This paper addresses control surface segmentation in micro aerial vehicles (MAVs) by leveraging neuro-evolutionary techniques that allow the control of a higher number of control surfaces. Applying classical control methods to MAVs is a difficult process due to the complexity of the control laws with fast and highly non-linear dynamics....
Micro Aerial Vehicles (MAVs) are notoriously
difficult to control as they are light, susceptible to minor
fluctuations in the environment, and obey highly non-linear
dynamics. Indeed, traditional control methods, particularly
those relying on difficult to obtain models of the interaction
between an MAV and its environment have been unable
to...