I've been experimenting with the compass and gyroscope on iPhone 4 and would like some help with an issue I'm having. I want to compensate for the slowness of the compass by using data from the gyroscope.
Using CMMotionManager and its CMDeviceMotion object (motionManager.deviceMotion), I get the CMAttitude object. Correct me if I'm wrong (please), but here is what I've deduced from the CMAttitude object's yaw property (I don't need pitch nor roll for my purposes):
yaw ranges from 0 to PI when the phone is pointing downwards (as indicated by deviceMotion.gravity.z) and swinging counterclockwise and 0 to -PI when swung clockwise
when the device is pointing upwards, yaw ranges from -PI to 0 and PI to 0, respectively
and from the compass data (I'm using locationManager.heading.magneticHeading), I see that the compass gives values from 0 to 360, with the value increasing when swinging clockwise
All right, so using all of this information together, I'm able to get a value I call horizontal that, regardless of whether the device is pointing up or down, will give values from 0 to 360 and increase when the device is swung clockwise (though I am still having trouble when deviceManager.gravity.z is around 0 -- the yaw value freaks out at this gravity.z value).
It seems to me that I could "synchronize" the horizontal and magneticHeading values, using a calculated horizontal value that maps to magneticHeading, and "synchronize" the horizontal value to magneticHeading when I feel the compass has "caught up."
So my questions:
Am I on the right track with this?
Am I using the gyro data from CMDeviceMotion properly and the assumptions I listed above correct?
Why might yaw freak out when gravity.z is around 0?
Thank you very much. I look forward to hearing your answers!
Just trying to answer... correct me if i'm wrong..
1.Yes you are on the right track
2.gravity in CM is already "isolated" from user gravity (gravity value caused by user acceleration) thats why there is two gravity, the "gravity" and "userAcceleration" its on apple CM documentation
// Note : not entirely isolated //
3.
if you have a gravity 0 it mean that the coresponding axis is perpendicular with gravity.
gravity.z is the iPhone screen thats why it -9.82m/s2 if you put on the desk with screen upright, actualy it hard to get 0 or maximum value of the gravity due to the sensor noise (it's normal, all sensor has a noise expecially cheap sensor).
what i do on my apps is I will switch my reference axis to other axis (in your case may be x or y) for certain limits, how the strategy is depend on the purpose or which side is your reference.
the other thing is, gyro is fast but its not stable, you need to re-calibrate the value for several interval. In my case every 5 second. I've experiment with gyro for calculating angle between two plane, i try with exacly 90 degree ruler and it will give an error about 0.5 degree every second try and keep increasing, but thats is mine, maybe others have a better method for avoid the error.
below is my steps "
Init
Read gravity XYZ -> Xg Yg Zg
Check if Xg < 0.25 If TRUE try Yg then Zg // Note 1 = 1g = 9.82 m/s^2
Read the compass and gyro
Configure and calibrate the gyro using the compass and calulate based on which axis i use in point 3.
If 5 second is pass then recalibrate, read the compass
If the the difference with gyro reading is > 5 degree skip recalibartion the gyro.
If the the difference with gyro reading is < 5 degree calibrate the gyro using compass value
Note: for number 7 : is to check if the phone affected with magnetic field or near huge steel such or high voltage electrical line or in noisy and heavy equipment in factory plant.
Thats all... Hope this could help you...
And sorry for my english..
Here is an example of an iPhone app where the compass get compensated with the gyroscope. Code and project can be seen here:
http://www.sundh.com/blog/2011/09/stabalize-compass-of-iphone-with-gyroscope/
The direction of the yaw axis vector is undefined when in zero gravity (or free fall, or close enough).
In order to do synchronization while in motion, you need to create a filter for your "horizontal" value that has the same lag/delay response characteristics as the magnetic compass. Either that, or wait until motion stops long enough for both values to settle before recalculating the offset.
Answer to question 1 is Yes, question 2 you are on the right track but you could use a variable name that is not 'horizontal', question 3 is answered by hotpaw2 and also a yaw in a chopper or helicopter at near zero altitude would alert the pilot with an alarm. There is a time lag because part of the software is local while there are other factors which can slow it down including access to a sensor for detecting magnetic waves, the device position and direction, preparing the graphic output for the compass display, computing and outputting data from the gyro and sensors through a relatively slow interface, using a general purpose handheld device not custom designed for the type of task being asked of it.
