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Sep 28, 2007, 03:14 AM
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Tachometer test flight


So the latest network is 615 nodes trained in 25,000,000 iterations offline. It uses 25 previous tilt -> velocity readings to predict the next velocity. Optimized the prediction loop to the point that the Gumstix could run it 15 times a second, but we only do 1 prediction per second. It seems to give better prediction than the best inflight training possible on this chip.

The answer is yes. She can compute a neural network much faster in fixed point and probably equal the accuracy of floating point, but she can't train a neural network in fixed point, so fixed point is dead.

Squeezed in a flight with RPM being recorded. Ideally this flight would be a static hover for 20 min, but lacking the discipline, crashed and destroyed the IMU. No neural network training on RPM this week.

This one was a stall in 20mph wind. Stalls with this copter are sudden losses of head speed due to aerodynamic load. Been losing head speed a lot with these 3.3Ah 12C batteries.

Magnetometer repair: done
Tachometer test: 1 flight down, 100 more to go
Algebraic navigation: couldn't solve the 180' heading problem. Leaving behind inflight training so this won't be an issue for a while.
Last edited by Jack Crossfire; Sep 28, 2007 at 01:11 PM.
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