As you all know when compass come near magnetic field its value got disturbance and it went away from its actual value. I have been working on a project in which i have to get device rotation with 95% accuracy. I have tried number of sensors which can be used to get device angle but all have some sort of external factors which make it un-useful for me to use in my case.
For example when i use TYPE_MAGNETIC_FIELD and i came closer to any magnetic thing or electric wires or even my laptop its value adds up error.
when i use TYPE_ORIENTATION (i know its deprecated) its value adds up a Drift Value after some time which makes it unreliable for me to use.
I have also used some other sensors to combine and make it to behave like compass without magnetic field but all of them either become unreliable with magnetic field or adds up some drift after some time.
I have read some of research papers from difference research institutes but i don't think anyone has ever produce rotation angle with 95% accuracy. I want to know if there is any way even with AI algorithm from which we can achieve this case? The end goal is to get a device angle which is 95%> accurate.
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I am building an Android app (for version 8 currently) that uses the magnetic compass. In the application, I have added a check to confirm that the compass is currently giving accurate results and, if it is not, the user gets prompted to perform a 'figure of 8' calibration sequence.
In order to properly test this, I would like to UNcalibrate the compass, so that I can check that the calibration code is actually working correctly. Is there any way to do this reliably?
Related to compass calibration although that refers to a long superseded version of Android.
If you allow the device to sit motionless for a while (with your app not reading the compass), that may do it.
You also might bring something magnetic close to it to throw the magnetometer off.
My understanding of "calibration" is as follows: the hardware (or low level drivers) know that earth's magnetic field is uniform, hence length of resulting magnetic vector should be constant regardless of device orientation. If there is a second magnetic field which rotates with the device, the sum of the two fields will not be constant; they detect this and mathematically subtract out the second field by analyzing how the sum field is distorted. Waving in a figure 8 provides enough sample data at various orientations to accomplish this.
All of the guides to getting compass orientation in Android I've found have a bug: when you hold the phone in portrait mode and "look" above the horizon, the compass arrow turns 180 degrees from the correct direction.
Google Maps orientation indicator doesn't have this problem.
Another nice thing that Google Maps have is that they somehow estimate compass accuracy. Any idea how they do this?
Error you ask is caused because of Euler angles or called Gimbal Lock.
To solve very high angle difference, you should check if your device is flat or not checking inclination after getting inclination using gravity sensor or getting gravity from accelerometer with lowpass filter. If it's not flat(AR application or inclination>25 || inclination < 155) remap coordinate system from x,y to x,z. That will solve the issue.
SensorManager.getRotationMatrixFromVector(rotationMatrix, event.values);
SensorManager.remapCoordinateSystem(rotationMatrix, SensorManager.AXIS_X, SensorManager.AXIS_Z, remappedRM);
SensorManager.getOrientation(remappedRM, orientation);
This solves the Gimbal Lock, however, 3D compasses(normal compasses does not give correct results due to they are only mapped in x,y and occurs Gimbal Lock) i've seen on Play Store and every code here has a diffence when you keep your device laying flat or screen pointing at you. That difference sometimes gets up to 10 degrees. I haven't able to solve it. Mostly difference is between 1-5 degrees but i sometimes see it rise up to 10 degrees which is not acceptable.
Google measures azimuth from your location. There is a code to find bearing.
currentLocation.getBearing();
Accuracy of lat long(accuracy of your current location) is what determines accuracy of bearing.
List of ways doing a compass with the most accurate to least is in order
Use GPS/Wife(Google's fused location) location and get bearing from location
Use Rotation Vector(requires magnetic field sensor, you should check if it's available), it's a fused sensor(magnetic field+gyroscope+accelerometer and software parts) and using Kalman filter to smooth values but check inclination to remap orientation
Gravity/Accelerometer + Magnetic Field Sensor. This will have a terrible noise attached to it, to smooth it you should use moving average or low-pass filter(this not for isolating gravity, it's for using a threshold frequency to prevent high jumps)
bug when looking above the horizon.
There is some tricky parts when you work with compass.
The compass orientation depends on magnetic fields and phone orientation, so, in order to correct deviation you need to do some matrix operations.
Check this article, it provides a simple example -> https://www.journal.deviantdev.com/android-compass-azimuth-calculating/
Paraphrasing the article: "So if the device is not holding flat (∓45° deviation) you have to use remapCoordinateSystem() in a useful way to get correct results."
accuracy.
First of all, accuracy rely on physical components present in the device. Fragmentation is a common problem here. Samsung magnetometers are different from LG's, and Android System is not going to abstract you from this.
On the other hand, devices could rely on different type of sensors: harward or sensor fusion. So you're going to experiment differences between one device and other.
So this is a mess. But it exists some techniques you could apply in order to get accuracy and uniformed data from sensors (not only for compass, probably GPS too).
Some people discard the first few seconds of sensor data. Some time is needed in order to calibrate the signal, so the first data retrieved use to have some deviation. The time you need to discard depends on manufacturer again, buy I'd try with 5 seconds or so.
Use Interpolators and Extrapolators. Many sensors in android provide you a way to retrieve data each certain milliseconds. But this is the abstraction provided by Android. Harward sensors have its own timing and they update the signal when they they think it is necessary. The rest of the time, when Android ask the sensor for signal data the sensor returns the last value or maybe some kind of operation of the last signal data provided by manufacturer (again).
So, it is interesting to have some abstraction layer (interpolator / extrapolator) which receive the data from Android system each 20, 50, 1000... This layer make some operations in order to have some uniformity, and then communicates the data to your app.
The operation here could be some kind of average between current and last value, accumulated average or maybe another kind of normalization.
