Never tried to make one, but i think the different part is when in aimlab, the target and background already have contrast color, so he can 'increase' the contrast, meanwhile in real fps game, the target is probably a character that is more blend to the background, so i assume the program would need to access the enemy character model, render it in different color that is contrast to the background, then continue with the same process. Again, just assumption.
@@Alex-de7rz I think Object recognition + Image classification might do the trick. No need to pin point the exact boundary of the character model, just draw a box over the character model and try to hit the center of that frame. May need to handle the delay and character movement tho.
@@welovethemallthesame1125 Yo en mi proyecto de tesis para acortar tiempos pasé de tensorflow a AWS Rekognition y era muy fácil el aprendizaje del modelo, en su momento creé un sistema de videovigilancia que detectaba objetos personales perdidos, supongo que la aplicación debe ser muy similar, sólo que al detectar un personaje de Valorant dispare... Claro que es más fácil decirlo, hay mucho ensayo y error.
I agree. You need to take note if 1. The mouse has mouse accel on/not, make sure it’s not 2. How many Gs the mouse can handle in terms of speed? Most modern gaming mice can handle adequate Gs that we mere humans cannot reach. 3. Do you turn off Windows pointer precision? This may cause you to do those complicated maths. My point is, replace the mouse and turn off Windows pointer precision. I recommend at minimal a Logitech G304 since thats the cheapest most adequate wireless gaming mouse I can think of; The more variables you can control, the merrier. Nice work!
@@barjuandavis Windows pointer precision doesn't affect games that use raw input (99% of modern shooters). Also, if anything, he should ideally just turn the sens up a shit ton and make the motors as precise as possible.
@@re4796 that's not my point. It proves that your mouse and screen don't matter that much when your movements are perfect. You don't need a fancy gaming mouse to be that good, otherwise the robot would not be be able to achieve the scores.
Possible improvements: (physical) - unshell the mouse and mount its optical sensors directly onto the robot. This will reduce rattle/wiggle and ditch the mass of the shell. - replace the mouse buttons with relays that can be directly triggered. - move as many components as possible into a separate stationary breakout box, again, to reduce the mass of the mobile unit. Ideally, your mousedroid will have only motor drives, wheels and the optical sensor(s) within the mobile unit. (possible complete reconstruction) - consider keeping the sensor itself completely stationary and inverted (pointing up) and moving the surface instead (a thin piece of roughened plastic that is easily optically trackable and could be moved with a geared/belted X/Y setup. - or, mount the sensor in the same way as the printing head of a 3D printer over the tracking surface. (programming) - keep tabs on the velocity of the mousedroid and don't just take the proximity of the target into account, but also try to select targets that are also in line with the current direction of motion to reduce the amount that the mouse has to turn.
Thank Mark for watching! These suggestions are great, and some of them I do plan on doing for a V2. This was really a demo, and was me really seeing if I can do it. But I don't like how bulky the system is so I am going to take a part a mouse and make a new much slimmer and faster system coming soon. Also, I love your name you gave to the mouse --- mousedroid is fantastic, and I might still that for the future video!
I am a backend developer, but I took 2 embedded systems courses, I like this a lot combining hardware with software with Machine Learning is just amazing and a complex task oh man , you are a "Real" software engineer, you had an idea and you made it into reality and kept developing it congratulations
Thanks for the kind words, and understanding how much work went into this! Software engineering is something else really difficult, but these one off programming challenges are fun.
Awesome stuff. An algorithm change to allow shots while on the move should give you those extra points. Plan ahead for the optimum path, re-evaluate if targets change, shoot as you pass the target on the way to the next. That's how the humans do it. Never slow down, and estimate distances in terms of time to get there, not physical distance. You might also want to get an old school rubber ball mouse, toss the ball, and turn the rollers directly.
@@niezbo And if you want, you could skip the motors entirely, and instead simply blink LEDs at a rate that suits you. The movement in a particular direction is detected by two photo junction devices that look at a LED through a perforated disk. Skip the disk and the LED, and excite the sensors with two of your own LEDs directly to create the movement you want. The challenge is to get the timing right, but once there, the number of moving parts is 0.
