ETD

Archivio digitale delle tesi discusse presso l'Università di Pisa

Tesi etd-11252018-095237


Tipo di tesi
Tesi di laurea magistrale
Autore
MARCHETTI, DANIELE
URN
etd-11252018-095237
Titolo
Design and implementation of a vision-based precision landing system for autonomous inspection aerial platforms
Dipartimento
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
INGEGNERIA ROBOTICA E DELL'AUTOMAZIONE
Relatori
relatore Prof. Pollini, Lorenzo
relatore Dott. Barbieri, Ugo
relatore Ing. Bancallari, Luca
relatore Prof. Innocenti, Mario
Parole chiave
  • motion capture
  • Kalman filter
  • optical flow
  • visual servoing
  • fiducial markers
  • computer vision
  • autonomous landing
  • unmanned aerial vehicle
  • offboard control
  • autopilot
  • guidance systems
  • indoor navigation
Data inizio appello
10/12/2018
Consultabilità
Non consultabile
Data di rilascio
10/12/2088
Riassunto
This work of Thesis is concerned with the design, implementation and test of a precision autonomous landing system for a multirotor. It is involved in the Dromosplan European project, which is aimed at introducing swarm of drones in autonomous inspection, monitoring and surveillance of steel plants. In particular, the focus of this work is to make the drone capable of going to recharge autonomously on a landing pad of limited size. At first, the requirements of the application are analyzed, the methods and the equipment considered more suitable are selected by evaluating the state of the art and the available technology, and then implemented on a development aerial vehicle. The images from a bottom camera are processed to detect a set of markers placed on the landing pad to estimate the position and orientation with respect to the platform. A distance sensor and an optical flow device are integrated onboard to measure the distance and the horizontal velocity with respect to the ground, respectively. All data from the onboard sensors are fused by an extended and delayed Kalman filter to obtain precise and robust estimates of the vehicle state. Furthermore, a ground map of markers is employed for indoor navigation. Proportional Navigation is implemented to guide the drone in the approach phase to the platform, while a more aggressive PID control is applied in the final phase, with a smooth transition between the two. A safety check is also performed during the descend to ensure a reliable landing. Finally, indoor flight tests are repeatedly carried out to properly tune the Kalman filter, and then flight data are compared with the measures from the Vicon motion capture system, considered as ground truth.
File