gyroscope

I listened to this talk: http://www.youtube.com/watch?v=C7JQ7Rpwn2k which is Invensense Inc prototyping their "Sensor fusion" system, which is where they combine gyro, accelerometer, compass measurements in Android, to get better results. Is this currently implemented in any version of Android? The reason I ask is, part of sensor fusion is the "Gravity" sensor and the "Linear Acceleration" sensor, which ARE implemented in Android ever since API Level 9... makes me think that either 1) sensor fusion is implemented 2) sensor fusion is not implemented, but these are just added into Android API in

Using my Android device how can I detect if the user is walking, cycling or driving? I have checked the Google Fit app. It differentiates between running, cycling and driving. I am puzzled about what algorithms I should use to differentiate between these activities. I know I would have to use the accelerometer sensor. But still I can't differentiate these activities. You can use the GooglePlayServices for this. It Provides special apis for ActivityRecognition, which returns the User activity with confidence level for each. https://developer.android.com/reference/com/google/android/gms/location

Recently I have made some research to use both the accelerometer + Gyroscope to use those senser to track a smartphone without the help of the GPS (see this post) Indoor Positioning System based on Gyroscope and Accelerometer For that purpose I will need my orientation (angle (pitch, roll etc..)) so here what i have done so far: public void onSensorChanged(SensorEvent arg0) { if (arg0.sensor.getType() == Sensor.TYPE_ACCELEROMETER) { accel[0] = arg0.values[0]; accel[1] = arg0.values[1]; accel[2] = arg0.values[2]; pitch = Math.toDegrees(Math.atan2(accel[1], Math.sqrt(Math.pow(accel[2], 2) + Math

Lots of posts talk about the gyro drift problem. Some guys say that the gyro reading has drift, however others say the integration has drift. The raw gyro reading has drift [link] . The integration has drift [link] (Answer1). So, I conduct one experiment. The next two figures are what I got. The following figure shows that gyro reading doesn't drift at all, but has the offset. Because of the offset, the integration is horrible. So it seems that the integration is the drift, is it? The next figure shows that when the offset is reduced the integration doesn't drift at all. In addition, I

Possible Duplicate: Combine Gyroscope and Accelerometer Data I have read a number of papers on Kalman filters , but there seem to be few good publically accessible worked examples of getting from mathematical paper to actual working code. I have a system containing a three-axis accelerometer and a single gyro measuring rotation around one of the accelerometer axes. The system is designed to be held by a human, and much of the time the gyro will be measuring rotation about the gravity vector or close to it. (People working in the same industry will likely recognise what I am talking about from

I'm trying to implement Madgwick sensor fusion algorithm from here on LSM9DS0 sensor (accelerometer, gyroscope and magnetometer) on STM Cortex M3 microcontroller. Raw data from all sensors seems to be fine. My problem is: when I hold sensor with it's z-axis horizontal or downwards (i.e. roll or pitch angle is more than 90 degrees) - quaternion from filter becomes really unstable and randomly flips 180 degrees. More correctly, q0 and q3 are constantly changing signs, resulting in 180 degree flip of rotation. I tried using constant values instead of real sensor output and still got this behavior

I wish to get the acceleration vector of an Android phone. The problem is, the accelerometer coordinates are relative to the phone's rotation. What I want is the "absolute" acceleration, i.e., it should return the same values whichever way the phone is facing. (I want to detect if a user that is skiing is sliding down a slope without using GPS. I also need to be able to differentiate sliding and going up the chairlift.) I can probably get those values by combining the accelerometer with the gyroscope, but I have no idea how I could offset the accelerometer's values with the gyroscope's. Is

I want to implement an indoor localisation system using the sensors of a mobile device (accelerometer, compass, gyro) . This problem was already discussed here on several places such as - here and here The first step is to decide which platform is the best one to implement such a system. The main possibilities are Samsung's Galaxy/ Galaxy tab, or the iphone/ ipad. The most important criteria is the accuracy of the sensors data. However, This comparison is very complicated, as the accuracy is dependent not only on the device itself but also on the software layers above it. Is there any research