Detect the iPhone rotation spin?

Question

Hello all,

I want to create an application could detect the number of spin when user rotates the iPhone device. Currently, I am using the Compass API to get the angle and try many ways to detect spin. Below is the list of solutions that I've tried: 1/ Create 2 angle traps (piece on the full round) on the full round to detect whether the angle we get from compass passed them or not. 2/ Sum all angle distance between times that the compass is updated (in updateHeading function). Let try to divide the sum angle to 360 => we could get the spin number

The problem is: when the phone is rotated too fast, the compass cannot catch up with the speed of the phone, and it returns to us the angle with latest time (not continuously as in the real rotation).

We also try to use accelerometer to detect spin. However, this way cannot work when you rotate the phone on a flat plane.

If you have any solution or experience on this issue, please help me.

Thanks so much.

Answer 1

You could use the velocity of the acceleration to determine how fast the phone is spinning and use that to fill in the blanks until the phone has stopped, at which point you could query the compass again.

Answer 2

The iPhone4 contains a MEMS gyrocompass, so that's the most direct route.

As you've noticed, the magnetometer has sluggish response. This can be reduced by using an anticipatory algorithm that uses the sluggishness to make an educated guess about what the current direction really is.

First, you need to determine the actual performance of the sensor. To do this, you need to rotate it at a precise rate at each of several rotational speeds, and record the compass behavior. The rotational platform should have a way to read the instantaneous position.

At slower speeds, you will see a varying degree of fixed lag. As the speed increases, the lag will grow until it approaches 180 degrees, at which point the compass will suddenly flip. At higher speeds, all you will see is flipping, though it may appear to not flip when the flips repeat at the same value. At some of these higher speeds, the compass may appear to rotate backwards, opposite to the direction of rotation.

Getting a rotational table can be a hassle, and ensuring it doesn't affect the local magnetic field (making the compass useless) is a challenge. The ideal table will be made of aluminum, and if you need to use a steel table (most common), you will need to mount the phone on a non-magnetic platform to get it as far away from the steel as possible.

A local machine shop will be a good place to start: CNC machines are easily capable of doing what is needed.

Once you get the compass performance data, you will need to build a model of the observed readings vs. the actual orientation and rotational rate. Invert the model and apply it to the readings to obtain a guess of the actual readings.

A simple algorithm implementation will be to keep a history of the readings, and keep a list of the difference between sequential readings. Since we know there is compass lag, when a difference value is non-zero, we will know the current value has some degree of inaccuracy due to lag.

The next step is to create a list of 'corrected' readings, where the know lag of the prior actual values is used to generate an updated value that is used to create an updated value that is added to the last value in the 'corrected' list, and is stored as the newest value.

When the cumulative correction (the difference between the latest values in the actual and corrected list exceed 360 degrees, that means we basically don't know where the compass is pointing. Hopefully, that point won't be reached, since most rotational motion should generally be for a fairly short duration.

However, since your goal is only to count rotations, you will be off by less than a full rotation until the accumulated error reaches a substantially higher value. I'm not sure what this value will be, since it depends on both the actual compass lag and the actual rate of rotation. But if you care only about a small number of rotations (5 or so), you should be able to obtain usable results.

Answer 3

If you're using an iPhone 4, the problem has been solved and you can use Core Motion to get rotational data.

For earlier devices, I think an interesting approach would be to try to detect wobbling as the device rotates, using UIAccelerometer on a very fine reporting interval. You might be able to get some reasonable patterns detected from the motion at right angles to the plane of rotation.