I have been experimenting with the Core Motion framework to detect a user spinning around, say on a merry-go-round, holding an iphone in his hand.
There are ways to detect the device motion around its own axes, but what is a good way to detect the iPhone spinning in circles?
Thanks
You can use the gyroscope. Take a look here: Gyroscope example
You have to remind that it is only availble on iPhone4 and iPhone4S.
There is one degenerate case where you can run into trouble, only magnetometer (compass) can help in that particular case.
If you put the device (a) on the desk in stationary position then (b) on a perfectly horizontal turntable rotating slowly you will get the same qualitative sensor readings. Both the gyro and the accelerometer readings are constant in the two cases, although the readings quantitatively differ. The sad part is: gyro bias error can render case (a) to look like (b) and vice-versa. In this particular case you need a compass to cancel the gyro drift. Case (a) is typical for a phone.
Apart from this degenerate case, gyroscopes and accelerometers with sensor fusion are sufficient to track arbitrary rotations of the device.
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I have a GPS app that I would like to detect if the user is standing still and not moving. Using Core Location works for this, but is sometimes not accurate because new updates move and gives the illusion of speed and motion.
So, I am wondering if in addition to that, I can also use Core Motion. Is this a good idea to detect motion such as someone walking, running, driving, etc, and know when they are no longer doing that motion? Or, is Core Motion only for small movements such as tilting the device or lifting it to your ear?
I wanted to tell others who visit this question what I've learned and what I think about this approach.
I have been doing some research of my own to know whether this is possible, and more importantly, even if it is what is the battery consumption and accuracy of the location change detected. For Android though, this question was asked quite sometime back. The answer provides links to this Google Tech Talk. At 23:20, the speaker talks about how difficult it is to achieve this and the accuracy you will achieve in the results.
Even though I have to come to realize the battery consumption from sensors on the iPhone is a little lesser than in most Android phones, I still think this is a costly affair in terms of accuracy and battery consumption.
you can use the GPS with the sensor readings to distinguish between walking, running, etc. if you combine the tilt angle frequency change and the GPS speed information (you need to do some work to get some of this info of course, but thats the way to do it).
You are talking about 4 different measurements from 4 different sensors (technically more than 4 but..) -
Latitude & Longitude - from CoreLocation. It uses a mix of GPS + cell tower triangulation.
Accelerometer - the current orientation of the device in 3D space.
Gyroscope - orientation of the device on its own axis.
Magnetometer - which tells you which direction a device is point w.r.t south,north,east,west
Of all these I think only Latitude & Longitude are of use to you. Basically what you do is to make the sensitivity (i.e. the update rate from the sensor) a bit more relaxed. With some tweaking around with this you should be able to tell with good accuracy if a person is standing or moving.
It is known that the raw accelerometer data is combination of both linear acceleration and gravity. In order to isolate them w need to apply appropriate filters. I would like to know the real time applications where we would need only "gravity" or only "linear acceleration".
Gravity is used when you are trying to figure out the orientation of the phone. In other words, when you are trying to figure out how the user holds the phone. It is good for tilt games, for example you use the phone to drive a car, etc.
Linear acceleration is used when you are trying to figure out how the phone is shaken. It good for shaking games.
I highly recommend this video. In particular, between 4:15-6:10 and staring from 33:30 you see demos.
I never really understand the applications of the gyroscope on the iPhone/iPad, does it serve the similar function as the accelerometer but like an improvement to the accelerometer? What is the practical use of it?
"An accelerometer is a direct measurement of orientation, while a gyro is a measurement of the time rate of change of orientation." (1) By combing the output of the two sensors, called sensor fusion, one can determine the orientation of the device precisely and fast.
If you only use accelerometer with a low-pass filter, you still get a reasonable estimate for the orientation but it will lag.
Here is an excellent live demo of both (Google Tech Talk), starting at 21:50.
Gyroscope measures orientation, where accelerometer measures movement. Both have useful applications (gyroscope: Which direction am I driving towards? Accelerometer: Did I just shake my device?)
The accelerometer tells you the difference in the force being experienced by the device and the force it would experience if it were in free fall. So if the device is static, the accelerometer tells you which way up is. When it's being shaken around, you get a summation of up plus the direction of the shake. Hence the accelerometer can detect some rotation, but not around the gravity vector and only if the device is otherwise static.
The gyroscope tells you the velocity at which the device is being rotated. So you can integrate values coming from it to keep track of orientation. That works across all axes and irrespective of device movement.
I'd like to transform the yaw, pitch and roll of the iPhone from the body frame to the world frame, i.e. azimuth, pitch and roll. On Android this is easily done with the
SensorManager.remapCoordinateSystem(), SensorManager.getOrientation methods as detailed here: http://blog.mysticlakesoftware.com/2009/07/sensor-accelerometer-magnetics.html
Are similar methods available for the iPhone or can someone point me in the right direction how to do this transformation?
Thanks
The accelerometer is good enough to get gravity direction vector in device coordinate system. That is in case when device calms down.
The next step for full device orientation is to use CLLocationManager and get the true north vector in device coordinate system.
With the normalized true north vector and gravity vector you can easily get all other directions using the dot and cross vectors product.
The accelerometer (UIAccelerometer) will give you a vector from the device's accelerometer chip straight down. If you can assume that the device is being held fairly steady (i.e., that you're not reading acceleration from actual movement), then you can use simple trig (acos(), asin()) to determine the device's orientation.
If you're worried that the device might be moving, you can wait for several accelerometer readings in a row that are nearly the same. You can also filter out any vector with a length that's ± TOLERANCE (as you define it) from 1.0
In more general terms, the device has no way of knowing its orientation, other than by "feeling gravity", which is done via the accelerometer. The challenges you'll have center around the fact that the accelerometer feels all acceleration, of which gravity is only one possible source.
If you're targeting a device with a gyroscope (iPhone 4 at the time of writing), the CoreMotion framework's CMMotionManager can supply you with CMDeviceMotion updates. The framework does a good job of processing the raw sensor data and separating gravity and userAcceleration for you. You're interested in the gravity vector, which can define the pitch and roll with a little trig. To add yaw, (device rotation around the gravity vector) you'll also need to use the CoreLocation framework's CLLocationManager to get compass heading updates.
Has any one developed 6DOF pose estimation using only the iPhone sensors, not video? Drift from the accelerometer and gyroscope are understood.
The gyroscope provides fairly reliable relative orientation rates. I've been able to develop with the gyroscope data.
However, I'm having more problems deriving translation from the accelerometer. Double integration of the acceleration leads to useless position data very quickly (less than half a second).
I have attempted to remove the bias with a calibration step, but the position is still poor. What's worse, is the bias isn't constant. It changes over time, and the noise drowse the signal.
I'm interested if anyone has been able to develop a 6DOF with only the accelerometer and gyroscope that works reliably for 5-10 seconds with little drift in both translation and orientation.
The gyro yaw using DeviceMotion has a drift when you first start updating, try not to take those samples and everyone will be happy.
I made a post about this: Get orientation device in the iPhone for Opengl Es, I having the same issue, I´m just trying to make a filter but it´s not working good, there is a book about these http://www.amazon.com/iOS-Sensor-Programming-Augmented-Location/dp/1449382657, but I didn´t read this book.