Go a step further. See how the mouse sends the electrical signal through USB and use an arduino to simulate mouse movement by sending the right vdc x and vdc y.
@@Shedding There's (some) danger in that one. It is conceivable that a future gaming product might look for that kind of a hack. So if you do it, it better emulate all of a gaming mouses behavior... That said, the standard mouse signaling over USB is well defined and plenty of sample code exists out there.
Cool video and nice work! I feel like the PID tuning would be much easier of you focus on singular events. For example if you let the robot shoot a couple of targets and then make a plot of "error" over time, you might have an easier time making the PID feedback faster while keeping an eye on overshoot and unwanted oscillations. Probably too much work but it would be cool to see these kind of plots!
First off thanks for watching. Yeah I have some plot of those errors I didn't think it made for interesting content but will write a technical post about that. And when I make a V2 I can add that in.
I think that and even bigger improvement could be made by using optimal control techniques instead of PID. In the video, it looks like the robot tends to overshoot some targets when it starts move large distances. Maybe using LQR or something and optimizing around minimizing some objective outputs would give much better system response than just tuning PID by hand.
i just postet it already now. i see, this would have been the right place. cnc-servo-motors are controlled with 3 pids. position->pid->speed->pid->torque->pid->dutycycle. sounds complicated, but makes tuning much easier in the end.
I think that you could get a couple more points by optimising the targetting algorithm. Instead of targeting the closest circle,.you could turn this into a travelling sales man problem, to select the shortest path. Because there are only 3 circles visible at once, there only 6 (3!) possibilities. You could add those paths into an array, sort it by total distance and pick the shortest path and repeat after every hit. Also, tuning the values for the mouse, sounded liie something you could also turn into an ML project
Very cool! The fastest way to get a screenshot is to copy directly from the game’s back buffer by hooking the Present function in the D3D render pipeline. This involves writing a small library and injecting the DLL into the game’s process. A much simpler method involves using the Windows GDI API. It’s not as fast, but you can still reach a few hundred FPS. You’d probably be able to achieve much higher scores by improving your kinematics. Directly driving two axes rather than using omniwheels will reduce slipping and allow you to increase acceleration.
Wow thanks watching and thanks for the information the screenshotting tips sound real helpful and I will look into them. My V2 will be still using wheels, but down the line definitely want to try with a 2 axis gantry.
Use gaming mouse with a good switch and good sensor. The higher DPI will help the robot tracking. By using unhumanly high sensitivity you can get the robot to aim with little (but precise) movement
Old trackball mice might be better for this as the mechanics required can be smaller and fit in the void for the ball. In reality you could also just disassemble the mouse completely to get to the bar rollers...
You could strip the mouse down to just its sensor and board for a smaller footprint. It'd probably be more accurate with it's reduced weight minimising inertia. You could also suspend it in place and have a small sliding base under the sensor.
You could try using a 3d printer gantry to move the mouse faster and more precisely, the mouse could be held stationary while the mousepad moves under it
You just need to detect a color pixel, one optimization can be made in the size of screen capture you take(resolution), make it as small as possible which still keeps the accuracy of detection high. So as to reduce the load on computation. Maybe as low as 128x128 for a 1:1 display. let me know how this may affect your performance
the problem with this is real life, in a game the more you lower resolution the lower information you have, which may cause the robot to not detect a head
3d printers cap out at 5-6 meters per second. They are incredibly accurate too. I suggest modifying your setup to use this tech. Gut the mouse and just have the laser attached to the print head. Lock the Z axis, and set some real records!!
imagine the origin of AI, instead of coming from high tech massive giants like Boston Dynamics or Raytheon searching for absolute manmade sentient conscience - it started from a TH-camr trying to create a perfect aimbot. kudos and godspeed, Kamal.