Related
I am working in a monocular 3D Mapping project, and I need every time both position and rotation (angle).
To filter Gyroscope Data, I decided to use the "compass" and set 0 value to the angle if it's north.
But to get the position, I will need to double integrate the accelerometer value with a small sampling step (1ms) and 7 values mean filter.
I think this will make position more accurate. But does someone have an idea about the error range ? for example, in 10 meters, How much the error will be.
And does anyone have a better idea?
The sensors are from STM32F3 Discovery Board
Thanks
The STM32F3 has two sensors you'd be using:
LSM303DLHC accelerometer and magnetometer
L3GD20 3-axis digital gyroscope.
The sensor accuracy should appear somewhere in the datasheet. Since you'll be using several sensors, you'll have to calculate the total error over the time your measuring. Note, the error won't be a single number like 10 meters because it will accumulate over time. If you had a GPS or some other way of determining your position you'd be able to limit your accumulated error.
What you're doing sounds like an Inertial Measurement Unit. If you haven't already, I'd recommend reading up on that and also Dead Reckoning.
I have a record session for my application. When user started a record session I start collecting data from device's CMMotionManager object and store them on CoreData to process and present later. The data I'm collecting includes gps data, accelerometer data and gyro data. The frequency of data is 10Hz.
Currently I'm struggling to calculate the lean angle of device with motion data. It is possible to calculate which side of device is land by using gravity data but I want to calculate right or left angle between user and ground regardless of travel direction.
This problem requires some linear algebra knowledge to solve. For example for calculation on some point I must calculate the equation of a 3D line on a calculated plane. I am working on this one for a day and it's getting more complex. I'm not good at math at all. Some math examples related to the problem is appreciated too.
It depends on what you want to do with the collected data and what ways the user will go with that recording iPhone in her/his pocket. The reason is that Euler angles are no safe and especially no unique way to express a rotation. Consider a situation where the user puts the phone upright into his jeans' back pocket and then turns left around 90°. Because CMAttitude is related to a device lying flat on the table, you have two subsequent rotations for (pitch=x, roll=y, yaw=z) according to this picture:
pitch +90° for getting the phone upright => (90, 0, 0)
roll +90° for turning left => (90, 90, 0)
But you can get the same position by:
yaw +90° for turning the phone left (0, 0, 90)
pitch -90° for making the phone upright (-90, 0, 90)
You see two different representations (90, 90, 0) and (-90, 0, 90) for getting to the same rotation and there are more of them. So you press Start button, do some fancy rotations to put the phone into the pocket and you are in trouble because you can't rely on Euler Angles when doing more complex motions (s. gimbal lock for more headaches on this ;-)
Now the good news: you are right linear algebra will do the job. What you can do is force your users to put the phone in always the same position e.g. fixed upright in the right back pocket and calculate the angle(s) relative to the ground by building the dot product of gravity vector from CMDeviceMotion g = (x, y, z) and the postion vector p which is the -Y axis (0, -1, 0) in upright position:
g • x = x*0 + y*(-1) + z*0 = -y = ||g||*1*cos (alpha)
=> alpha = arccos (-y/9.81) as total angle. Note that gravitational acceleration g is constantly about 9.81
To get the left-right lean angle and forward-back angle we use the tangens:
alphaLR = arctan (x/y)
alphaFB = arctan (z/y)
[UPDATE:]
If you can't rely on having the phone at a predefined postion like (0, -1, 0) in the equations above, you can only calculate the total angle but not the specific ones alphaLR and alphaFB. The reason is that you only have one axis of the new coordinate system where you need two of them. The new Y axis y' will then be defined as average gravity vector but you don't know your new X axis because every vector perpedicular to y' will be valid.
So you have to provide further information like let the users walk a longer distance into one direction without deviating and use GPS and magnetometer data to get the 2nd axis z'. Sounds pretty error prone in practise.
