take one iota from this massive achievement, but have you seen the Foos Gadget one? It allows you to record a defense for a certain amount of time and then jump across the table to shoot against the defense you just recorded. It also has presets in a phone app that you can load up and send to the defensive rods with increasing difficulty, it's pretty cool. However, those stick lane passes that your machine does are insane, reminds me of Tony Spredeman lane passes. Lastly, there are some foosers already saying, "He should bring this to Worlds!" (Tornado World Finals, Lexington Kentucky, Labor Day weekend)
For the third, I didn't need to do much other than manually tune the timings on the snakes. The rotational motors are insanely fast, so even though the sideways motion to start the snake is faster than the average human's, when the ball is hit it has enough forward velocity that it's reasonably straight (hopefully I'm interpreting what you mean by recoil correctly here). This was actually a bit surprising to me; I originally started with the robot doing a push shot which I thought would be a lot more consistent, but it turns out snakes are much easier to get working. For the first lastly, not 100% which device you mean, from what I can tell Foos Gadgets just sells goal spedometers/automatic scoring. Regardless the goal of this project wasn't to be solely a training aid, I really wanted a fully autonomous table so I didn't spend much time on stuff like a practice app. For the last lastly, unfortunately it's probably not possible. I've already disassembled it (I want my room back!) and I'd like to move on to other projects for now. It's not out of the question though, it would be neat!
@@built-from-scratch Wow, I was only HOPING for a response and yet here you are! Yes, you interpreted the recoil I was speaking of correctly - when humans shoot a snake they need to strike the ball while moving in the opposite direction to offset the first rule of motion. From what you are saying, it sounds like your machine does it so fast that it doesn't allow spray, which is insane. It would have been cool to see what it did with a push, I have to recoil my push back to the wall so hard that it practically jars the table. Yeah, I added two "Lastly" paragraphs, sorry. I understand that us foosers probably won't see this at the next World or National Championships but it is impressive and the foos community would love to see it live and get a chance to meet someone who loved the game enough to attempt what you have done. Once again, bravo and keep creating!
Mad props on this, awesome. Only thing I'd try adding, as it doesn't go too deep in the weeds, would be to "take shots from any point you can find a clear path". Even if it misses, it will rebound hard, and your robotic front line has better reaction time than humans so it can chain another shot from there.
This is a case of where machine learning could really shine. There are so many kinds of networks that could be employed and be trained on. Furthermore, it could train itself since the win condition is pretty obvious. Would be also be interesting to pre-training in a mechanical simulation model before hitting the real model for training refinement.
I’m sure so many people have thought about this idea. I know I have. Ultimately we all thought.. yeah that’s going to be way too complicated. Really cool that you followed through with it!
Huge recommendation. Usually if you find yourself coding very small simple tasks humans are naturally familiar with… use a neural network. I’d love to see this in a new iteration but with nerfed action/reaction speeds for human viability and the robot actually being a great player.
this would be very much more interesting if it were a competition between teams consisting of people coming up with the computer vision part + AI for maybe creating tactics to circumvent the opponent and ofc the Mechanical side of things (not necessarily the physical construction but also how to use the table ) one system playing against the system of someone else ^^
That's an awesome project. I myself thought about building something like this 😍 can you try training a Neural network for playing table soccer. I would love to see different tactics that the machine would come up with
Really impressive mate - would love to see passing improved. But what would be great is introducing angles, especially side angles where you slam the ball into the side wall with the players. Considering this - it would be just too hard - so seriously the next logical step - and not too hard would be some machine learning with a bit of AI - tensorflow, OpenCV etc - you may have to model the entire system in 3D with Bullet or Jolt physics library.
Dude you’re awesome…. Can you make a video explaining your approach to coding this thing… how exactly you manage to code all the possible cases when the robot handling the ball… how does the robot make an offense strategy or is the same thing done very precisely… i would appreciate it if you do a video about it … thanks in advance
Now create a mirror of the robot to the other side of the table and throw some AI to learn from each other. Here is your senior project done and dusted lol
Now add a second robot system on the other side, use reinforced learning instead of pre-programmed moves and let them play against each other for a while. Then get surprised when you find out the robots started to use angled shots, managed to find physical exploits in your build and it's almost impossible to beat.
