@yngwievanhendrix It is theoretically possible for an AHRS to track position (dead-reckoning) but often extremely difficult to implement practically. Check out some of my other videos for examples.
how can i do this with it reading just 1 axis. what would i need? i have the arduino nano already but i dont know what to use for a gyro and accelerometer. its going to control camera tilt in 1 direction (left to right) on a motorcycle. any ideas.?
@revoracer523 A 1 DOF version of this system would be very easy to achieve. You need to fuse the accelerometer and gyro data into single angular measurement of the horizon relative to the sensor. If the servo angle is constantly set to be equal to this angle then the camera will remain level. If you need more guidance then I suggest you ask this question in a forum.
Wow, I'm keen on something similar for my Arducopter aerial photography project. Could almost be used in conjunction with target acquisition for tracking a subject. Great video man, exciting.
Excellent work! How did this fare with sensor drift? Did the alignment of the camera drift away from the initial position if the sensors were left alone for a while? (particularly in yaw unless you coupled the yaw gyro with a magnetometer?)
Excellent work regardless. Very applicable in the real world.
Wow I see this thing going far. Imagine a war room shaped like a ball. Have someone in the middle with a rotating projector.Could use a small helmet for the imu unit. The next step would be to capture motion of someones head.
This video uses the x-io Board (which is discontinued). x-io's latest generation IMU product (The x-IMU) is planned to feature camera control/stabilisation with a forthcoming firmware update.
Hello, I'm working on a project for the University of Illinois and the NASA Student Launch Initiative, and we are considering building a camera mount very similar to this to put in the rocket. Could you possibly email me your report and any code you would be willing to share? Thanks so much for the great video!
There is no report. This demo was thrown together in an evening. It builds on other work I've done with IMU and AHRS sensors arrays - see my other videos their 'video descriptions' for links to source code, documentation, etc.
wow. i also on work for almost same 3- axis stabilization...but i end up sitting in front of a wall. could you help me by sending the papers for your great project.tq.
That is really amazing. It looks fast and robust. Is the control algorithm runs from the external PC or from the X-IO board?. Does any body have an idea?
That is all the resources I have. The report appendix contains platform independent algorithms implementations in C and the downloads include C# project folders with graphical outputs.
I'm a college intern from the Adler Planetarium in Chicago Illinois. I'm very lucky to find your video here because we started a project to make a camera stabilization system. Your system is exactly what we were envisioning for ours. Actually when we found your video we had our Razor 9DoF, Arduino Duemiladnove, and board camera sitting next to our laptops. I was wondering if you'd be willing to help us by sending the report. My email is dmiladinovich "at" gmail "dot" com. Thank you!
The camera control and stabilisation is as simple as the equalities presented in the video. The pitch/roll/yaw angles are obtained from the sensor array using a sensor fusion algorithm; for link (to report, source code etc.), see video description of video: "An efficient orientation filter for MARG sensor arrays...". YouTube prevents me form posting URLs here.
Thank you. We are awaiting acceptance of papers but I can send you a copy of my internal report, if you wish? It does not discuss hardware used in this video, only the sensor fusion algorithm.
This is amazing. I did something similar using 3d camera. One question for you. Using AHRS can i also estimate the position in 3D ???
yngwievanhendrix 1 month ago
@yngwievanhendrix It is theoretically possible for an AHRS to track position (dead-reckoning) but often extremely difficult to implement practically. Check out some of my other videos for examples.
SebMadgwickResearch 1 month ago
how can i do this with it reading just 1 axis. what would i need? i have the arduino nano already but i dont know what to use for a gyro and accelerometer. its going to control camera tilt in 1 direction (left to right) on a motorcycle. any ideas.?
revoracer523 2 months ago
@revoracer523 A 1 DOF version of this system would be very easy to achieve. You need to fuse the accelerometer and gyro data into single angular measurement of the horizon relative to the sensor. If the servo angle is constantly set to be equal to this angle then the camera will remain level. If you need more guidance then I suggest you ask this question in a forum.
SebMadgwickResearch 2 months ago
Nice, but you need faster servos. You can see the servo lag. The question I have, does it help in eliminating camera vibrations?
Nomoreidsleft 5 months ago
that is cool
vincentjanse 6 months ago
good work
tecnoshack 6 months ago
Wow, I'm keen on something similar for my Arducopter aerial photography project. Could almost be used in conjunction with target acquisition for tracking a subject. Great video man, exciting.
obooth 8 months ago
Excellent work! How did this fare with sensor drift? Did the alignment of the camera drift away from the initial position if the sensors were left alone for a while? (particularly in yaw unless you coupled the yaw gyro with a magnetometer?)