This is such an awesome project, came across the video on your tiktok and you’re making super high quality content, keep it up man, and I can’t wait to see how far you can go
Not a python developer but have you tried pillow module to take the center of the screen instead of the whole screen as a screenshot? I just imagine there's a lot of dead space around the edges that could be cropped to make the image smaller for faster encoding. Possibly faster to use .PNG encoding but not 100% sure on that. from PIL import ImageGrab ss_region = (300, 300, 600, 600) ss_img = ImageGrab.grab(ss_region) ss_img.save("SS3.png")
I had a similar idea but with a metal frame and when you move one end of the frame to the other it does a 360 turn so u can get more consistent results with a steadier frame for faster flicks
Great work! A couple of suggestions: First, opencv library in python it's easy to use and setup but if you manage to code it in c++ you would improve the perfomances. Second, as far as for the PID controller. I dont know the gains you set but it's importat to have the correct sample time (for you it would be the frequency at which you execute the PID) since it influence the effectiveness of the control. Moreover, given you case, it might be enough to have a PD controller that basically has the integration gain set as zero (or just a very little value compared to the other two). The proportional part let you have a fast response while the derivative avoid the mouse to go over the target. However, again, great work! I love it! Edit: I realized too late that the video is old..lol
Great job, as a vision engineer, i really impressed ! I don't use python/open source in my industrial project, but maybe OpenCv in C++ is faster ? For the modelisation in the discrete automation is really math heavy, you've done a great job to find the value by trying !
Hello, thank you for your kind words, especially from someone that do computer vision for a living. How would you go about simplifying this model of the system because at the moment it's definitely nonlinear and wheel slippage will be a problem? Would you first get it into state space form?
OpenCV-python is just a wrapper around the C++ library so it shouldn't actually be much faster to switch, provided you are using numpy and not native python features
I also do computer vision stuff, and I usually cv2.split(frame) to get the blue, green and red frame, and then just get the mask by cv2.subtract(g,b) to get the mask that only green stuff remains
This with an arm would probably rip. I think the wheels and traction as cool as they are add a lot of inaccuracies and slowness to the entire system. Still sick though 😁
Intellectually interesting, but potentially gameplay ruining: If someone were to perfect and market such a device, it would be harder to detect (as you said), which would ruin the FPS gaming experience for gamers who treat it as a sport (e-sport). I never understood why people created bots for games if they weren't good at it knowing it would ruin the experience for others, and I think your project enlightens me a bit. Perhaps, they do it to solve a programming problem and out of intellectual curiosity. However, ironically, it destroys the reason for playing FPS games; people play to be competitive against other people, not to be competitive against computer programs. I did enjoy how you broke down each part into a step and explained how it progressed the idea further.
Yes I see the worry some people have. This was mainly for my own intellectual curiosity. When I try this in real games I will only do it with custom matches with friends. Cheating sucks, so I don't want to ruin someone I don't know day.
@@KamalCarter yet you have proved the cheaters this is viable and theres already a machine learning ai that detected enemies in Cod cold war and warzone with a super hight succes rate, combine that with this and you have an undetectable cheat
This is really great! I've done each piece of this project for other things and I never would've thought you could throw thresholding, PID controllers, and basic distance calculations into a controller and wire it up to a omniwheel rig around a mouse and make it an aimbot, that's so creative! Great work!!
Thank you for watching! Similar to you I have done each of those things individually PID, Computer Vision, Robot Design and that's why I felt confident I could do this projectm
this is really cool! if your gameplay gets audited most games will ban you for dual mouse inputs though, spoofing an arduino as a mouse fixes this, in your case you might need 2 arduino + host shields since you have a physical robot rather than just sending the arduino serial commands.
This is awesome. No doubt you could've passed Tenz's score if you spent more time tweaking your design, but that's besides the point, this was so neat.
Honestly, I wonder how big of a difference the mouse would've made. Going from a cheap wireless office mouse to a proper gaming mouse is a huge difference for humen, let alone a robot.