Next step, set up sensors that can detect the rotation and etc of all the rods, then play on it with friends for a few months until you've accumulated enough data to teach it how to play with ML
If you copied the controls on the other side and then put in a automatic ball dispenser you could let it play against itself with reinforcement learning and see how good it gets
Awesome project! Did you ever consider using a lil lidar sensor scanning the very bottom of the field to detect the ball? I think it could scan just below the feet of the players and detect the ball without any kind of top-mounted camera system. If im not missing something obvious, that might be a real cool solution. I might try that actually :D
Congratulations, you're the engineer I always aspired to be. Just a few questions: Why do your goalies have two side goalie-buddies? Also, when will we see an IA, instead of a procedural program, controlling the rods?
Make it do that obnoxious thing that beginner foosball players do where they just quickly spin the rods in the hopes of somehow catching the ball and immediately shooting it back. Like, make it just spin some of the rods very quickly for a few seconds at a time while also moving them up and down, like General Grievous or something
The robot turns the player a full revolution, that is not allowed I think. Are the the tables International foosball tables? As a Software developer myself, this is an awesome project and a great achievement. I play on a Bonzini at my workplace, and those are so great. Also the should when you block a shot, with those aluminium players, is great. The table is word and everything has a superb feel. Those table in this video looks like cheap and plastic compared to the Bonzini.
This is awesome. You could also take it a step farther without too much more difficulty. Keep the robot how it is but add another to the other side but instead for the new robot you use AI and have it learn against the robot until it is able to beat it.
as someone who wrote a bachelor's thesis on self playing foosball tables 9 years ago i am still impressed. using 5 cameras feels like cheating though (i had the restraint of analyzing video footage from competitive games). i did occlusion handling from the information i had about the balls trajectory, guessing under which player it is. with this camera system it's easy enough to find the player position and angle but it was easy enough without. Whats the frame rate of those cameras? are they only sensitive to the light they emmit/reflect? it turned out that 30 fps is not fast enough to track a pro players shot (the ball goes from mid to goal in 2 frames, rolling shutter applies) the robotics hardware seems pretty straight forward (still time consuming). but the software...oh the software...
Cool, out of curiosity which one did you work on? The cameras are shooting 200 fps, but they can go a bit higher if you compromise a bit on image quality I think
Awesome video! Love the fast-pace and presentation of clearly in-depth research about your criteria and constraints. I’m only a few minutes in and this is a great representation of the design process! I just had one suggestion: 4:18 - Although the idea of using this quote in this way seems funny, I don’t think I’m alone in saying this looks like blasphemy. I don’t have any intention to accuse you as a blasphemer, but I would recommend steering clear of playing with the Bible like this. Just a suggestion, thanks for a great video and awesome entertainment!!
I wonder if it'd be possible to build a second set of control rods, and then have two AI players play against each other repeatedly to improve themselves. Would the end result be a truly unbeatable foosball agent? :0
*Uploads a video that goes viral
*Disappears for 10 months
*Comes back with another banger
I love this.
The Michael Reeves Stratagem
and hes a little kid, 10 months to him is like 5 years. he'd even put Howard Wolowitz to shame
he probably worked 10 months on this
@@Turalcar That's who I immediately thought of.
Quality not quantity.
A new "Stuff Made Here" is born !
Amazing project.
If only he could stop using the exact same punch lines as SMH.
Really!
@@impact_42 Hey, at least he only did it once.
I came looking for this comment.
I was about to say this too!
A god-level foosball robot and it’s remotely controllable? Insane! Quite possibly the coolest toy anyone’s ever had in their bedroom
It is until you realize I have 5 cameras menacingly staring at my bed... (albeit not plugged in all the time)
@@built-from-scratchI’m curious if you thought about using some sort of gyroscopic/accelerometer equipped ball instead of the cameras?
I'd like to see another set of motors added to the other side and he can invite other programmers to challenge his programming. Add in more camera angles and hi-speed replays and you've got something.
@@rider573 same thing I thought about - instead of robots killing robots in arena - this gem!
