Optimal algorithm design for transfer path planning for unmanned aerial vehicles

Pollock, Andrew George (2014) Optimal algorithm design for transfer path planning for unmanned aerial vehicles. PhD thesis, University of Glasgow.

Full text available as:
[img] PDF
Download (14MB)

Abstract

Over the past three decades unmanned aerial vehicles (UAV) have seen significant development with a current focus on automation. The main area of development that is pushing automation is that of path planning allowing a UAV to generate its own path information that it can then follow to carry out its mission. Little work however has been carried out on transfer path planning. This work attempts to address this shortcoming by developing optimal algorithms for a path planning task to move on to a circular flightpath to carry out a target tracking mission. The work is developed in three main sections. Firstly the transfer algorithm itself is derived including gradient analysis for the cost function being applied, adaptation of this cost function into two separate minimising actions and analysis of a cost function issue that introduces a separation distance constraint. The algorithm is tested proving correct constraint activation and cost selection. The second part of this work looks at validating the results of the transfer algorithm against the Dubin's car result and a receding horizon approach when applied to the transfer operation. Utilising the cost results from the transfer algorithm an efficiency analysis against the equivalent costs from the other methods is carried out. Lastly this work looks at the comparison between the developed transfer algorithm and a more flexible transfer approach by developing a new cost function form. A switching cost function is introduced where environmental parameters from the target tracking mission (i.e target position and velocity) are used to switch between a number of applicable cost functions (time minimal, distance minimal and minimum speed transfer). An analysis is carried out to investigate the performance of both the original algorithm and the newly developed switching function based on key target tracking parameters

Item Type: Thesis (PhD)
Qualification Level: Doctoral
Keywords: UAV, Unmanned Aerial Vehicle, Path Planning, Optimal
Subjects: T Technology > T Technology (General)
T Technology > TL Motor vehicles. Aeronautics. Astronautics
Colleges/Schools: College of Science and Engineering > School of Engineering > Aerospace Sciences
Funder's Name: UNSPECIFIED
Supervisor's Name: Kim, Dr. Jongrae
Date of Award: 2014
Depositing User: Andrew G Pollock
Unique ID: glathesis:2014-5485
Copyright: Copyright of this thesis is held by the author.
Date Deposited: 10 Sep 2014 09:16
Last Modified: 10 Sep 2014 13:56
URI: http://theses.gla.ac.uk/id/eprint/5485

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year