Well, now the hardest part, feeding bot the data from game to teach how to find players. I saw someone doing something like that a while ago, very interesting thing. Great thing to study
Its really impressive to see your robot hit 118k even with a burnt out motor. Before I stopped playing fps my aimlabs score sat around 103k though am I no expert by all means, realistically anything higher than 100k isn't necessary for anyone at all.
A couple of suggestions, use a better mouse with custom DPI, G-203 would be enough, also, if you make it for other games, you'll need 2 mice, one for the robot and another for the player, and both at different DPI. Otherwise great execution, as interesting as the other AI powered aimbot that someone showcased working outside the machine running the gane.
For people who code, we all know this not as simple as his explanation. Great work.
How would this be able to work in an actual fps game? There are so many different colors everywhere?
@@ProdByCari good question. probably require a lot more AI 'training'
Never tried to make one, but i think the different part is when in aimlab, the target and background already have contrast color, so he can 'increase' the contrast, meanwhile in real fps game, the target is probably a character that is more blend to the background, so i assume the program would need to access the enemy character model, render it in different color that is contrast to the background, then continue with the same process. Again, just assumption.
@@Alex-de7rz I think Object recognition + Image classification might do the trick. No need to pin point the exact boundary of the character model, just draw a box over the character model and try to hit the center of that frame. May need to handle the delay and character movement tho.
@@welovethemallthesame1125 Yo en mi proyecto de tesis para acortar tiempos pasé de tensorflow a AWS Rekognition y era muy fácil el aprendizaje del modelo, en su momento creé un sistema de videovigilancia que detectaba objetos personales perdidos, supongo que la aplicación debe ser muy similar, sólo que al detectar un personaje de Valorant dispare... Claro que es más fácil decirlo, hay mucho ensayo y error.
Please give that robot a better mouse. You're holding it back
I agree. You need to take note if
1. The mouse has mouse accel on/not, make sure it’s not
2. How many Gs the mouse can handle in terms of speed? Most modern gaming mice can handle adequate Gs that we mere humans cannot reach.
3. Do you turn off Windows pointer precision? This may cause you to do those complicated maths.
My point is, replace the mouse and turn off Windows pointer precision. I recommend at minimal a Logitech G304 since thats the cheapest most adequate wireless gaming mouse I can think of; The more variables you can control, the merrier. Nice work!
Give that robot some RGB lighting + mouse with RGB lighting, instantly 200x Pro
Nah he doesn't have to
@@thickgirlsneedlove2190 does he want a gamer robot or not? Make that mouse look like a Christmas tree!
@@barjuandavis Windows pointer precision doesn't affect games that use raw input (99% of modern shooters). Also, if anything, he should ideally just turn the sens up a shit ton and make the motors as precise as possible.
Way late, but this was one of the coolest videos I've seen. Good ingenuity
This is true physical: "I Made Real-life Airsoft AIM-ASSIST: Aimbot V3"
3:10 “This took me 2 painstaking months.”
This proves that you can get pro level aim with a cheap wireless mouse and a high latency screen.
@QUAD849 His OpenCV code taking screenshots is slow, compared to "pro gaming 100000Hz RGB monitors".
@ Nooo it isn't slow
No it doesn't its quite literally a robot
@@re4796 that's not my point. It proves that your mouse and screen don't matter that much when your movements are perfect. You don't need a fancy gaming mouse to be that good, otherwise the robot would not be be able to achieve the scores.
@ I hope to God you're joking
Move the mousepad, not mouse
Ohhhh!!! Damn smart!!!
It’s cheating
It's easy to say but the whole program will change if you invert the moving medium. He don't make the code he just copied it.
It's even easier to just emulate a mouse with an arduino
@@respise You don't have any idea how gameguard/anticheat program works. Arduino devices are an old school cheat using it will detect you easily.
0:01 "whole round of ammo" 💀
Possible improvements:
(physical)
- unshell the mouse and mount its optical sensors directly onto the robot. This will reduce rattle/wiggle and ditch the mass of the shell.
- replace the mouse buttons with relays that can be directly triggered.
