6 ms·

Fast line-following robots

207 points by a1k0n 8y ago

a1k0n 8y ago
Didn't mention it in the post, but info about the car hardware and all the code is at https://github.com/a1k0n/cycloid https://github.com/a1k0n/cycloid
drivers99 8y ago
This is really inspiring. I played around with converting an RC car to self-driving with an arduino but it was very simplistic. It used an ultrasonic sensor (Parallax "Ping)))" sensor) to try to keep a specific range of distance from a wall to its left. It wasn't aware of its angle so it had a positive feedback loop in its reactions which caused it to oscillate more and more out of control. Just knowing there are people are there playing around with this for fun makes me want to get back into it.
- a1k0n 8y ago
  I think just adding a simple low-pass filter on your distance measurements and tracking the derivative for PD control would cure that problem. Try it!
- sgillen 8y ago
  Can also put two distance sensors on and fet the angle using some trig. And when you’re ready to get a little more serious you can get an imu and gps. Maybe even get a more beefy computer and add a camera!
  - drivers99 8y ago
    > Can also put two distance sensors on and fet the angle using some trig. That is exactly what I was planning to do next. I realized that when the angle was greater, it would see the distance to the wall as higher than it really is, because of trigonometry. And that is a positive feedback loop which makes it worse. (I just realized that is only true when it headed towards the wall at an angle, but is the opposite when heading away from the wall at an angle. It reacts later (steer right) when it's angle towards the wall, but it should react sooner (steer left) when it's angled away from the wall... hmm...) Getting the angle, I could set a target angle and distance together, and steer as needed.
TaylorAlexander 8y ago
Awesome post! I really need to attend the robo cars event. I’m working slowly on my own autonomous robot: https://youtu.be/UrVnzHuTtBk https://youtu.be/UrVnzHuTtBk
- a1k0n 8y ago
  Yeah, come check it out, it's pretty fun! https://www.meetup.com/DIYRobocars/ https://www.meetup.com/DIYRobocars/
hobolord 8y ago
This is great, I did a robotics course in uni that was essentially this. We never took it further than PID control though. https://www.youtube.com/watch?v=oDqfKm4Ovcg https://www.youtube.com/watch?v=oDqfKm4Ovcg That was a fun time in uni
- bufferoverflow 8y ago
  We did too. Had to use Lego Mindstorms. It was a pain in the a$$ to program back then. One of the guys built a very fast line-following robot, much faster than what we see here. It was simpler though, it was a solid black line.
  - berti 8y ago
    I remember having to do the solid black line with a couple of photo-diodes and a small AVR in first year EE. Was kind of a neat project thinking back, but we all hated it at the time because it soaked up quite a lot of time tuning it aggressively to beat everyone else without losing the track, going back where you came from, etc!
  - hobolord 8y ago
    luckily ours was arduino-ish and pretty simple to program. But we had to built everything since it was more of a mechanical + electrical design class, so there was lots of machine shop time
SubiculumCode 8y ago
This is pretty dang cool, imo.
bananasbandanas 8y ago
There is a similar competition in Germany called the CaroloCup. Here is a video of our run when I was still a student [1]. We used model-predictive control which evaluated about 10k trajectories with look-ahead, which works really well even when tires begin to degrade after a few minutes. You can see the effects in the video towards the end, where the car starts to slide, but the controller manages to catch it in time. Our CV was a bit more complex as we had to deal with missing line segments. We pre-processed the camera image with a distance transform, then used an optimization pass written in opencl to fit a 3rd-order polynomial to the image. [1] https://www.youtube.com/watch?v=Of_D_Z9gbeg https://www.youtube.com/watch?v=Of_D_Z9gbeg
- a1k0n 8y ago
  Nice! Are you doing probabilistic roll-outs, iLQR, or SQP, or what? What does your model look like? I've been struggling with this -- not sure how complex the tire dynamics model needs to be, for instance; do you need the whole Pacejka magic formula or is tanh() good enough?
  - gugagore 8y ago
    Do you know if there's work on adapting to the vehicle dynamics on the fly? The comment about tires degrading made me thing that there should be some parameters in the model corresponding to how degraded the tires are, and instead of relying purely on feedback to correct for model-mismatch, you could try to get a better model on the fly.
    - a1k0n 8y ago
      I'm aware of one paper which tries to fit a local polynomial model to the lateral dynamics, and they have a different model for different positions on the track (it requires really good localization to work): https://arxiv.org/abs/1610.06534 https://arxiv.org/abs/1610.06534 I had some of the vehicle parameters as part of my EKF for a while, but it led to some instabilities in the control. The main problem is that it's really hard to know what the car's instantaneous lateral velocity is. I think the best you can do is check the difference of velocity*gyro yaw rate and lateral accelerometer measurement to get a noisy lateral acceleration measurement, and that can tell you how well your tires are hooking up. I might try fitting a least-squares model on the fly with something like that.
adrianN 8y ago
A similar discipline is Micromouse, where robots have to solve mazes and then race the path they found. https://www.youtube.com/watch?v=NqdZ9wbXt8k https://www.youtube.com/watch?v=NqdZ9wbXt8k
Already__Taken 8y ago
Looking forward to seeing this thing remember the line each lap and refine its curve. At that point you're then working on traction control problems wouldn't you?
- a1k0n 8y ago
  Yes, that's the current state of the car. It's constantly fighting for traction; there are some lower-level control systems trying to maintain yaw rate (which automatically does things like counter-steering in a drift). I'll get to that in a future post.
cmontella 8y ago
Very cool! We ran a competition like this once for undergrads: https://vaderlab.wordpress.com/roscar-robot-stock-car-autonomous-racing/ https://vaderlab.wordpress.com/roscar-robot-stock-car-autono... It had to be a little more complex than line following, because at one point in the track there are a bunch of line crossings. So you had to do some mapping and tracking too in order to stay in the right lane. It's really fun seeing how fast you can make them go. One team maxed out the speed on the platform.
msadowski 8y ago
That's super interesting! How do you generate those canvases showing the algorithm behaviour? I think such animations could be very useful for teaching PID tuning. If you don't mind I would love to add this article in my next WeeklyRobotics (https://weeklyrobotics.com/ https://weeklyrobotics.com/) issue.
- a1k0n 8y ago
  The canvases are just some javascript code which draw to the 2d context after a requestAnimationFrame(): https://www.a1k0n.net/js/steering.js https://www.a1k0n.net/js/steering.js Sure, that sounds good!
elwell 8y ago
Wow, really the best email address spam protection method [0]: _=0;k;main(){while(_<641){for(k=0;"##K#8(38D-##C]L5870.X7\\M_b;90\\" "MC-M/NZGB6Q,I0VGB6a0FbN<VG.6Q\\bNb7^@`X=N@`XQaOVX:^]NX=:Z8PY]B`:>P" "NY8^$#SM):XA"[_/6]-35>>_++%6&1;k++);putchar(k[" _/\\\n,`)('<-"]);}} [0] - bottom of OP's homepage https://www.a1k0n.net/ https://www.a1k0n.net/
- a1k0n 8y ago
  Heh, you can just click on it to see the result if you don't want to actually compile it.
  - elwell 8y ago
    Pretty cool. Works here too: https://www.onlinegdb.com/online_c_compiler https://www.onlinegdb.com/online_c_compiler

