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Leoluca Rigogliuso


Rel. Marcello Chiaberge. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2022

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Research on autonomous landing methods of UAVs on a moving platform has experienced rapid growth in recent years and found applications in civil and military sectors. The extreme precision of drone landing is required to overcome problems related to the low battery autonomy of drones, through landing in mobile charging stations, but at the same time also finding applications in the most varied sectors ranging from parcel delivery to rescue operations. This work implements an autonomous algorithm that allows for the landing onto a vehicle that is moving at high speed, through the use of different sensors, chosen depending on the relative drone-rover position. The result is a robust three state machine that makes use of GPS measurements when the drone-rover distance is large, UWB when the rover is nearby and the fusion of information from the camera and the UWB when the drone is landing. The relative position, computed from the UWB sensors with a Least Square algorithm, must be rotated from the rover's mobile system to the NED reference frame. Therefore, a correct estimate of the orientation of the rover and a consistency between the UAV and UGV compasses is of vital importance for an autonomous landing at high speed. This limit is overcome by mounting a camera on the drone that computes the orientation of the apriltag with extreme precision and this information replaces the noisy one of the rover compass. Kalman filter manages the information coming from the various sensors and generates an estimate of the relative position and relative speed. These are then passed to a PID speed controller that allows accurate and fast tracking and landing on the moving target. Through a purely proportional control over long distances of the rover and a proportional-integrative-derivative control when UAV and UGV are close together, the drone speed value is computed and this is passed to the autopilot which in turn generates the correct thrust of the motors corresponding to that speed. Since the rover landing occurs with a vertical descent after the engines are turned off, a predictive control must be implemented so that the drone predicts the progression of the rover in the next timesteps. The adoption of a predictive control system, the introduction of new sensors and the correction of the misalignment between the compasses of the drone and rover made it possible to reach landing speeds above 30 km/h.

Relators: Marcello Chiaberge
Academic year: 2022/23
Publication type: Electronic
Number of Pages: 83
Corso di laurea: Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica)
Classe di laurea: New organization > Master science > LM-25 - AUTOMATION ENGINEERING
Aziende collaboratrici: Politecnico di Torino - PIC4SER
URI: http://webthesis.biblio.polito.it/id/eprint/25594
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