- move as many components as possible into a separate stationary breakout box, again, to reduce the mass of the mobile unit. Ideally, your mousedroid will have only motor drives, wheels and the optical sensor(s) within the mobile unit.
(possible complete reconstruction)
- consider keeping the sensor itself completely stationary and inverted (pointing up) and moving the surface instead (a thin piece of roughened plastic that is easily optically trackable and could be moved with a geared/belted X/Y setup.
- or, mount the sensor in the same way as the printing head of a 3D printer over the tracking surface.
(programming)
- keep tabs on the velocity of the mousedroid and don't just take the proximity of the target into account, but also try to select targets that are also in line with the current direction of motion to reduce the amount that the mouse has to turn.
Thank Mark for watching! These suggestions are great, and some of them I do plan on doing for a V2. This was really a demo, and was me really seeing if I can do it. But I don't like how bulky the system is so I am going to take a part a mouse and make a new much slimmer and faster system coming soon. Also, I love your name you gave to the mouse --- mousedroid is fantastic, and I might still that for the future video!
@@KamalCarter You can also completely ditch the mouse and make the micro controller pretend to be a mouse.
@@gSys1337 yes but the whole point is tho have a physical aimbot
Dude joined TH-cam 15 years ago!
@@topkek5853 microcontroller can act as a HID device too... So that will be convenient..
Now I wanna see an aim lab tournament with this against 5 pros lol
I am a backend developer, but I took 2 embedded systems courses, I like this a lot
combining hardware with software with Machine Learning is just amazing
and a complex task
oh man , you are a "Real" software engineer, you had an idea and you made it into reality and kept developing it
congratulations
Thanks for the kind words, and understanding how much work went into this! Software engineering is something else really difficult, but these one off programming challenges are fun.
That was an awesome project! I was super impressed with how well it turned out. I’m sure that you could beat TenZ with a little more optimizing.
I'm happy you enjoyed it. I, too, think I could have beat Tenz, but it would have taken a considerable more amount of work.
Sick idea, even sicker execution!
I had the same idea i just never learned to code cuz i got sick
Where is V2 ?
Actually sounds like a great idea
He already made it. It's the second most recent video, called undetectable AI robot aimbot
Another genius using his powers for evil lol
Awesome stuff. An algorithm change to allow shots while on the move should give you those extra points. Plan ahead for the optimum path, re-evaluate if targets change, shoot as you pass the target on the way to the next. That's how the humans do it. Never slow down, and estimate distances in terms of time to get there, not physical distance.
You might also want to get an old school rubber ball mouse, toss the ball, and turn the rollers directly.
Using ball mouse is actually pretty damn good idea!! It would require only to motors with small torque. It could be extremely fast!
@@niezbo And if you want, you could skip the motors entirely, and instead simply blink LEDs at a rate that suits you.
The movement in a particular direction is detected by two photo junction devices that look at a LED through a perforated disk. Skip the disk and the LED, and excite the sensors with two of your own LEDs directly to create the movement you want. The challenge is to get the timing right, but once there, the number of moving parts is 0.
Go a step further. See how the mouse sends the electrical signal through USB and use an arduino to simulate mouse movement by sending the right vdc x and vdc y.
@@Shedding There's (some) danger in that one. It is conceivable that a future gaming product might look for that kind of a hack. So if you do it, it better emulate all of a gaming mouses behavior... That said, the standard mouse signaling over USB is well defined and plenty of sample code exists out there.
@@akiko009 yep. There might already be someone who did this already. :)
Cool video and nice work!
I feel like the PID tuning would be much easier of you focus on singular events. For example if you let the robot shoot a couple of targets and then make a plot of "error" over time, you might have an easier time making the PID feedback faster while keeping an eye on overshoot and unwanted oscillations.
Probably too much work but it would be cool to see these kind of plots!
First off thanks for watching. Yeah I have some plot of those errors I didn't think it made for interesting content but will write a technical post about that. And when I make a V2 I can add that in.
