Relative movement of two MetaMotion modules
I have some technical questions related to the "Meta Motion R – 10 Axis IMU + Sensor Fusion":
1) I would like to record the differential 3D position of two MetaMotion, i.e. how the two positions of the MetaMotion move relatively to each other. The relative movement would have a range of about 0-30mm in one case and 0-200mm in another case with a frequency of movement of about 5-10Hz.
Would the sensor signals be accurate enough to get reasonable data for such application?
2) in order to achieve no. 1) I would need to synchronize the logged samples from two MetaMotion very accurately. I read about synchronization of sensors of a single MetaMotion here, but I need to synchronize sensor data from tow different MetaMotion. So my questions are:
What are the mechanisms to synchronize the time stamps of the two MetaMotion?What would be the resolution of the timestamp and maximum error of the synchronization?What would be the jitter of the sample rate and the latency of the sampled data?
3) I need high data rate, up to 800 samples per second in order not to miss changes in the relative position. Therefore I would like to ingelligently filter data directly on the MetaMotion in order to limit logging to about 50 entries per second.
Is there a way to achieve that with the current iOS / C++ APIs?If not for logging mode, would filters effectively reduce traffic on the bluetooth cannel in streaming mode or do they just filter received data?
4) I would like to log sensor fusion samples as well as all the 9 axis separately.
Would it be possible to log one record of all sensor data "atomically", i.e. are all the values of one sample period saved as one record in into the flash so that these values are synchronized?What is the maximum sample rate of sensor fusion data to the flash log?
What is the maximum amount of entries that can be logged to the the flash of the device?
Many thanks for you info.
This discussion has been closed.
Comments
The logger does not synchronize log entries from multiple data sources. Each sensor has its own records though again, these sensors have very accurate timing.