In this section, the techniques involved in the process of building the drone are shown.


The IMU that it is being used has to be calibrated in order to get more accurate values, above all from the accelerometer and from the gyroscope. For this purpose three platforms were built and they are shown in the next pictures:


Platform to calibrate the X and Y axis


Platform to calibrate the Z axis






Platform to calibrate all axis of the IMU itself












After all this effort of calibration, it was discovered that there are other IMU devices, which are better and are not more expensive. They do not need to be calibrated and moreover they come with a built-in processor that makes the process of obtaining data easier.

Controller code

The controller of the drone, which is executed in the main board, has to collect data from the sensors and act through the actuators to modify the behaviour of the motors depending on its attitude. The question here is, how to do this? Well, probably there are many ways to do it, but here is another question, what is the best? and another question is, how much time does it take to implement it?

The next subsections show the approaches taken.

Mathematical modelling

This approach is managed by mathematics. So, the algorithm is based on physics around the drone and how it affects it. There are several problems with this approach:

  1. The conditions of the drone have not to be always the same. So, if the behaviour is represented with an ideal model of the environment of the drone, perhaps it does not match as precise as it is expected.
  2. The algorithm is complex to obtain due to the complicated mathematical theories involved.

So, although this was the first approach chosen, it is not the way to build the controller.

PID controlling

This approach is managed by the control theory. The algorithm is robust and it does not need to have knowledge about the physics of the environment of the drone. This algorithm is extremely used, so probably it is the best choice to implement the controller.

Here is some information in order to understand how the PID works:

The inconvenient is that the algorithm has to be tuned in order to obtain the accuracy needed.


Links of interest

Article about the use of the kalman filter specifically for UAVs:



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