This work addresses the robotization of a small-scale commercial helicopter. The solution involves three subtasks: (i) design and implementation of algorithms for localization, (ii) development of the helicopter model, and (iii) design and implementation of control laws. For localization, the combination of a stereo vision system and inertial sensors information via Kalman Filtering is proposed. The estimated states, which are linear and angular positions and velocities, along with the pilot commands are used to estimate, through system identification methods, the parameters of a gray box model. This model is further used to design the system controllers, which are traditional PID cascade control. Experimental results show the stabilization of all degrees of freedom of the mini-helicopter.
Aerial Robotics; autonomous helicopters; unmanned aerial vehicles
