Accelerometers are used to sense both static (gravity) and dynamic (sudden starts/stops) acceleration - in m/s² or g.
Gyroscopes measure angular velocity, how fast something is spinning about an axis - in RPM, or degrees per second.
Accelerometer data are noisy, Gyros tend to drift; the combination (data fusing) gives usable information
haha97: 33cm (13")
Gibby623: I received my 3800mAh 12V Battery, the robot will (should) balance this weekend
Here is a comparaison between the raw accelerator angle (red) and the Kalman filtered angle (blue)
The smoothing effect is impressive :o P1020588 - YouTube?
I know you are going to get swarmed for your code for the Kalman, but I am really struggling getting this to work. Can you detail how you went about this? Was the programming intensive? ...
Hi Gibby623, sorry, I just got your PM's
If your robot rolls about the x axis, you only need GYR_X, ACC_Y and ACC_Z
I notice that signal quality is much better when the sensor is upward, apparently, the IMU does not appreciate to be up side down
I will publish the full code pretty soon
I was so busy with my other projects that I neglected my balancing robot (I bought smaller motors and same Pololu wheels, they plug in directly on the motor shaft). I have a 2 axis accelerometer and a one axis gyro, do you think it will suffice or should I get a 5 axis IMU?
Hi Kas, awesome work on the project! My mate at uni was showing this to me today looks cool, great progress!
I am also working with an IMU a 6dof one and just wondering for your kalman filter above, how did you find the covariance matrices for measurement error and process error? lke what did you do and stuff?
Because im upto that aswell, i have my state space of the kalman filter, just dont understand how to get the covariance matrix.
Any help would be appreciated.
I hope your robot will balance soon
Two axis accelerometer & one axis gyro are OK for the job
If you use separate breakout boards, make sure that axis are orthogonal, you may end up having the gyro board being perpendicular to the main board.
Also sensors units should match, don't fuse radian with deg/sec in your code
Finally the backlash we talked about is noticiable, but manageable
why is mine so bad... Sigh...
I understand your frustration, I have been pursuing this quest nearly for 2 years
Please post photos of your bot, together with the code, I will look for possible obvious reasons
i will do this later,if i success[ch65292]i'll show my pictures.
i got a question ,why do you put the battery on the top[ch65311]
i think that if you put it on the bottom,you can controll the balance better.
i think that if you put it on the bottom,you can controll the balance better.
I know nothing about balancing robots, but I would tend to think having the mass at the top would be easier to balance. Try to balance a pencil on your hand, then try it with a weight on top (blob of clay), then a weight near the hand - you'll find its easier with the weight at the top. I imagine the same would be true for a robot (ie, inverted pendulum)...
i think that if you put it on the bottom,you can controll the balance better.
I know nothing about balancing robots, but I would tend to think having the mass at the top would be easier to balance. Try to balance a pencil on your hand, then try it with a weight on top (blob of clay), then a weight near the hand - you'll find its easier with the weight at the top. I imagine the same would be true for a robot (ie, inverted pendulum)...
Your are right cr0sh
the robot acts as an inverted pendulum and works better when the weight is high (it increases intertia and allows more reaction time).
Try to balance a broom in the palm of your hand and see which side is easier to balance.
However, PID parameters need different tuning
Hi Kas, awesome work on the project! My mate at uni was showing this to me today looks cool, great progress!
I am also working with an IMU a 6dof one and just wondering for your kalman filter above, how did you find the covariance matrices for measurement error and process error? lke what did you do and stuff?
Because im upto that aswell, i have my state space of the kalman filter, just dont understand how to get the covariance matrix.
Any help would be appreciated.
Thanks!!
Kalman filter module works pretty well but is still a Black Box for me
I tried hard to understand and finally gave up. :o
I am confused, on the let's make Robots site, you stated that thanks to Dallaby your robot balances. Now, Dallaby uses a complementary filter. You mention you are using a Kalman filter. So, is this the case, if so what is the contribution from Dallaby?
I am asking because I am trying to start similar project and not sure whether to spend more time trying to be able to run the kalman routines or go ahead with the complementary filter. Several sites talks very good about this simpler approach.