207 points by a1k0n 8y ago

Didn't mention it in the post, but info about the car hardware and all the code is at https://github.com/a1k0n/cycloid https://github.com/a1k0n/cycloid

drivers99 8y ago

This is really inspiring. I played around with converting an RC car to self-driving with an arduino but it was very simplistic. It used an ultrasonic sensor (Parallax "Ping)))" sensor) to try to keep a specific range of distance from a wall to its left. It wasn't aware of its angle so it had a positive feedback loop in its reactions which caused it to oscillate more and more out of control. Just knowing there are people are there playing around with this for fun makes me want to get back into it.

a1k0n 8y ago
I think just adding a simple low-pass filter on your distance measurements and tracking the derivative for PD control would cure that problem. Try it!
sgillen 8y ago
Can also put two distance sensors on and fet the angle using some trig. And when you’re ready to get a little more serious you can get an imu and gps. Maybe even get a more beefy computer and add a camera!
- drivers99 8y ago
  > Can also put two distance sensors on and fet the angle using some trig. That is exactly what I was planning to do next. I realized that when the angle was greater, it would see the distance to the wall as higher than it really is, because of trigonometry. And that is a positive feedback loop which makes it worse. (I just realized that is only true when it headed towards the wall at an angle, but is the opposite when heading away from the wall at an angle. It reacts later (steer right) when it's angle towards the wall, but it should react sooner (steer left) when it's angled away from the wall... hmm...) Getting the angle, I could set a target angle and distance together, and steer as needed.

TaylorAlexander 8y ago

Awesome post! I really need to attend the robo cars event. I’m working slowly on my own autonomous robot: https://youtu.be/UrVnzHuTtBk https://youtu.be/UrVnzHuTtBk

a1k0n 8y ago
Yeah, come check it out, it's pretty fun! https://www.meetup.com/DIYRobocars/ https://www.meetup.com/DIYRobocars/

hobolord 8y ago

This is great, I did a robotics course in uni that was essentially this. We never took it further than PID control though. https://www.youtube.com/watch?v=oDqfKm4Ovcg https://www.youtube.com/watch?v=oDqfKm4Ovcg That was a fun time in uni

bufferoverflow 8y ago
We did too. Had to use Lego Mindstorms. It was a pain in the a$$ to program back then. One of the guys built a very fast line-following robot, much faster than what we see here. It was simpler though, it was a solid black line.
- berti 8y ago
  I remember having to do the solid black line with a couple of photo-diodes and a small AVR in first year EE. Was kind of a neat project thinking back, but we all hated it at the time because it soaked up quite a lot of time tuning it aggressively to beat everyone else without losing the track, going back where you came from, etc!
- hobolord 8y ago
  luckily ours was arduino-ish and pretty simple to program. But we had to built everything since it was more of a mechanical + electrical design class, so there was lots of machine shop time