The total angle is no problem as we can replace (0, -1, 0) with the average gravity vector (pX, pY, pZ):
g•p = xpX + ypY + zpZ = ||g||||p||*cos(alpha) = ||g||^2*cos(alpha)
alpha = arccos ((xpX + ypY + z*pZ) / 9.81^2)
Two more things to bear in mind:
Different persons wear different trowsers with different pockets. So the gravity vector will be different even for the same person wearing other clothes and you might need some kind of normalisation
CMMotionManager does not work in the background i.e. the users must not push the standby button
If I understand your question, I think you are interested in getting the attitude of your device. You can do this using the attitude property of the CMDeviceMotion object that you get from the deviceMotion property of the CMMotionManager object.
There are two different angles that you might be interested in the CMAttitude class: roll and pitch. If you imagine your device as an airplane with the propeller at the top (where the headphone jack is), pitch is the angle the plane/device would make with the ground if the plane were in a climb or dive. Meanwhile, roll is the angle that the "wings" would make with the ground if the plane were to be banking or in mid barrel roll.
(BTW, there is a third angle called yaw that I think is not relevant for your question.)
The angles will be given in radians, but it's easy enough to convert them to degrees if that's what you want (by multiplying by 180 and then dividing by pi).
Assuming I understand what you want, the good news is that you may not need to understand any linear algebra to capture and use these angles. (If I'm missing something, please clarify and I'd be happy to help further.)
UPDATE (based on comments):
The attitude values in the CMAttitude object are relative to the ground (i.e., the default reference frame has the Z-axis as vertical, that is pointing in the opposite direction as gravity), so you don't have to worry about cancelling out gravity. So, for example, if you lie your device on a flat table top, and then roll it up onto its side, the roll property of the CMAttitude object will change from 0 to plus or minus 90 degrees (+- .5pi radians), depending on which side you roll it onto. Meanwhile, if you start it lying flat and then gradually stand it up on its end, the same will happen to the pitch property.
While you can use the pitch, roll, and yaw angles directly if you want, you can also set a different reference frame (e.g., a different direction for "up"). To do this, just capture the attitude in that orientation during a "calibration" step and then use CMAttitude's multiplyByInverseOfAttitude: method to transform your attitude data to the new reference frame.
Even though your question only mentioned capturing the "lean angle" (with the ground), you will probably want to capture at least 2 of the 3 attitude angles (e.g., pitch and either roll or yaw, depending on what they are doing), potentially all three, if the device is going to be in a person's pocket. (The device could rotate in the pocket in various ways if the pocket is baggy, for example.) For the most part, though, I think you will probably be able to rely on just two of the three (unless you see radical shifts in yaw throughout the course of a recording session). So for example, in my jeans pocket, the phone is usually nearly vertical. Thus, for me, pitch would vary a whole bunch as I, say, walk, sit or run. Roll would vary whenever I change the direction I'm facing. Meanwhile, yaw would not vary much at all (unless I do kart-wheels, which I can't!). So yaw can probably be ignored for me.
To summarize the main point: to use these attitude angles, you don't need to do any linear algebra, nor worry about gravity (although you may want to use this for other purposes, of course).
UPDATE 2 (based on Kay's new post):
Kay just replied and showed how to use gravity and linear algebra to make sure your angles are unique. (And, btw, I think you should give the bounty to that post, fwiw.)
Depending on what you want to do, you may want to use this math. You would want to use the linear algebra and gravity if you need a standardized way of "talking about" and/or comparing attitudes over the course of your recording session. If you just want to visualize them, you can probably still get away with not using the increased complexity. (For example, visualizing (pitch=90, roll=0, yaw=0) should be the same as visualizing (pitch=0, roll=90, yaw=90).) In my approach above, while you could have multiple ways of referring to the "same" attitude, none of them is actually wrong, per se. They will still give you the angles relative to the ground.
But the fact that the gyroscope can switch from one valid description of an attitude to another means that what I wrote above about getting away with only 2 of the 3 components needs to be corrected: because of this, you will need to capture all three components, no matter what. Sorry.
The apple documentation for UIAcceleration class says,
"When a device is laying still with its back on a horizontal surface, each acceleration event has approximately the following values:
x: 0
y: 0
z: -1"
Now, I am confused! How can the acceleration be non-zero, when you clearly say the "device is laying still"?