OK, i figured it out myself. first you need to calculate the bearing from the compass. then the Maps api-2 camera can be rotated.
public void updateCamera(float bearing) {
CameraPosition currentPlace = new CameraPosition.Builder()
.target(new LatLng(centerLatitude, centerLongitude))
.bearing(bearing).tilt(65.5f).zoom(18f).build();
googleMap.moveCamera(CameraUpdateFactory.newCameraPosition(currentPlace));
}
set SensorListener in your code and call this method in onSensorChanged event. i have added a tilt value so the map will rotate in 3D.
[Reference:] [Android Maps v2 rotate mapView with compass1
if you can know about more details http://www.techotopia.com/index.php/Working_with_the_Google_Maps_Android_API_in_Android_Studio
Compasses will give you what you want, but it's so noisy. It is noisy for 2 reasons, one of reason is, it is picking up, real noise, real signal. So, we live in an environment that's magnetically very noisy. So, this compasses, picking up everything that's magnetic. The other reason is that, it's not integrated, so it doesn't have benefit of dropping the frequency component. So, try to combine your compass with gyroscope data. This video will help you so much for using these sensors.
Some more details, you can combine accelerometers also. So in summary, Gyroscopes provide orientation, Accelerometers provide a correction due to gravity, and compasses provide a correction due to magnetic North.
I am trying to use the phone as a gun aiming with the gyroscope. I calibrate with the phone or tablet in a certain orientation. This will shoot straight. Then depending on the direction the phone is turned (left/right/up/down.), the gun shoots in that direction.
I am using the gyroscope. And all this works. Except after shooting for about 30 secs, the gyroscope slowly starts drifting towards left or right. So when I go back to the orientation I calibrated with, it doesn't shoot straight anymore. Does anyone have any experience writing a Complementary or Kalman Filter to fuse gyro and accelerometer data to give better results in Unity 3D?
I've found this online - http://www.x-io.co.uk/open-source-ahrs-with-x-imu/. It seems to do exactly what I want. But I am using it wrong. I sometime get better and sometimes get worse results with. Anybody have any experience with it ?
First place, Gyro/accelerometer fusion will stabilize your pitch/roll angles, since gravity indicates in which direction ground is. However, you cannot correct "left/right" drift because actual heading is unknown. Getting proper heading stabilization cannot be achieved with gyro/accelerometer alone: it requires additional information.
The example you provide (Madgwick’s MARG/IMU filter) is a filter that can integrate magnetometers ("north" reference), but it has two requirements for getting good results:
The magnetometer has been properly calibrated.
There are no magnetic field disturbances. This is generally not true if you are indoors, or if you are moving close to power lines or metallic structures.
An alternative is using a video signal to get optical flow information, or detecting if the phone is resting in a fixed position to compensate gyro biases from time to time.
I have a question regarding inertial navigation with a mobile device.
I am using an android tablet for development but I think the question is related to
all types (even with better sensors) of hardware.
The most basic question when developing an inertial system is how to determine the
direction of the carrier's movement.
Even if we assume that the magnetometer readings are 100% accurate (which they are obviously not!) There is still the question of the device orientation relative to the user.
Simple example - if the user is walking north, but holds the device with the device's Y axis points north-east, (a link to a picture of the different axis: http://developer.android.com/reference/android/hardware/SensorEvent.html)
Then the magnetometer will point towards north-east.
How can we tell which way the user is actually heading?
(The same will be true if we use both magnetometer and Gyro for determining heading)
A possible solution will be to use the Accelerometer's Y-axis and X-axis readings.
Something in the direction of using arctan(a-Y/a-X)
(for example - if the user holds the device perfectly straight, then the X-Axis will show nothing...)
But since the Accelerometer's readings are not stable, it is not so easy...
Does anyone know of an algorithm that actually works? I am sure this is a well known problem, but I can't seem to find references to solutions...
Thanks in advance!
Ariel
See this answer for an idea: by obtaining the acceleration values in relation to the earth, you can then use the atan2 function to compute the actual direction.
You mention the user holds the tablet, and I assume fairly stable (unlike a case I am working on, where the user moves the phone constantly). Yet, for some reason, the user may change the orientation of the device, and this may influence the readings you obtain.
Thus, in the event of an orientation change, you should call remapCoordinates() accordingly to fix the readings you obtain.
NOTE: You can also use the getOrientation() method accordingly, and the first field represents the heading direction.
The really right answer is to leave the device sitting there for a while, detect the rotation of the earth, and then compute true north from that. Unfortunately, the gyros in a mobile phone aren't accurate enough for that....
I'm using the Android SDK (2.2) with a Droid and I have access to the 3-axis accelerometer and gyrometer.
I apologize in advance if this reveals my ignorance of physics. It has been awhile.
What I don't understand is why the accelerometer is giving different x,y,z values when I tilt the phone. It's standing still, at least, with negligible acceleration and even mostly constant velocity, it's just tilted. I thought that this was the gyrometer's job?
I don't want gravity in the equation...I just want the other forces affecting the phone. Everything had better be 0,0,0 unless I'm moving it faster. I want to know how hard I hit the phone on the table, and the direction and magnitude of the x,y,z forces when I do so. So far, I am confused beyond belief about how to access this with the accelerometer and gyrometer data. I'm trying to take the gyrometer as the direction and the accelerometer as the magnitude. Unfortunately, the data for those aren't really in sync (I have to setup two events to get each pair of data, and they may come at different times), but it might be good enough to just buffer them and assume some sort of synchronization.
Desperate,
Andrew
I'm afraid that's just how accelerometers work, here on earth there will always be 9.8 Gs pointing at the ground.
If you can assume that you have a working compass, just take a vector of length STANDARD_GRAVITY, rotate with the current orientation taken from the magnetometer and subtract this from your accelerometer's vector.
Keep in mind that you should also dampen the values you get back from the accelerometer, use a running average of the last few values.