Excellent work regardless. Very applicable in the real world.
peter140988 9 months ago
The system uses an AHRS so there is no drift.
SebMadgwickResearch 9 months ago
good work
saa442 9 months ago
Nicely done! That's pretty good execution.
briansmobile1 9 months ago
Wow I see this thing going far. Imagine a war room shaped like a ball. Have someone in the middle with a rotating projector.Could use a small helmet for the imu unit. The next step would be to capture motion of someones head.
detectiveinspekta 11 months ago
That's so cool Id like to add 32 of those to my spaceship
plazmafeld 1 year ago
So when and where can I get something comparable to this?
canonphoto 1 year ago
Great job :)
canadese 1 year ago
Very nice!!!
gallenwolf 1 year ago
very good for my videos ........
Videoxon 1 year ago
Went to listed website but do not see this product listed. Is it for sale?
canonphoto 1 year ago
This video uses the x-io Board (which is discontinued). x-io's latest generation IMU product (The x-IMU) is planned to feature camera control/stabilisation with a forthcoming firmware update.
SebMadgwickResearch 1 year ago
How did you attach the servos together and the servo to the camera? Some sort of glue or screws?
reis1745 1 year ago
Glue gun AKA hot-melt adhesive. As I said previously, this was just a quick demo thrown together in few hours; the hardware was only temporary.
SebMadgwickResearch 1 year ago
Hello, I'm working on a project for the University of Illinois and the NASA Student Launch Initiative, and we are considering building a camera mount very similar to this to put in the rocket. Could you possibly email me your report and any code you would be willing to share? Thanks so much for the great video!
regan10@illinois.edu
Vertigoed12 1 year ago
There is no report. This demo was thrown together in an evening. It builds on other work I've done with IMU and AHRS sensors arrays - see my other videos their 'video descriptions' for links to source code, documentation, etc.
SebMadgwickResearch 1 year ago
Wall-E !
deadking13 1 year ago
need faster servos, i have the servos but not the system :D
great work!!!
benybeeJz 1 year ago
@benybeeJz :D I got the system but not the servos :D
canadese 1 year ago
wow. i also on work for almost same 3- axis stabilization...but i end up sitting in front of a wall. could you help me by sending the papers for your great project.tq.
misterpotato2 1 year ago
looks like just what I'm looking for.
rodstartube 1 year ago
That is really amazing. It looks fast and robust. Is the control algorithm runs from the external PC or from the X-IO board?. Does any body have an idea?
isaacfayad 1 year ago
The control algorithm is running on the PC but could easily run a a microcontroller. The x-io Board is an I/O board for PCs, not a standalone device.
SebMadgwickResearch 1 year ago
you should use faster servos, and then it would really work
A digital high speed servo...
josebuezas 1 year ago
Fantastic work. Thank you very much for sharing your paper and code!!!!
EuNaoBeboDetergente 1 year ago
Oh great! yeah i understand those but do you have any firmware / source code you would be willing to share?
Thanks again
dmiladinovich 1 year ago
That is all the resources I have. The report appendix contains platform independent algorithms implementations in C and the downloads include C# project folders with graphical outputs.
SebMadgwickResearch 1 year ago
HI,
I'm a college intern from the Adler Planetarium in Chicago Illinois. I'm very lucky to find your video here because we started a project to make a camera stabilization system. Your system is exactly what we were envisioning for ours. Actually when we found your video we had our Razor 9DoF, Arduino Duemiladnove, and board camera sitting next to our laptops. I was wondering if you'd be willing to help us by sending the report. My email is dmiladinovich "at" gmail "dot" com. Thank you!
dmiladinovich 1 year ago
The camera control and stabilisation is as simple as the equalities presented in the video. The pitch/roll/yaw angles are obtained from the sensor array using a sensor fusion algorithm; for link (to report, source code etc.), see video description of video: "An efficient orientation filter for MARG sensor arrays...". YouTube prevents me form posting URLs here.
SebMadgwickResearch 1 year ago
hi, very good, can I have more material of this project, firmware and other. thank You. my e-mail: vincenzo.rainone@gmail.com
MrHelicam 1 year ago
Absolutely beautiful. I'm struggling with using an HMC5843 for yaw positioning. Have you published anything yet?
Vortagg 1 year ago
Thank you. We are awaiting acceptance of papers but I can send you a copy of my internal report, if you wish? It does not discuss hardware used in this video, only the sensor fusion algorithm.
SebMadgwickResearch 1 year ago