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Addressing pose estimation issues for machine vision based UAV autonomous serial refuelling

Published online by Cambridge University Press:  03 February 2016

G. Campa
Affiliation:
Department of Mechanical and Aerospace Engineering, West Virginia University, Morgantown, USA
M. R. Napolitano
Affiliation:
Department of Mechanical and Aerospace Engineering, West Virginia University, Morgantown, USA
M. Perhinschi
Affiliation:
Department of Mechanical and Aerospace Engineering, West Virginia University, Morgantown, USA
M. L. Fravolini
Affiliation:
Department of Electronics and Information, Perugia University, Perugia, Italy
L. Pollini
Affiliation:
Department of Electrical Systems and Automation, Pisa University, Pisa, Italy
M. Mammarella
Affiliation:
Department of Electrical Systems and Automation, Pisa University, Pisa, Italy

Abstract

This paper describes the results of an effort on the analysis of the performance of specific ‘pose estimation’ algorithms within a Machine Vision-based approach for the problem of aerial refuelling for unmanned aerial vehicles. The approach assumes the availability of a camera on the unmanned aircraft for acquiring images of the refuelling tanker; also, it assumes that a number of active or passive light sources – the ‘markers’ – are installed at specific known locations on the tanker. A sequence of machine vision algorithms on the on-board computer of the unmanned aircraft is tasked with the processing of the images of the tanker. Specifically, detection and labeling algorithms are used to detect and identify the markers and a ‘pose estimation’ algorithm is used to estimate the relative position and orientation between the two aircraft.

Detailed closed-loop simulation studies have been performed to compare the performance of two ‘pose estimation’ algorithms within a simulation environment that was specifically developed for the study of aerial refuelling problems. Special emphasis is placed on the analysis of the required computational effort as well as on the accuracy and the error propagation characteristics of the two methods. The general trade offs involved in the selection of the pose estimation algorithm are discussed. Finally, simulation results are presented and analysed.

Type
Research Article
Copyright
Copyright © Royal Aeronautical Society 2007 

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