Controlling Self Driving Cars
ฝัง
- เผยแพร่เมื่อ 20 ก.ค. 2015
- [IEEE CSS Video Clip Contest 2015 Submission]
This is a video introduction to controlling self-driving cars, specifically using PID-control. Special emphasis is placed on how the proportional, integral, and derivative gains affect the performance of the vehicle.
Music:
th-cam.com/users/audiolibrary... - Solar Flares
Video References:
DARPA Urban Challenge MIT footage
Google Earth
Dog Driving Car • Meet Monty. The World'...
Car in Parking Lot • Strong Wind Blows Over...
Truck • Video
Credits:
Script & Narration: Luke Johnson
Hardware & Control: Brett Lopez
Visualization: Shih-Yuan Liu
Editing & Overlays: Justin Miller
Lab footage courtesy of:
Aerospace Controls Laboratory @MIT
Jonathan P. How, Director - วิทยาศาสตร์และเทคโนโลยี
As someone with masters on control engineering, I can safely say that this is the easiest to follow introduction to PID controllers I've seen. Wish my professor had told it like this in the first class instead of throwing 4 whiteboards full of Laplace transforms.. .
Haha, couldn't agree more!
same here
So true
+! dude)
Same here. My mouth was agape half-way through.
PID beautifully explained.
By far the best PID control tutorial i've seen. Far better than that Aero engineering class I took in last fall term.
i disagree. th-cam.com/video/qKy98Cbcltw/w-d-xo.html
Currently working on implementing self-driving vehicle behavior for my video game, and this is exactly what I needed! Thank you so much!
And our brain does this perfectly once we know how to drive. now that's cool.
Our Brain works more like an MPC (model predictive control) I think
our brain does not use the PID model, although for some tasks we have been observed doing this
our brain mimics this for controlling our limbs.
the best PID algorithm tutorial I have seen. The visual aids makes it so much easier to understand and give an intuition
Very good introduction to closed loop PID controllers. Video and narration was very well done.
That made way more sense than other videos! Thank you so much for your clear explanation!
One of the best explanations and associated animation of PID control I've ever seen. Well done.
i disagree. th-cam.com/video/qKy98Cbcltw/w-d-xo.html
PID BOOOM! As I watch more and more videos and read more on PID control, it is getting clearer to me! fascinated by this beauty!
very well explained, i love when the complex topic is explained via breaking in down into simpler pieces
The best explanation and visualisation ever. No body else can do it better.
This video is beautifully well made. Awesome job guys!
The best PID explanation I have sen so far! Good Job!
Found this while trying to understand PID in 3D printer temperature control. Amazed at how almost exactly the same these issues are
Of all all youtube video i saw regarding car autonomy this one is the most detailed and easy to understand
One of the best PID controller explanation!!!
This video with the formulas are the perfect example of the new way to learn. Nice videos guy!
Very good explanation on PID controllers
As expected from MIT :)
so beautifully explained about the PID ^.^
Very well stated and simple explanation of PID control. Kudos.
Fantastic video! A great introduction to PID control.
One of the best PID explanations that i have ever seen...
That's the most beautiful lecture, I have ever heard!!
Great video and explanation of PID
Very nice visualization!
one of the best explanation of PID control!. thanks!
This is currently the best example of PID control I have ever seen.
the best tutorial I have found so far on PID control. Thank you! it helped a lot.
i disagree. th-cam.com/video/qKy98Cbcltw/w-d-xo.html
I can say this is the best explanation of PID control on Utube
Brilliant! An excellent presentation! Easy to understand.
I feel like i am going to forget this cause its late, but one of the best and simplest explanations i have seen....when you learn things the smart way :) sucks we all learn different at times
Excellent video, thank you for sharing!
BEST video ever for PID! Even under 5 minutes. Good job!
i disagree. th-cam.com/video/qKy98Cbcltw/w-d-xo.html
good explanation on PID. Congrats guys
this is exactly how I created my ksp throttle hover control script, And I didn't even think about it that much
Great video and explanation on PID control. Thank you.
great job for controll PIDs thank you
The best PID explanation
I took this class and I just now know what does PID mean.
Well done my Prof "You know what I'm saying" I heard that sentence more than the times I heard my name
This is probably the only video that gives a proper intuition about PID control. I wanted to develop that intuition to tune the roll, pitch, and yaw controls of my drone. None of the drone experts know how to properly explain the impact of changing P, I, and D.
What a phenomenal video.
god damn I finally found a video that properly explains every part of a PID controller.