UPDATE
Judging by the responses, I think this should be called something like 'forceometer' or 'gravitometer' and not accelerometer!
You get a -1 on the Z axis because gravity is acting on the device, applying a constant acceleration of 1G. I assume you want user acceleration, which you can get from the DeviceMotion object using a device motion handler as opposed to an acceleration handler. The userAcceleration property filters out the effects of gravity on the device and only gives you how much the user is accelerating it.
I found the answer [in the CoreMotion Reference guide, thanks to bensnider:
The accelerometer measures the sum of two acceleration vectors: gravity and user acceleration. User acceleration is the acceleration that the user imparts to the device.
You'll find the best answers in datasheet of the accelerometer used (LIS302DL).
It measures the gravity. The unit is chosen so that the gravity, 9.81 m/s^2, equals 1 unit. The sign tells how the phone axis is directed. In other words, what the phone considers downwards.
The phone measures 0 as acceleration in free fall. I don't know how much you want to throw your phone up and down to test it :)
When you're sitting, gravity is pulling you down to your chair. If it weren't for the chair or ground for that matter, you'd be falling down with acceleration of about 9.8m/s^2. In order for the chair to prevent you from falling down, it has to act with a force in the opposite direction with at least the same value.
The accelometer shows the value of the pulling force and it's a three-dimensional vector. In this case it's directed straight down. And the value given is expressed in G, units of gravity acceleration multiplied by that value.
Answerers keep missing the right wording that should set it straight for you... The device is "laying still" only relatively to you. It is actually not laying still at all. The http://en.wikipedia.org/wiki/Centripetal_force of gravity gives it (and you) centripetal acceleration. It is real, it is what keeps you from flying off Earth on a tangent, and it is what the accelerometer dutifully shows. (Earth is nothing special - we rotate about the Sun also etc etc, whose centripetal accelerations are way smaller, but they would be all shown by an accelerometer sensitive enough.)
I don't yet have sufficient reputation to reply directly to the comment by #gigahari above, but as an addendum, folks should be aware that some apps (such as the physics apps phyphox and PhysicsToolbox Sensor Suite) do not report (a+g) -- both phyphox's "with g" option and PhysicsToolbox report the vector sum (a-g), which is sometimes referred to as the "Operational Definition of Weight." A brief discussion of this version of the operational definition of weight is on WikiPedia, at https://en.wikipedia.org/wiki/Weight#Operational_definition
I am relatively new to iPhone development and I am playing with the gyroscope, using Core Motion. After a few tests, this is my question.
What information is exactly the gyroscope measuring? absolute angles? I mean, suppose I hold my phone in portrait, at exactly 90 degrees and start sampling. These may be not the correct values, but suppose that at this position, the gyroscope gives me 0, 0 and 0 degrees for yaw, pitch and roll.
Now I throw my iphone in the air and as it goes up it rolls at random a high number of full turns in all axis and returns to my hand at the same position as before. Will the gyroscope read 0,0,0 (meaning that it has the same position as before = absolute angle) or not?
If not, there's a way to measure absolute degrees in all axis? As absolute degrees I mean assuming 0,0,0 as the position it was when the sampling started.
thanks
The gyroscope measures many things for you, and yes, one of these is "absolute angles". Take a look at the docs on CMDeviceMotion. It can give you a rotation rate, which is how fast the device is spinning, and it can give you a CMAttitude. The CMAttitude is what you're calling "absolute angles". It is technically defined as:
the orientation of a body relative to
a given frame of reference
The really nice thing is that normal gyroscopes, as noted in the other answer, are prone to drift. The Core Motion framework does a lot of processing behind the scened for you in an effort to compensate for the drift before the measurements are reported. Practically, I've found that the framework does a remarkable (though not perfect) job at this task. Unless you need long term precision to a magnetic pole or something, the attitude reported by the framework can be considered as a perfect relative attitude measurement, for all intents and purposes.
The iPhone uses accelerometers for its internal angle measurements, which means they are relative to the Earth's gravity. That's about as absolute as you're going to get, unless you need this program to work in space, too.
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.
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.
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.
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.