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Development of a potential field estimator for a path-planning application using neural networks
dc.creator | Smith, Darin William | |
dc.date.accessioned | 2012-06-07T22:50:34Z | |
dc.date.available | 2012-06-07T22:50:34Z | |
dc.date.created | 1997 | |
dc.date.issued | 1997 | |
dc.identifier.uri | https://hdl.handle.net/1969.1/ETD-TAMU-1997-THESIS-S64 | |
dc.description | Due to the character of the original source materials and the nature of batch digitization, quality control issues may be present in this document. Please report any quality issues you encounter to digital@library.tamu.edu, referencing the URI of the item. | en |
dc.description | Includes bibliographical references: p. 65-66. | en |
dc.description | Issued also on microfiche from Lange Micrographics. | en |
dc.description.abstract | This thesis presents the development of a potential field estimator for a locally constrained autonomous path-planning application. The potential field estimator was developed using back-propagation neural networks, which have been shown to be useful for solving classification problems. It is shown that a back-propagation neural network may be used to classify a three-dimensional obstacle field on the basis of geometrical statistical data. The results of the classification may then be used to find a set of weighting factors that are used to reduce the computational effort needed to solve a path-planning problem. Using the method described here, a reduction of approximately seven percent of the worst-case total computational time for a path-planning problem is observed. The computational expense is still higher than desired for path-planning problems, providing opportunities for further research. Computational expense is measured as the total central processing unit (CPU) time spent solving a path-planning problem. The mathematical framework for the potential field estimator and the path-planning application it supports is presented. This thesis is the product of research performed for Texas A&M University and United Space Alliance. | en |
dc.format.medium | electronic | en |
dc.format.mimetype | application/pdf | |
dc.language.iso | en_US | |
dc.publisher | Texas A&M University | |
dc.rights | This thesis was part of a retrospective digitization project authorized by the Texas A&M University Libraries in 2008. Copyright remains vested with the author(s). It is the user's responsibility to secure permission from the copyright holder(s) for re-use of the work beyond the provision of Fair Use. | en |
dc.subject | aerospace engineering. | en |
dc.subject | Major aerospace engineering. | en |
dc.title | Development of a potential field estimator for a path-planning application using neural networks | en |
dc.type | Thesis | en |
thesis.degree.discipline | aerospace engineering | en |
thesis.degree.name | M.S. | en |
thesis.degree.level | Masters | en |
dc.type.genre | thesis | en |
dc.type.material | text | en |
dc.format.digitalOrigin | reformatted digital | en |
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