Please suggest some beginning point in this process of finding distance displaced by an iPhone. The requirement of accuracy in current system is in cm, and displacement can be in 3D.
What I have already done is
1. Tried using sound to calculated distance between between 2 iPhones, but I need distance calculation with one iPhone only, i.e need displacement.
2. Tried CMMotionManager and its accelerometer data, but values received is helpless.
I think I need a good filter to get useful data out of that junk. I already used Kalman Filter and gone through link
iphone accelerometer speed and distance,
How to calculate distance using accelerometer using iphone sdk?,
How do I measure the distance traveled by an iPhone using the accelerometer?,
Basic calculus behind this problem is in the expression
Tried DCT-II algorithm and Multidimensional DCTs to filter data.
I dont know what did I miss, or where should I go from here, as it is hard to believe that no one has used accelerometer for such an accuracy, because there are so many practical examples of it being used for greater accuracy.
Please provide me some pointer that suggest some way out of current situation.
You can't achieve cm accuracy. The reason is, surprisingly, the orientation error.
The above link contains some tips what you can do if you need displacement.
An even better alternative is to use orientation in you application, if you can.
Related
I would like to use accelerometer to detect distance traveled for indoor distance detection (sorry if this is a silly question I am very new to flutter)
I found code that will let me present accelerometer data but not save it.
https://inducesmile.com/google-flutter/how-to-use-device-sensors-in-flutter-gyroscope-proximity/
this of course is not my own code its just I found this and I would like to use the data recorded and calculated the distance traveled.
So this issue is not very solvable in Dart/Flutter.
The better way to do this app is with Java.
With a Java app simply find an accelerometer app and through that you can calculate speed and distance. The difference is that the in Java the stream that is used in Dart is a repeating function. In that function calculations can be conducted.
I need to create an app that Calculates the moving car velocity/speed, with x/y/z speed.
My idea is using device's accelerometer.
I am using Sensor.TYPE_ACCELEROMETER and getting ax,ay,az (acceleration in x,y,z direction). how to get sped of device. Lots of physics formulas suggested by people to get speed but any one of then not giving correct speed compared to GPS. Please tell me code or good link which solve my problem.
That would be very difficult. To calculate the speed of the device, you need to calculate the integral of the acceleration. But to do so, you need to very accurately know for very dense points in time both the device's rotation and its acceleration. Assuming you do have those things, you simply need to take the device's initial speed, and for each point in time add to it (rotation matrix * acceleration vector * time to next measurement). That's probably the most accurate thing you can that is simple enough.
What's the easiest way to plot location track based on series of reading of accelerometer/gyro/compass sensors taken over time? Let's say I have following data taken every second:
ElapsedTime(s) xMag(uT) yMag(uT) zMag(uT) xAccel(g) yAccel(g) zAccel(g) xRate(rad/sec) yRate(rad/sec) zRate(rad/sec) roll(rad) pitch(rad) yaw(rad)
...
Is there an easy way to draw a location plot for any given time? I'm using iPhone 4 with xSensor app to capture data, but can't just use GPS. I would appreciate any hints. Both standalone applications and Java libraries would be good.
Double integration of the acceleration vector (after gyro & compass direction correction) will give you a location from some initial or arbitrary offset. The problem is that any small offset or errors in the acceleration data, which there will be, will result in a rapidly diverging position.
What might be more possible is to get frequent and precise GPS position data, and use the acceleration data to estimate the route in between two very nearby GPS fixes.
Using iPhone's SDK GPS API, how accurate can I get? Is it within a few meters or kilometers? I'm interested in the accuracy when it is indoor. My software will only be used in door.
The best possible accuracy seems to be 9 meters. Common values (outdoor, good coverage) is 17 m, 23 m and 49 meters. With trees covering the sky you'll probably stay under a hundred meters, but hardly accurate enough for GIS or anything like that.
The API has a property or method that returns the current accuracy of the location measurement. If your goal is only to use the location if accuracy is within some limit then you should make sure that you check the returned accuracy, since the location may be only accurate to within a few thousand meters initially as its just using your location from the cell towers, and it will typically get better and better accuracy as the GPS powers up and starts getting a fix.
Most standard GPS chips (and the iphone is that) can get around 10 meters accuracy.
Best results are outside on a clear sky obviously.
The difference between GPS chips is usually how quickly they can reception and how well they can hold it. Accuracy is pretty constant except for those using WAAS sattelite (which the iphone GPS doesn't do)
Based on my own experience it's within meters.
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.