Your video explanation is intuitive. Please make a video on Model Predictive Controller, Linear Quadratic Controller, H-Infinity Controller and Observer, Sliding Mode Control, Controllability, Observability, etc. :D
As an FPV quadcopter flyer I found this very interesting. We use PID values to tune our quadcopters.
+FPVSpace right on
+FPVSpace agree
Agreed, up
i disagree. th-cam.com/video/qKy98Cbcltw/w-d-xo.html
This is the best control theory video I’ve ever seen.
That Save tho! a@ 3:03
Amazing explanation.
Wonderful explanation.
The best explanation ever
incredible! thank you so much for your wonderful video! pls do more! subbed
Nice explantion!
Thanks, great explanation
Great explaination for intermediates! Keep it up!
I’d intuitively reasoned out these three ideas from analysing how my car drives and holds its lane centre, but only in a basic form and had no real grasp of what was at play. This video was brilliant, explained it really well while taking us through to an understanding of the higher concepts and mathematics!
Pretty nice explanation!
Im a brazilian in high school and im preparing to a robotics competicion, thank you so much, this explanation was perfect to me.
FRC?
Omg I finally understand this! This helped a lot thanks!!
Really good explanation about PID without mention PID first.
It’s always a amazing how our brains can function so well & handle so many things.
I came for the example and explanation of the PID, but oh dear, this caught me off guard. What a recovery that was! A human PID tuned to perfection! 3:02
Outstanding!
amazing vid
Great content
Amazing Video!!!!!
I love this video, and I love you
Pro truck-driver!
this is exactly what i was looking for. Im in design school prototyping a autonomous beer buggy
thank u for sharing this info :)
This is the best
Props for them to use an actual rc car, trackers and a projector instead of just a simulation
Awesome nice excellent
you are great
I have never had a class on PID controllers, but I am trying to use them in my holonomic robot. It is really difficult trying to tune a PID controller, while dealing with the motor configuration of a holonomic robot!
Thank you 😊 sir
Awesome
Can you share the code and design requirement?
It will be of great help
Title nothing mention PID, but PID beautiful explained.
could i get more details on the implementation of PID
its cool as hell
# passionate about your thesis
Nice
Thanks for this great video. I just have a question, how can we derive the relationship between the cross tracking and the steering angle? Are there any documents written about this? Thank you in advance.
By code use open cv paython
You should use car body approach angle in proportional gain method and add steering wheel angle to control that parameter. Your approach to relate steering wheel angle directly is wrong.
how i can find the best value of the constante
Which microcontroller is best for this type of control??
How to click the thumbs up multiple times?
huh thought it was gonna be a video on MPC but ok i guess its a quick PID vid.
what is the cross track error to a curve? will the car follow a curve path?
So what is the back up system.....Embedded road sensors?
good thx
Pretty standard control-system theory.
+Ray Perkins Yes, and there are a lot of videos explaining it, but fewer more clear than this. IMO you can't have too many explanations of such basic concepts, because you want as many ways to explain them as possible to maximize the number of people who really "get it."
Interesting, graphical and logical.Like to bring my regulatory technology the best.
Can you please name those advanced controllers u mentioned at 4:10 please
Nice explanation and visualization of PID, but probably not the best controller for a non-linear system as a car ;)
tuloski works for this video since there is a constant reference. But I agree, for a non linear potential path, this wouldn't be sufficient
Would PID be appropriate for following curved paths? If so, what error function should be used?
It should respond fine with the functions already given, the path is curved, so as the vehicle turns to correct it will continue turning until the path straightens out again. You can see it moving along a curved path at the end of the video.
The trick/difficulty is in defining the path to follow, not necessarily in following it. PID will do fine along a curved target path, provided the gradients and time constants are appropriate to the actuators/inputs.
I want the code that do this please
Sorry, but I couldn't get what's going on at 3:19 . I mean, even though the car gets off the track due to some external factors, knowing that it is off the path, the already existing P and D are there to steer it in the right direction right?
What's the advantage of this PID when it's compared with pure-pursuit, and for the point-to-point trajectory tracking how come you guys keep away from using the MPC controller?
hope you share the answer if you got it
Nice explanation! But why would the PD system not correct itself after the rocks incident?
Let's say in the normally working car with only a P control, the scaling was such that 1m left error causes a 1deg right steering command. After the alignment gets knocked, all steering commands are mechanically remapped 1deg the the left. So the same 1m left error, now gives 0deg steering (the electrically commanded 1 deg right, minus the 1 deg mechanical offset)