Paper Info
Title
Modelling And Performance Analysis Of A Machine Vision-Based Semi-Autonomous Aerial Refuelling
Abstract
A critical aspect in the design of Semi-Autonomous Aerial Refuelling (SAAR) control schemes for Unmanned Aerial Vehicles (UAVs) is the availability of accurate measurements of the relative UAV-Tanker distance and attitude. In this effort, the attention was focused on the development of an accurate modelling of the SAAR manoeuvre and on the development of a Machine Vision-based scheme for the estimation of the tanker-UAV relative pose. The developed MV scheme is based on markers installed on the surface of the tanker, and performs specific tasks as Feature Extraction, Feature Matching, and tanker-UAV relative Pose Estimation. The accuracy/robustness of the overall scheme was evaluated in the event of markers occlusion, in presence of inaccuracy in the positioning of the markers on the tanker aircraft, as a function of the level of attitude and GPS sensors' noise and as a function of the data Transmission Delay (TD) between aircrafts.
Year
DOI
Venue
2008
10.1504/IJMIC.2008.020544
INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL
Keywords
Field
DocType
unmanned aerial vehicle modelling, machine vision modelling, sensors, feature extraction, FE, fracture matching, pose estimation, PE
Computer vision,Data transmission,Machine vision,Feature extraction,Control engineering,Robustness (computer science),Pose,Feature matching,Artificial intelligence,Global Positioning System,Mathematics
Journal
Volume
Issue
ISSN
3
4
1746-6172
Citations 
PageRank 
References 
2
0.44
5
Authors
3
Name
Order
Citations
PageRank
Mario Luca Fravolini15012.71
G. Campa210212.38
Marcello R. Napolitano35612.38