I think that and even bigger improvement could be made by using optimal control techniques instead of PID. In the video, it looks like the robot tends to overshoot some targets when it starts move large distances. Maybe using LQR or something and optimizing around minimizing some objective outputs would give much better system response than just tuning PID by hand.
i just postet it already now. i see, this would have been the right place.
cnc-servo-motors are controlled with 3 pids. position->pid->speed->pid->torque->pid->dutycycle. sounds complicated, but makes tuning much easier in the end.
I think that you could get a couple more points by optimising the targetting algorithm. Instead of targeting the closest circle,.you could turn this into a travelling sales man problem, to select the shortest path.
Because there are only 3 circles visible at once, there only 6 (3!) possibilities.
You could add those paths into an array, sort it by total distance and pick the shortest path and repeat after every hit.
Also, tuning the values for the mouse, sounded liie something you could also turn into an ML project
RIP SHOOTERS 1987-2022, THANKS
Very cool! The fastest way to get a screenshot is to copy directly from the game’s back buffer by hooking the Present function in the D3D render pipeline. This involves writing a small library and injecting the DLL into the game’s process. A much simpler method involves using the Windows GDI API. It’s not as fast, but you can still reach a few hundred FPS. You’d probably be able to achieve much higher scores by improving your kinematics. Directly driving two axes rather than using omniwheels will reduce slipping and allow you to increase acceleration.
Wow thanks watching and thanks for the information the screenshotting tips sound real helpful and I will look into them. My V2 will be still using wheels, but down the line definitely want to try with a 2 axis gantry.
that mean kernel cheat guard certainly detect that?
Actually People didn’t won, if you give the robot a better mouse and faster click and rotation speed it could dominate e-sporters too
Use gaming mouse with a good switch and good sensor. The higher DPI will help the robot tracking. By using unhumanly high sensitivity you can get the robot to aim with little (but precise) movement
Yeah bro, also higher sens allows the mouse to hit a target without moving a long distance, which will speed it up a bit.
Legends say even the game developers approved him for his innovative idea.
Kamal, you could apply for NASA or similar. You've a natural interest, you can solve the problem, you can get the results. You achieve.
Old trackball mice might be better for this as the mechanics required can be smaller and fit in the void for the ball. In reality you could also just disassemble the mouse completely to get to the bar rollers...
Glad to see your back creating content hopefully in a more regular basis.
And this was the humble beginning of Mr. Glass
how can a human being be this creative
put that robot on a gaming chair it will hit 200k no cappp
I just heard about this. Pretty impressive skills you are showing off. Great work!
Thank you for watching. More content to come!
would love to see you develop this further
Props for not using this strong aim bot in game :)
Thanks man. But you might not like what I do in the next video.
You could strip the mouse down to just its sensor and board for a smaller footprint. It'd probably be more accurate with it's reduced weight minimising inertia. You could also suspend it in place and have a small sliding base under the sensor.
自瞄滑鼠墊感覺是個不錯的東西
這樣馬達就不用再負擔滑鼠的重量
The way it can be improved so much, make me think the extent of robots and Ai powers. And bro just casually made it.
Awesome work man, very cool project!
daaaaamn 4:26 👏 👏 👏
wow, what a nice piece of robot you made 😳👍
have a few ideas for the V2 if you want 😊
Let me hear them! I have ideas in my head and am working on some things but would love to hear what others say.
Bro you have potential in youtube, keep making these bangers
You could try using a 3d printer gantry to move the mouse faster and more precisely, the mouse could be held stationary while the mousepad moves under it
good idea!
You just need to detect a color pixel, one optimization can be made in the size of screen capture you take(resolution), make it as small as possible which still keeps the accuracy of detection high. So as to reduce the load on computation. Maybe as low as 128x128 for a 1:1 display.
let me know how this may affect your performance
the problem with this is real life, in a game the more you lower resolution the lower information you have, which may cause the robot to not detect a head
3d printers cap out at 5-6 meters per second. They are incredibly accurate too. I suggest modifying your setup to use this tech. Gut the mouse and just have the laser attached to the print head. Lock the Z axis, and set some real records!!
imagine the origin of AI, instead of coming from high tech massive giants like Boston Dynamics or Raytheon searching for absolute manmade sentient conscience - it started from a TH-camr trying to create a perfect aimbot. kudos and godspeed, Kamal.