@@BuLLGotcha So we need a ball that's the same size and with a similar surface that's hollow enough to contain an accelerometer and all it's gubbins. It must not be bouncy and must be shock resistant.
sounds kinda hard
With such projects across the internet the "getting there" part is usually pretty boring, so I often just skip to the good part of the presentation of the finished thing. But you've made the problem solving part as interesting as the final demo which made this video overall interesting to watch. Well done!
Bro if this shit doesn't blow up like your last. . . Man, that first seven seconds had me already hooked. It's not enough that you're building a robot, but you gotta pull off feats of skill like *that?* Man, my jaw dropped. Glad I subbed back then.
Alsp holy crap the flexing with that blind shot. You're nuts.
The companies that were smart enough to give you the materials for this project easily made their money back with the advertising, great video!
Video turned out amazing. Btw That's my hand in the stream at 13:48.
Can confirm if anyone had doubts about this prestigious honor, that was indeed him.
@@built-from-scratch Did the foosbar ever smack your fingers? XD
nice
Your hand is awesome, thank you so much for gracing us with such beautiful sight.
The hand made the video fr, I'd be otherwise very bored! Gracious sight!
I love that your brother has the confidence of a LLM!
Was this an LLM? It sounded like he wrote the instructions. Was actually gonna ask about using a model lol
Absolutely amazing seeing these young creaters spring up all over youtube
you could train neural networks by continually pitting them against each other on your real foosball table. you could then eventually (after a long time) and up with a neural network that is very good at irl foosball
Ideally you'd be able to model the game in software so it didn't need to physically play each game for training.
It would be interesting to see how well training on a simplistic model translated to playing in the real world. Hopefully well enough to work as pre training, which could be fine tuned with real games. It would speed up the overall training time significantly.
@@JscWilson Human players can currently beat the robot cause they have a better intuition of the real physics. So a NN would definitively need to learn this. A physics simulation would need to be very accurate to do the training in order to be better than the hand written software.
@@salia2897 "Intuition of the real physics" isn’t the only factor. Foosball is dynamic-another critical factor is how quickly a player or robot can receive input, make decisions, and act upon them.
As an extreme example, imagine a robot capable of perfect predictions but taking an hour to process them. Another robot with faster reaction times, but less accurate predictions, could score a goal before the slower robot could respond.
More accurate predictions are obviously better (all else being equal), but the robot doesn't need to have a better "Intuition of the real physics" to beat a human.
That is why I said it would be interesting to see how realistic the model would need to be to be useful.
One approach could involve initial training on a simpler and faster model, followed by fine-tuning on a more realistic yet slower model. Such a strategy might outperform dedicating the entire training time solely to the realistic model - but again, the question is how accurate do the models need to be?
@@jessewilson3571 It does not need a better one. But it does need one that is good enough to do the required maneuvers that humans can do. And doing that can only be learned from a physics model that is good enough and that will already be quite complicated.
@@salia2897 With a quick Google search, you can find a number of examples of foosball-playing neural networks that have been trained using simulations. This includes a few public GitHub repositories with Unity models that aren't very complex.
So, training on simulations can definitely be done with models that aren't extremely complex.
Nice job on this! I designed built one of these as well for Oklahoma State University, on ours I trained a neural network to control the rod actuators. Additionally a core objective of ours was to make it the same footprint as an actual foosball table because the previous version had the side mounted actuators like yours and was extremely large!
You're one of my favorite youtubers and you only have two videos! I think it's partially because you have a very similar style to another of my favorites, Stuff Made Here. You made a few (maybe unintentional, but probably not?) references to some of his jokes (only have to do it once, magic wand, etc.) which just makes it better! I can't wait to follow your path to (hopefully) success as an engineering youtuber!
The amount of passion into this is unleveled, UNBELIEVABLE JOB :O
Dude, first of all this is amazing, you are obviously a true fooser and finally built a foosball simulation worth playing... This is big. I'm so excited. I sent this to all my foos friends... Just the idea that I could zone out and practice solo is a game changer in itself.
