Accurate pose determination for autonomous vehicle navigation

Author

Walker, Michael J. ; Sasiadek, Jerzy Z.

Author_Institution

Dept. of Mech. & Aerosp. Eng., Carleton Univ., Ottawa, ON, Canada

fYear

2013

fDate

26-29 Aug. 2013

Firstpage

356

Lastpage

361

Abstract

In this paper, the translational accuracy performance of two algorithms that allow the pose of an Unmanned Aerial Vehicle (UAV) to be estimated is reported, based on preliminary data. The two algorithms are the 2D Homography and the 3D Iterative Closest Point (ICP) algorithm. Performance is measured against real image data taken with a digital Nikon D70 camera, with lens set at 3 different focal lengths. It is shown that best accuracy is achieved with the 3D Iterative Closest Point algorithm and that focal length itself has little or no bearing on this performance. Calibration errors may impact accuracy.

Keywords

autonomous aerial vehicles; calibration; cameras; iterative methods; path planning; pose estimation; 2D homography; 3D ICP algorithm; 3D iterative closest point algorithm; UAV pose estimation; accurate pose determination; autonomous vehicle navigation; calibration errors; digital Nikon D70 camera; focal length; image data; translational accuracy performance; unmanned aerial vehicle pose estimation; Accuracy; Calibration; Cameras; Iterative closest point algorithm; Lenses; Position measurement; Three-dimensional displays;

fLanguage

English

Publisher

ieee

Conference_Titel

Methods and Models in Automation and Robotics (MMAR), 2013 18th International Conference on

Conference_Location

Miedzyzdroje

Print_ISBN

978-1-4673-5506-3

Type

conf

DOI

10.1109/MMAR.2013.6669933

Filename

6669933