What I want to achieve is to build a neural network with Keras which will have to stabilize a quadcopter I've built. The network would have three inputs: pitch, roll, yaw, acceleration x, accel y and accel z and four outputs: pwm length for motor 1, 2, 3 and 4. The problem is that the length of the pwm wave needs to fit the range from 1000 (no throttle) to 2000 (max throttle). I know I can map the output to this range, but will this work? And another problem is if it's even possible to train such a network, because I have no model data, they would be submitted real-time during training, when the mpu6050 updates the gyro and accel data, which will rely on the network's output - the speed of each motor?

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    $\begingroup$ Will this work? Only one way to know – try it out. $\endgroup$ – Yuval Filmus Jun 8 '17 at 20:27
  • $\begingroup$ That's right, but the problem is testing - is there any proper software with integration with python to train a generic and general model so that the nn doesn't pull the throttle to full at first, but only calibrates itself to the model ready from simulations? $\endgroup$ – Artus 90 Jun 8 '17 at 20:29
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    $\begingroup$ Software recommendation is off-topic here. $\endgroup$ – Yuval Filmus Jun 8 '17 at 20:31

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