This is such an awesome project, came across the video on your tiktok and you’re making super high quality content, keep it up man, and I can’t wait to see how far you can go
"The crux of it was, I was changing three numbers around for days" - yep, sounds about right.
ur a genuis, motivation 101
Thank you for the kind words
when the terminators attack we gotta call tenz
Wow... what a nice piece of wheels... cleverrrr ❤
And also, nice coding!
Probably would be much easier to mount just 2 motors directly to ball-mouse sensors
The year is 2035, anti chest now requires you to install a camera in your home aimed at your computer and feed the recording to your motherboard.
Not a python developer but have you tried pillow module to take the center of the screen instead of the whole screen as a screenshot? I just imagine there's a lot of dead space around the edges that could be cropped to make the image smaller for faster encoding. Possibly faster to use .PNG encoding but not 100% sure on that.
from PIL import ImageGrab
ss_region = (300, 300, 600, 600)
ss_img = ImageGrab.grab(ss_region)
ss_img.save("SS3.png")
Nicely done.
I believe the Sentdex (on yt) has made a gta bot. He also ran into slow screen capture but solved it somehow.
It's like watching a video from "stuff made here" similar style. Talking ect.
I had a similar idea but with a metal frame and when you move one end of the frame to the other it does a 360 turn so u can get more consistent results with a steadier frame for faster flicks
Great work! A couple of suggestions:
First, opencv library in python it's easy to use and setup but if you manage to code it in c++ you would improve the perfomances.
Second, as far as for the PID controller. I dont know the gains you set but it's importat to have the correct sample time (for you it would be the frequency at which you execute the PID) since it influence the effectiveness of the control. Moreover, given you case, it might be enough to have a PD controller that basically has the integration gain set as zero (or just a very little value compared to the other two). The proportional part let you have a fast response while the derivative avoid the mouse to go over the target.
However, again, great work! I love it!
Edit: I realized too late that the video is old..lol
@@111Crytek hey love suggestions the video is old but this definitely process for improvement
Great job, as a vision engineer, i really impressed ! I don't use python/open source in my industrial project, but maybe OpenCv in C++ is faster ?
For the modelisation in the discrete automation is really math heavy, you've done a great job to find the value by trying !
Hello, thank you for your kind words, especially from someone that do computer vision for a living. How would you go about simplifying this model of the system because at the moment it's definitely nonlinear and wheel slippage will be a problem? Would you first get it into state space form?
Totally agreed c++ will make a better program in terms of speed, and ofc an AMAZING PROJECT! Love it!
OpenCV-python is just a wrapper around the C++ library so it shouldn't actually be much faster to switch, provided you are using numpy and not native python features
@@chawakornchaichanawirote1196 correct the CV was very fast due to the python wrapper
Fair play no Cheats
This whole video was entertaining af
I also do computer vision stuff, and I usually cv2.split(frame) to get the blue, green and red frame, and then just get the mask by cv2.subtract(g,b) to get the mask that only green stuff remains
I find it faster than hsv threshold, as I work on computer vision for FRC competitions
then you can blur, or erode the mask to filter out noise from the mask, then get the contours, center of contours, and so on
I swear engineering people are the one that we shouldn't be messing with
Bruh why didnt youtube recommend this much sooner i sub for your work you put into this video
I welcome our robot masters.
And people thought learning ML via C++ was tough. Your dedication is insane,keep up the good work.
Great robot man. Great video pacing and editing too
That is very impressive
Yes do more video about this this could destroy p2w games
Great video
This with an arm would probably rip. I think the wheels and traction as cool as they are add a lot of inaccuracies and slowness to the entire system. Still sick though 😁
Very surprised you have such little subscribers for this high quality content
Tell me about it! Thank you for watching the video though.
fast way to screenshot on python would probably be dxcam, pretty much the fastest way to do screenshots possible.
