11/12/2022 0 Comments Gyroscope android![]() ![]() Since it had to adapt audio output to the orientation of the users head, it required to respond quickly and be accurate at the same time. ![]() In my work I was developing a head tracking component for a prototype system. While working on my master thesis, I've made some experiences with sensors in Android devices and I thought I'd share them with other Android developers stumbling over my blog. The low-pass filtering of the noisy accelerometer/magnetometer signal ( accMagOrientation in the above figure) are orientation angles averaged over time within a constant time window.Android Sensor Fusion Tutorial download code (.zip) read this on CodeProject Their values can be shown as signals in a graph with the time as the x-axis, similar to an audio signal. So what exactly does high-pass and low-pass filtering of the sensor data mean? The sensors provide their data at (more or less) regular time intervals. The overall sensor fusion and filtering looks like this: This is equivalent to low-pass filtering of the accelerometer and magnetic field sensor signals and high-pass filtering of the gyroscope signals. To avoid both, gyro drift and noisy orientation, the gyroscope output is applied only for orientation changes in short time intervals, while the magnetometer/acceletometer data is used as support information over long periods of time. These small errors add up over time resulting in a constant slow rotation of the calculated orientation, the gyro drift. During this process small errors are introduced in each iteration. The sum of all rotation increments yields the absolut orientation of the device. This is done by multiplying the angular speeds with the time interval between the last and the current sensor output. ![]() To get the actual orientation those speed values need to be integrated over time. The gyro provides the angular rotation speeds for all three axes. The gyroscope in the device is far more accurate and has a very short response time. However both sensor outputs are inacurate, especially the output from the magnetic field sensor which includes a lot of noise. The Information from both sensors suffice to calculate the device’s orientation. In simple terms, the acceletometer provides the gravitiy vector (the vector pointing towards the centre of the earth) and the magnetometer works as a compass. These two angles are based on the accelerometer and magenotmeter output. The common way to get the attitude of an Android device is to use the SensorManager.getOrientation() method to get the three orientation angles. Everybody who thinks the theory is boring and wants to start programing right away can skip directly to the second part. The second part describes the implementation in the Java programming laguage. The first part covers the theoretical background of a complementary filter for sensor signals as described by Shane Colton from MIT here. This tutorial is based on the Android API version 10 (platform 2.3.3). The following tutorial describes in detail how it’s done. To acheive this I implemented a complementary filter to get rid of the gyro drift and the signal noise of the accelerometer and magnetometer. I used my Samsung Galaxy S2 and decided to use its gyroscope in conjunction with the accelerometer and the magnetic field sensor in order to measure the user’s head rotations both, quickly and accurately. Since it had to adapt audio output to the orientation of the users head, it required to respond quickly being accurate at the same time. While working on my master thesis, I’ve made some experiences with sensors in Android devices and I thought I’d share them with other Android developers. Jose Collas created a more user komfortable framework from the original code and put it into a github repository. Since then the code has been put into use by several developers. ![]() However, the approach could still be an interesting topic. The original article has been posted 16th March 2012, so it uses a dated Android API. The request for this article were so high, that I decided to save it here on Code Project. This article is a repost of an original from my former blog on which has been discontinued. ![]()
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