SubiculumCode 8y ago

This is pretty dang cool, imo.

bananasbandanas 8y ago

There is a similar competition in Germany called the CaroloCup. Here is a video of our run when I was still a student [1]. We used model-predictive control which evaluated about 10k trajectories with look-ahead, which works really well even when tires begin to degrade after a few minutes. You can see the effects in the video towards the end, where the car starts to slide, but the controller manages to catch it in time. Our CV was a bit more complex as we had to deal with missing line segments. We pre-processed the camera image with a distance transform, then used an optimization pass written in opencl to fit a 3rd-order polynomial to the image. [1] https://www.youtube.com/watch?v=Of_D_Z9gbeg https://www.youtube.com/watch?v=Of_D_Z9gbeg

a1k0n 8y ago
Nice! Are you doing probabilistic roll-outs, iLQR, or SQP, or what? What does your model look like? I've been struggling with this -- not sure how complex the tire dynamics model needs to be, for instance; do you need the whole Pacejka magic formula or is tanh() good enough?
- gugagore 8y ago
  Do you know if there's work on adapting to the vehicle dynamics on the fly? The comment about tires degrading made me thing that there should be some parameters in the model corresponding to how degraded the tires are, and instead of relying purely on feedback to correct for model-mismatch, you could try to get a better model on the fly.
  - a1k0n 8y ago
    I'm aware of one paper which tries to fit a local polynomial model to the lateral dynamics, and they have a different model for different positions on the track (it requires really good localization to work): https://arxiv.org/abs/1610.06534 https://arxiv.org/abs/1610.06534 I had some of the vehicle parameters as part of my EKF for a while, but it led to some instabilities in the control. The main problem is that it's really hard to know what the car's instantaneous lateral velocity is. I think the best you can do is check the difference of velocity*gyro yaw rate and lateral accelerometer measurement to get a noisy lateral acceleration measurement, and that can tell you how well your tires are hooking up. I might try fitting a least-squares model on the fly with something like that.

adrianN 8y ago

A similar discipline is Micromouse, where robots have to solve mazes and then race the path they found. https://www.youtube.com/watch?v=NqdZ9wbXt8k https://www.youtube.com/watch?v=NqdZ9wbXt8k

Already__Taken 8y ago

Looking forward to seeing this thing remember the line each lap and refine its curve. At that point you're then working on traction control problems wouldn't you?

a1k0n 8y ago
Yes, that's the current state of the car. It's constantly fighting for traction; there are some lower-level control systems trying to maintain yaw rate (which automatically does things like counter-steering in a drift). I'll get to that in a future post.

cmontella 8y ago

Very cool! We ran a competition like this once for undergrads: https://vaderlab.wordpress.com/roscar-robot-stock-car-autonomous-racing/ https://vaderlab.wordpress.com/roscar-robot-stock-car-autono... It had to be a little more complex than line following, because at one point in the track there are a bunch of line crossings. So you had to do some mapping and tracking too in order to stay in the right lane. It's really fun seeing how fast you can make them go. One team maxed out the speed on the platform.

msadowski 8y ago

That's super interesting! How do you generate those canvases showing the algorithm behaviour? I think such animations could be very useful for teaching PID tuning. If you don't mind I would love to add this article in my next WeeklyRobotics (https://weeklyrobotics.com/ https://weeklyrobotics.com/) issue.

a1k0n 8y ago
The canvases are just some javascript code which draw to the 2d context after a requestAnimationFrame(): https://www.a1k0n.net/js/steering.js https://www.a1k0n.net/js/steering.js Sure, that sounds good!

elwell 8y ago

Wow, really the best email address spam protection method [0]: _=0;k;main(){while(_<641){for(k=0;"##K#8(38D-##C]L5870.X7\\M_b;90\\" "MC-M/NZGB6Q,I0VGB6a0FbN<VG.6Q\\bNb7^@`X=N@`XQaOVX:^]NX=:Z8PY]B`:>P" "NY8^$#SM):XA"[_/6]-35>>_++%6&1;k++);putchar(k[" _/\\\n,`)('<-"]);}} [0] - bottom of OP's homepage https://www.a1k0n.net/ https://www.a1k0n.net/

a1k0n 8y ago
Heh, you can just click on it to see the result if you don't want to actually compile it.
- elwell 8y ago
  Pretty cool. Works here too: https://www.onlinegdb.com/online_c_compiler https://www.onlinegdb.com/online_c_compiler