Masters Theses
Abstract
"In this thesis, a path planning method using a three-level hierarchical system model is proposed. In the top level of the hierarchy, the given location points to visit are taken as waypoints. The waypoint navigation process is formulated as a traveling salesman problem (TSP). The Lin-Kernighan algorithm is used to solve the TSP and transfer the solution to the lower level of the hierarchy. In the middle level, the path is represented by a grid-based costmap. A novel modified Grossberg neural network is designed to solve the point-to-point path planning. The bottom level of the hierarchy smoothens the path with kinematic constraints. The final results are simulated in a 3D virtual reality environment by using the MATLAB VR toolbox"--Abstract, page iii.
Advisor(s)
Balakrishnan, S. N.
Committee Member(s)
Dagli, Cihan H., 1949-
Wunsch, Donald C.
Department(s)
Mechanical and Aerospace Engineering
Degree Name
M.S. in Mechanical Engineering
Publisher
Missouri University of Science and Technology
Publication Date
Spring 2011
Pagination
vii, 44 pages
Note about bibliography
Includes bibliographical references (pages 41-43).
Rights
© 2011 Songjie Chen, All rights reserved.
Document Type
Thesis - Open Access
File Type
text
Language
English
Subject Headings
Traveling salesman problemNeural networks (Computer science)Intelligent control systems -- Mathematical models
Thesis Number
T 10227
Print OCLC #
863049523
Electronic OCLC #
909535007
Recommended Citation
Chen, Songjie, "A neural network based approach for path planning on costmap" (2011). Masters Theses. 4482.
https://scholarsmine.mst.edu/masters_theses/4482