Development of a potential field estimator for a path-planning application using neural networks /
and United Space Alliance.
| Main Author: | |
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| Format: | Thesis eBook |
| Language: | English |
| Published: |
[Place of publication not identified] :
[publisher not identified] ;
1997.
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| Subjects: | |
| Online Access: | Link to OAKTrust copy |
| Summary: | and United Space Alliance. application. The potential field estimator was developed classification may then be used to find a set of weighting classify a three-dimensional obstacle field on the basis of described here, a reduction of approximately seven percent of estimator for a locally constrained autonomous path-planning factors that are used to reduce the computational effort framework for the potential field estimator and the path- geometrical statistical data. The results of the higher than desired for path-planning problems, providing is the product of research performed for Texas A&M University measured as the total central processing unit (CPU) time needed to solve a path-planning problem. Using the method opportunities for further research. Computational expense is planning application it supports is presented. This thesis problem is observed. The computational expense is still shown that a back-propagation neural network may be used to spent solving a path-planning problem. The mathematical the worst-case total computational time for a path-planning This thesis presents the development of a potential field to be useful for solving classification problems. It is using back-propagation neural networks, which have been shown |
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| Item Description: | "Major subject: Aerospcae Engineering". Vita. |
| Physical Description: | ix, 80 leaves : illustrations ; 28 cm. Also available online. Issued also on microfiche from Lange Micrographics. |
| Bibliography: | Includes bibliographical references: pages 65-66. |