Tagging on to the end of your video here... I think with tweaks you've already realized that you have the ability to really fine-tune this thing to be unbeatable, But what's the fun in that? Chess against the computer is fun I'm sure, but as with the game of chess, the joy of foosball is really defined by the interactions between two players.
I feel like you've might not be seeing the obvious next step: making a whole second control setup on the other side and allowing two people to play online against each other on a physical table.
I have an idea here, and I'm going to send you a DM.
First off, I am in complete awe of what you did, from start to finish the meticulous detail is amazing.
Second, this has been shared by many online foos groups so expect some praise and compliments from the foos community from all over.
Third, how did you account for the recoil needed to straighten out those rollovers? Seeing those snake shots at that speed gave me nightmares of the one time I played Brandon Munoz and his insane speed.
Also, and not to take one iota from this massive achievement, but have you seen the Foos Gadget one? It allows you to record a defense for a certain amount of time and then jump across the table to shoot against the defense you just recorded. It also has presets in a phone app that you can load up and send to the defensive rods with increasing difficulty, it's pretty cool.
However, those stick lane passes that your machine does are insane, reminds me of Tony Spredeman lane passes.
Lastly, there are some foosers already saying, "He should bring this to Worlds!" (Tornado World Finals, Lexington Kentucky, Labor Day weekend)
For the third, I didn't need to do much other than manually tune the timings on the snakes. The rotational motors are insanely fast, so even though the sideways motion to start the snake is faster than the average human's, when the ball is hit it has enough forward velocity that it's reasonably straight (hopefully I'm interpreting what you mean by recoil correctly here). This was actually a bit surprising to me; I originally started with the robot doing a push shot which I thought would be a lot more consistent, but it turns out snakes are much easier to get working.
For the first lastly, not 100% which device you mean, from what I can tell Foos Gadgets just sells goal spedometers/automatic scoring. Regardless the goal of this project wasn't to be solely a training aid, I really wanted a fully autonomous table so I didn't spend much time on stuff like a practice app.
For the last lastly, unfortunately it's probably not possible. I've already disassembled it (I want my room back!) and I'd like to move on to other projects for now. It's not out of the question though, it would be neat!
@@built-from-scratch Wow, I was only HOPING for a response and yet here you are! Yes, you interpreted the recoil I was speaking of correctly - when humans shoot a snake they need to strike the ball while moving in the opposite direction to offset the first rule of motion. From what you are saying, it sounds like your machine does it so fast that it doesn't allow spray, which is insane. It would have been cool to see what it did with a push, I have to recoil my push back to the wall so hard that it practically jars the table. Yeah, I added two "Lastly" paragraphs, sorry. I understand that us foosers probably won't see this at the next World or National Championships but it is impressive and the foos community would love to see it live and get a chance to meet someone who loved the game enough to attempt what you have done. Once again, bravo and keep creating!
When I was in college I played more foosball than I did studying. This is the coolest thing I've ever seen. You're brilliant my man!
This channel will grow faster than this robot can shoot the ball. Nice to have i third channel to choose next to Stuff Made Here and Mark Rober
Mad props on this, awesome. Only thing I'd try adding, as it doesn't go too deep in the weeds, would be to "take shots from any point you can find a clear path". Even if it misses, it will rebound hard, and your robotic front line has better reaction time than humans so it can chain another shot from there.
I love that you come up with an idea and then follow it through to completion, no matter what it is. This was a treat to watch!
Very impressive. Right up there with the self-solving Rubics cube.
This is a case of where machine learning could really shine. There are so many kinds of networks that could be employed and be trained on. Furthermore, it could train itself since the win condition is pretty obvious. Would be also be interesting to pre-training in a mechanical simulation model before hitting the real model for training refinement.
I am a primarily drunken foosball enjoyer, so I don’t encounter it often, but I am an engineer at heart; and holy hell this project is mad impressive.
Seems like the logical next step is for Tornado to host robot foosball competitions using their table as the standard playing field.
So glad I subscribed, this is fire. Excited to see what other projects you will work on!
I’m sure so many people have thought about this idea. I know I have. Ultimately we all thought.. yeah that’s going to be way too complicated. Really cool that you followed through with it!