This was awesome man. Actually so cool
really nice video
You shoot a whole round of ammo and miss wow that's crazy. A whole round?? Damn
Multiplayer's days are numbered
"do you shoot a some whole round of ammo" is some "do you blow your nose with a whole tissue" shit haha
iv never seen the subscribe button glow like that when u said like and subscribe lol that was cool
Intellectually interesting, but potentially gameplay ruining: If someone were to perfect and market such a device, it would be harder to detect (as you said), which would ruin the FPS gaming experience for gamers who treat it as a sport (e-sport).
I never understood why people created bots for games if they weren't good at it knowing it would ruin the experience for others, and I think your project enlightens me a bit. Perhaps, they do it to solve a programming problem and out of intellectual curiosity. However, ironically, it destroys the reason for playing FPS games; people play to be competitive against other people, not to be competitive against computer programs.
I did enjoy how you broke down each part into a step and explained how it progressed the idea further.
Yes I see the worry some people have. This was mainly for my own intellectual curiosity. When I try this in real games I will only do it with custom matches with friends. Cheating sucks, so I don't want to ruin someone I don't know day.
You kids really think he's the first to make a hardware aimbot. Was your first shooter fortnite?
@@KamalCarter yet you have proved the cheaters this is viable and theres already a machine learning ai that detected enemies in Cod cold war and warzone with a super hight succes rate, combine that with this and you have an undetectable cheat
The pro player training session was insane
This is really great! I've done each piece of this project for other things and I never would've thought you could throw thresholding, PID controllers, and basic distance calculations into a controller and wire it up to a omniwheel rig around a mouse and make it an aimbot, that's so creative! Great work!!
Thank you for watching! Similar to you I have done each of those things individually PID, Computer Vision, Robot Design and that's why I felt confident I could do this projectm
Awesome job, man. Keep it up. I'd like to see more stuff like that
This guys content is underated🙌👏👏
Idk why he stop uploading tho
Nice 😂 nice Idea. would like to have something like that too 😂
cool experiment
You could use a Ball Mouse and.just directly inject your movement to the rollers
Honestly, this is crazy.
That is amazing!!!
I’ve done 91,876 , definitely not as good as I used to be but i’m 40 years old with arthritis.
That’s what 30 years of video games gets you.
I'd like to see it on osu. I wonder if it can, at least, match top 10k players.
this is really cool! if your gameplay gets audited most games will ban you for dual mouse inputs though, spoofing an arduino as a mouse fixes this, in your case you might need 2 arduino + host shields since you have a physical robot rather than just sending the arduino serial commands.
Great attempt. You did good. Detecting players in a real game is much harder….and slower
This is awesome. No doubt you could've passed Tenz's score if you spent more time tweaking your design, but that's besides the point, this was so neat.
Honestly, I wonder how big of a difference the mouse would've made.
Going from a cheap wireless office mouse to a proper gaming mouse is a huge difference for humen, let alone a robot.
0 chance you could beat his score on this setup with all of the 'tweaking' in the world.
Well, now the hardest part, feeding bot the data from game to teach how to find players. I saw someone doing something like that a while ago, very interesting thing. Great thing to study
Very cool
I would love you to put the whole documentation somewhere so that we could read it!
Its really impressive to see your robot hit 118k even with a burnt out motor. Before I stopped playing fps my aimlabs score sat around 103k though am I no expert by all means, realistically anything higher than 100k isn't necessary for anyone at all.
This video deserves 1 million view
You can actually plug-in a hardware monitor emulator and read image directly from its input instead of taking screenshots.
Awesome work! Getting the PIDs right is an act already. But making all of this... Insane!
Nice
things that can improve your robot are mechanum wheels and a better mouse
A couple of suggestions, use a better mouse with custom DPI, G-203 would be enough, also, if you make it for other games, you'll need 2 mice, one for the robot and another for the player, and both at different DPI.
Otherwise great execution, as interesting as the other AI powered aimbot that someone showcased working outside the machine running the gane.