"This was a few years ago so sensors may have improved"
Apparently they're much better than previously. When I first tried this around 3 years ago, I had the same problems you did. The errors get cubed by the double integration. Software Kalman filters and other tricks didn't really help.
A lot of the newer sensor chips now do "sensor fusion"[1] on the chip itself, which means that the raw data is much more useful, and requires almost no post-processing.
I assume that this, in combination with higher sampling rates, means that the errors are small enough for the output to be useful over "human interaction" scale.
Apparently they're much better than previously. When I first tried this around 3 years ago, I had the same problems you did. The errors get cubed by the double integration. Software Kalman filters and other tricks didn't really help.
A lot of the newer sensor chips now do "sensor fusion"[1] on the chip itself, which means that the raw data is much more useful, and requires almost no post-processing.
I assume that this, in combination with higher sampling rates, means that the errors are small enough for the output to be useful over "human interaction" scale.
[1]: http://en.wikipedia.org/wiki/Sensor_fusion
Examples:
http://www.kionix.com/sensor-fusion
http://www.invensense.com/mems/technology.html
http://www.st.com/web/en/catalog/sense_power/FM89?sc=mems