Awesome work! I'd be really interested to see end to end deep reinforcement learning on this :)
Dude. Who are you? 😮 This is amazing. UA-cam algorithm took me here and i am staying! Keep up the mindblowing work!
Would be fun to see the foosball machine playing itself, while learning how to get better
“Foosball, also known as Table Soccer”
Damn, son, it was right there.
No way, he's back!
@StuffMadeHere This project seems right up your alley. How about a friendly Robot vs Robot competition?
Saw about 30 seconds and subscribed like i did for Stuff Made Here. The more the merrier!
What an incredible project and video, so glad I found your channel!
I've never seen someone good at foosball before so just the first like 7 seconds of this video was mindblowing enough.
Huge recommendation. Usually if you find yourself coding very small simple tasks humans are naturally familiar with… use a neural network. I’d love to see this in a new iteration but with nerfed action/reaction speeds for human viability and the robot actually being a great player.
So cool! Now plug another one in and have them play against each other.
this guy has uploaded 2 videos and they've both been absolutely insane
someone needs to bring all the robots together for a tournament
It is so tempting to build one now but I know I will cry before I even try
Protect this kid at all cost. This is the kid that will invent real virtual reality gaming for us!
I wasn't about to like this but when you mentioned that everything is opensource I instantly liked the video even before you could mention it.
Ohhh boy!! I would love to see all those different robots he showed in the beginning of the video competing against each other!!
i desperately need to see this man doing something with factorio
Subscribed! Thank you for sharing your talent, ingenuity and passion with us ☺
this would be very much more interesting if it were a competition between teams consisting of people coming up with the computer vision part + AI for maybe creating tactics to circumvent the opponent and ofc the Mechanical side of things (not necessarily the physical construction but also how to use the table ) one system playing against the system of someone else ^^
That's an awesome project. I myself thought about building something like this 😍 can you try training a Neural network for playing table soccer. I would love to see different tactics that the machine would come up with
8:51 Eric knows the internet well
I skipped the 10 month wait... now i have to wait for the next one... you are doing awesome sht
Really impressive mate - would love to see passing improved. But what would be great is introducing angles, especially side angles where you slam the ball into the side wall with the players.
Considering this - it would be just too hard - so seriously the next logical step - and not too hard would be some machine learning with a bit of AI - tensorflow, OpenCV etc - you may have to model the entire system in 3D with Bullet or Jolt physics library.
Great project! I loved to see this video. Now I'm waiting for the AI trained robot version.
SUCH a clever cookie! You're gonna go far kid
Now this... This is engineering. Amazing build!
Exceptionally great experimental physics and software here, Cheers !!
Glad I became part of your YT journey this early.
well done, gives me the vibe of micheal reeves combined with stuff made here, keep it up, im glad i got this recommended
2 videos and almost a 100k subscribers.. this channel is going to blow up!!!
Oh my gosh this is one of the best algorithm pulls EVER
If you make a second one and an automatic return mechanism for the ball and this thing would have the most epic endless battles!!
Amazing! And doing all of that in your bedroom... Keep up the awesome work!
Imagine a table with two of these playing each other
Dude you’re awesome…. Can you make a video explaining your approach to coding this thing… how exactly you manage to code all the possible cases when the robot handling the ball… how does the robot make an offense strategy or is the same thing done very precisely… i would appreciate it if you do a video about it … thanks in advance
damn the rach concerto
I'm officially gobsmacked. Brilliant.
Great project. Would also be cool if you could program it with different speeds and strategies.
I wanna see "stuff made here" build one and have a competition :D
Now create a mirror of the robot to the other side of the table and throw some AI to learn from each other. Here is your senior project done and dusted lol
Please do that for the other team too and let them play against each other while doing machine learning! :)
Amazing project man. Kudos for going all the way!
Now add a second robot system on the other side, use reinforced learning instead of pre-programmed moves and let them play against each other for a while. Then get surprised when you find out the robots started to use angled shots, managed to find physical exploits in your build and it's almost impossible to beat.
Next step, set up sensors that can detect the rotation and etc of all the rods, then play on it with friends for a few months until you've accumulated enough data to teach it how to play with ML
I wonder what a robot playing each side would look like.
