Hello! I'm in a group at Chalmers University of Technology that are working on a self stabilized quadcopter with position hold, see picture.

We've got a little problem: We need to know the speed relative to the ground in x, y and z. What's the best way to handle this?

THANKS!


You need to be a member of diydrones to add comments!

Join diydrones

Email me when people reply –

Replies

  • Thanks everyone for your input!

    We have decided to control our quadcopter with position (not velocity) using GPS, an absolute pressure sensor and a magnetometer.

    More info and pics about the quadcopter will be posted soon! =)
  • While the absolute error for GPS chips can be quite big, their drift in the short term (minutes) is very small. So for distances relative to the start point, they are pretty good. You need to be outdoors and have very good sat readings.

    That said, you're reqs are probably pretty tight and for testing you will need a system that will work indoors (for testing at least). Then it is pretty much image flow that you need to use, like the parrot quad copter (at CES). They use a downward facing camera and process the image into, I think, 16 sectors. They then find edges or other distinctive features in the image and compare XY positions of those from frame to frame to determine orientation and movement.

    Works indoors (using horrible carpet with nasty designs) and outdoors. Needs a fair bit of processing power, but small arm boards should do it. http://designsomething.org/leopardboard/default.aspx

    Look up optical flow in google

    http://www.google.ie/search?hl=en&safe=off&client=firefox-a...

    Great looking platform you have. Any info on specs, etc

    Cheers

    Diarmuid
  • That's a pretty good idea! But how good will the measurements of the speed be, calculated by GPS?
  • There's a couple of ways to go about this. The simplest is just to differentiate the latitude and longitude given by GPS, and that'll give you your x and y. GPS altitude isn't really accurate enough to give a z, so for that you need an airspeed, from something like the pressure sensor sold on this site. Then just compare the airspeed, which is sqrt(x2 + y2 + z2) to the groundspeed, which is just sqrt(x2 + y2), and from the difference between the two you can get your z velocity.
This reply was deleted.

Activity

DIY Robocars via Twitter
RT @TinkerGen_: "The Tinkergen MARK ($199) is my new favorite starter robocar. It’s got everything — computer vision, deep learning, sensor…
Monday
DIY Robocars via Twitter
Monday
DIY Robocars via Twitter
RT @roboton_io: Join our FREE Sumo Competition 🤖🏆 👉 https://roboton.io/ranking/vsc2020 #sumo #robot #edtech #competition #games4ed https://t.co/WOx…
Nov 16
DIY Drones via Twitter
First impressions of Tinkergen MARK robocar https://ift.tt/36IeZHc
Nov 16
DIY Robocars via Twitter
Our review of the @TinkerGen_ MARK robocar, which is the best on the market right now https://diyrobocars.com/2020/11/15/first-impressions-of-tinkergen-mark-robocar/ https://t.co/ENIlU5SfZ2
Nov 15
DIY Robocars via Twitter
RT @Ingmar_Stapel: I have now explained the OpenBot project in great detail on my blog with 12 articles step by step. I hope you enjoy read…
Nov 15
DIY Robocars via Twitter
RT @DAVGtech: This is a must attend. Click the link, follow link to read the story, sign up. #chaos2020 #digitalconnection #digitalworld ht…
Nov 15
DIY Robocars via Twitter
RT @a1k0n: Got a new chassis for outdoor races (hobbyking Quantum Vandal) but I totally didn't expect that it might cause problems for my g…
Nov 11
DIY Drones via Twitter
First impressions of the Intel OpenBot https://ift.tt/36qkVV4
Nov 10
DIY Robocars via Twitter
Nov 9
DIY Robocars via Twitter
Excellent use of cardboard instead of 3D printing! https://twitter.com/Ingmar_Stapel/status/1324960595318333441
Nov 7
DIY Robocars via Twitter
RT @chr1sa: We've got a record 50 teams competing in this month's @DIYRobocars @donkey_car virtual AI car race. Starting today at 10:00am…
Nov 7
DIY Robocars via Twitter
Nov 6
DIY Robocars via Twitter
RT @a1k0n: Car's view, using a fisheye camera. The ceiling light tracking algorithm gave me some ideas to improve ConeSLAM, and having grou…
Nov 5
DIY Robocars via Twitter
RT @a1k0n: To get ground truth I measured the rug, found the pixel coordinates of its corners, calibrated my phone camera with my standard…
Nov 5
DIY Robocars via Twitter
RT @a1k0n: @DIYRobocars is back in December, but outside. Time to reinvestigate ConeSLAM! I rigged up a quick and dirty ground-truth captur…
Nov 5
More…