UAV Inspection of Large Components. Adaptive Navigation at Runtime

Thèse de Bachelor , 2019 , 49 Pages , Note: 1.0

Informatique - Informatique appliquée

In this thesis, two problems are covered. The first one is to estimate the position of a drone out of two different given transformations, which don’t have the same coordinate origin. Furthermore, measurement errors have to be outbalanced so that the position estimation is as accurate as possible. In order to solve this problem, a Kalman Filter was utilized.

The second problem is to direct the drone to given goal positions while avoiding obstacles. For directing the drone to the desired location a vector flight control with temporary goals was created. The vector flight control is working online and is constantly using the current estimated position of the Kalman Filter in order to direct the drone correctly at each time. This thesis is covering the concept, the implementation and evaluation of these algorithms.

• Université: University of Augsburg
• Note: 1.0
• Auteur: Michelle Bettendorf (Auteur)
• Année de publication: 2019
• Pages: 49
• N° de catalogue: V1162994
• ISBN (PDF): 9783346584656
• ISBN (Livre): 9783346584663
• Langue: anglais
• mots-clé: UAV, drone, computerscience, bachelorthesis, kalmanfilter, potentialfield