Awesome video... and project! Thank you for sharing!
If you copied the controls on the other side and then put in a automatic ball dispenser you could let it play against itself with reinforcement learning and see how good it gets
This really screams for a foosball robot competition. Maybe you can get other builders involved for a competition
That is absolutely amazing - well done. I can see big things in your future.
Awesome project! Did you ever consider using a lil lidar sensor scanning the very bottom of the field to detect the ball? I think it could scan just below the feet of the players and detect the ball without any kind of top-mounted camera system.
If im not missing something obvious, that might be a real cool solution. I might try that actually :D
and now its time to send your robot to the RoboFoosball Thunderdome Throwdown. there can only be one
Congratulations, you're the engineer I always aspired to be. Just a few questions: Why do your goalies have two side goalie-buddies?
Also, when will we see an IA, instead of a procedural program, controlling the rods?
This is like Scott the woz with the skills of stuff made here!
That's a cool project for people to play against robots without having to invite a friend 😂😂
Amazing project, congrats! That one last addition is so cool too :O
Make it do that obnoxious thing that beginner foosball players do where they just quickly spin the rods in the hopes of somehow catching the ball and immediately shooting it back. Like, make it just spin some of the rods very quickly for a few seconds at a time while also moving them up and down, like General Grievous or something
i am sad it took me so long to find your channel its amazing
The robot turns the player a full revolution, that is not allowed I think. Are the the tables International foosball tables? As a Software developer myself, this is an awesome project and a great achievement. I play on a Bonzini at my workplace, and those are so great. Also the should when you block a shot, with those aluminium players, is great. The table is word and everything has a superb feel. Those table in this video looks like cheap and plastic compared to the Bonzini.
This is awesome. You could also take it a step farther without too much more difficulty. Keep the robot how it is but add another to the other side but instead for the new robot you use AI and have it learn against the robot until it is able to beat it.
A second stuff made here, perfect
You really are amazing. Please keep this up you're going to be the next stuff made here!
Well done young man!
You should have tried 2 layers of laminated acrylic to avoid flex. 3 layers if needed.
omg of course this is the same guy that made the terraria computer lol, this is just stupidly impressive and i love it.
as someone who wrote a bachelor's thesis on self playing foosball tables 9 years ago i am still impressed. using 5 cameras feels like cheating though (i had the restraint of analyzing video footage from competitive games). i did occlusion handling from the information i had about the balls trajectory, guessing under which player it is. with this camera system it's easy enough to find the player position and angle but it was easy enough without.
Whats the frame rate of those cameras? are they only sensitive to the light they emmit/reflect?
it turned out that 30 fps is not fast enough to track a pro players shot (the ball goes from mid to goal in 2 frames, rolling shutter applies)
the robotics hardware seems pretty straight forward (still time consuming).
but the software...oh the software...
Cool, out of curiosity which one did you work on? The cameras are shooting 200 fps, but they can go a bit higher if you compromise a bit on image quality I think
That's so cool! Wow, I am very impressed by what you achieved!!! Congrats!!!!🙌👊👏👏👏😆
GG! Finishing project like this is Huge achievement
Great video, great work. And lucky you for being provided with such expensive Equipment 🥰
Next step: Two robots playing against each other.
this is so fascinating, how many projects did it take you to get to this point and how did you learn engineering and coding at the same time?
Awesome video! Love the fast-pace and presentation of clearly in-depth research about your criteria and constraints. I’m only a few minutes in and this is a great representation of the design process! I just had one suggestion:
4:18 - Although the idea of using this quote in this way seems funny, I don’t think I’m alone in saying this looks like blasphemy. I don’t have any intention to accuse you as a blasphemer, but I would recommend steering clear of playing with the Bible like this.
Just a suggestion, thanks for a great video and awesome entertainment!!
You should have a tournament your robot against the other robots and vice versa
And here I was thinking you couldn't be good at foosball
I wonder if it'd be possible to build a second set of control rods, and then have two AI players play against each other repeatedly to improve themselves. Would the end result be a truly unbeatable foosball agent? :0