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Dynamic neural network approach to i...

Sakalaukus, James R.

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Dynamic neural network approach to integrated autonomous path planning and navigation.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Dynamic neural network approach to integrated autonomous path planning and navigation./
Author:	Sakalaukus, James R.
Description:	73 p.
Notes:	Source: Masters Abstracts International, Volume: 48-06, page: 3809.
Contained By:	Masters Abstracts International48-06.
Subject:	Engineering, Computer. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1485493
ISBN:	9781124132150

Dynamic neural network approach to integrated autonomous path planning and navigation.
Sakalaukus, James R.

Dynamic neural network approach to integrated autonomous path planning and navigation. - 73 p.

Source: Masters Abstracts International, Volume: 48-06, page: 3809.

Thesis (M.S.)--University of South Alabama, 2010.

A new method for autonomously navigating a robot in an indoor dynamic environment was developed. A fuzzy inference system (FIS) and a neural network were developed and tested, and the FIS was better able to navigate the robot in a complex environment. The FIS system was implemented in the embedded hardware of the robot, thus eliminating a laptop computer running MATLAB and LabVIEW. A wrapper for the FIS was made to accept human directions over a TCP/IP protocol. The protocol can be used to navigate a robot autonomously from one location to another in the same building using the FIS.

ISBN: 9781124132150Subjects--Topical Terms:

1669061
Engineering, Computer.

Dynamic neural network approach to integrated autonomous path planning and navigation.
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020 $a 9781124132150
035 $a (UMI)AAI1485493
035 $a AAI1485493
040 $a UMI $c UMI
100 1 $a Sakalaukus, James R. $3 1672556
245 1 0 $a Dynamic neural network approach to integrated autonomous path planning and navigation.
300 $a 73 p.
500 $a Source: Masters Abstracts International, Volume: 48-06, page: 3809.
500 $a Adviser: Thomas G. Thomas, Jr.
502 $a Thesis (M.S.)--University of South Alabama, 2010.
520 $a A new method for autonomously navigating a robot in an indoor dynamic environment was developed. A fuzzy inference system (FIS) and a neural network were developed and tested, and the FIS was better able to navigate the robot in a complex environment. The FIS system was implemented in the embedded hardware of the robot, thus eliminating a laptop computer running MATLAB and LabVIEW. A wrapper for the FIS was made to accept human directions over a TCP/IP protocol. The protocol can be used to navigate a robot autonomously from one location to another in the same building using the FIS.
590 $a School code: 0491.
650 4 $a Engineering, Computer. $3 1669061
650 4 $a Engineering, Electronics and Electrical. $3 626636
650 4 $a Engineering, Robotics. $3 1018454
690 $a 0464
690 $a 0544
690 $a 0771
710 2 $a University of South Alabama. $3 1017878
773 0 $t Masters Abstracts International $g 48-06.
790 1 0 $a Thomas, Thomas G., Jr., $e advisor
790 $a 0491
791 $a M.S.
792 $a 2010
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1485493