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Path planning for an unmanned terrestrial vehicle in an obstacle ridden environment

Thesis (MEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2009.

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Bibliographic Details
Main Author: Ferreira, Thomas Ignatius
Other Authors: Peddle, I. K.
Format: Thesis
Language:English
Published: Stellenbosch : University of Stellenbosch 2009
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access_status_str Open Access
author Ferreira, Thomas Ignatius
author2 Peddle, I. K.
author_browse Ferreira, Thomas Ignatius
Peddle, I. K.
author_facet Peddle, I. K.
Ferreira, Thomas Ignatius
author_sort Ferreira, Thomas Ignatius
collection Thesis
dc_rights_str_mv University of Stellenbosch
description Thesis (MEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2009.
format Thesis
id oai:scholar.sun.ac.za:10019.1/1775
institution Stellenbosch University (South Africa)
language English
last_indexed 2026-06-10T12:44:13.588Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository
publishDate 2009
publishDateRange 2009
publishDateSort 2009
publisher Stellenbosch : University of Stellenbosch
publisherStr Stellenbosch : University of Stellenbosch
record_format dspace
source_str SUNScholar — Stellenbosch University Repository
spelling oai:scholar.sun.ac.za:10019.1/1775 Path planning for an unmanned terrestrial vehicle in an obstacle ridden environment Ferreira, Thomas Ignatius Peddle, I. K. University of Stellenbosch. Faculty of Engineering. Dept. of Electrical and Electronic Engineering. Path planning Visibility graphs Vehicles, Remotely piloted Dissertations -- Electrical engineering Theses -- Electrical engineering Thesis (MEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2009. This thesis relates to the successful development of an unmanned terrestrial vehicle (UTV) capable of operating in an obstacle ridden environment. The primary focus of the project is on the specific path planning algorithms. It is shown that specific methods of populating the obstacle-free space can be combined with methods of extracting the shortest path from these popula- tions. Through use of such combinations the successful generation of optimal collision-free paths is demonstrated. Previously developed modular architectures are combined and modified to create a UTV platform which meets all the requirements for implementation of navigational systems and path planning algorithms on board the platform. A two-dimensional kinematic state estimator is developed. This estimator makes use of extended Kalman Filter theory to optimally combine measurements from low cost sensors to yield the vehicle’s state vector. Lateral guidance controllers are developed to utilize this estimated state vector in a feedback control configuration. The entire system is then successfully demonstrated within a simulation environment. Finally, practical results from two days of test runs are provided in both written and interactive form 2009-02-25T14:19:03Z 2010-06-01T08:32:59Z 2009-02-25T14:19:03Z 2010-06-01T08:32:59Z 2009-03 Thesis http://hdl.handle.net/10019.1/1775 en University of Stellenbosch application/pdf Stellenbosch : University of Stellenbosch
spellingShingle Path planning
Visibility graphs
Vehicles, Remotely piloted
Dissertations -- Electrical engineering
Theses -- Electrical engineering
Ferreira, Thomas Ignatius
Path planning for an unmanned terrestrial vehicle in an obstacle ridden environment
title Path planning for an unmanned terrestrial vehicle in an obstacle ridden environment
title_full Path planning for an unmanned terrestrial vehicle in an obstacle ridden environment
title_fullStr Path planning for an unmanned terrestrial vehicle in an obstacle ridden environment
title_full_unstemmed Path planning for an unmanned terrestrial vehicle in an obstacle ridden environment
title_short Path planning for an unmanned terrestrial vehicle in an obstacle ridden environment
title_sort path planning for an unmanned terrestrial vehicle in an obstacle ridden environment
topic Path planning
Visibility graphs
Vehicles, Remotely piloted
Dissertations -- Electrical engineering
Theses -- Electrical engineering
url http://hdl.handle.net/10019.1/1775
work_keys_str_mv AT ferreirathomasignatius pathplanningforanunmannedterrestrialvehicleinanobstacleriddenenvironment