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Robot controller architecture: Layer...

University of Arkansas at Little Rock., Applied Science.

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Robot controller architecture: Layered mode selection logic with Fuzzy Sensor Fusion Network.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Robot controller architecture: Layered mode selection logic with Fuzzy Sensor Fusion Network./
Author:	Born, Traig E. B.
Description:	150 p.
Notes:	Adviser: Andrew B. Wright.
Contained By:	Masters Abstracts International46-06.
Subject:	Computer Science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1453495
ISBN:	9780549561859

Robot controller architecture: Layered mode selection logic with Fuzzy Sensor Fusion Network.
Born, Traig E. B.

Robot controller architecture: Layered mode selection logic with Fuzzy Sensor Fusion Network. - 150 p.

Adviser: Andrew B. Wright.

Thesis (M.S.)--University of Arkansas at Little Rock, 2008.

A behavior based robot controller was implemented using Layered Mode Selection Logic as a behavior coordination mechanism and a Fuzzy Sensor Fusion Network to provide perception. A series of collision experiments were conducted to create a Fuzzy Sensor Fusion Network capable of detecting collisions using acceleration readings from wheel encoders. An obstacle avoidance behavior was created, and it was demonstrated that the robot could be constrained by movable obstacles. The avoidance behavior was modified to create an obstacle manipulation behavior. This behavior allowed the robot to escape when enclosed by movable obstacles. The fuzzy sensor fusion network was enhanced to allow for the identification of heavy obstacles by adding a force sensor. Fault tolerance was demonstrated by faulting either the force sensor or the acceleration sensor and observing that the system retained its collision detection capabilities. The system was shown to be scalable toward task complexity and robot complexity.

ISBN: 9780549561859Subjects--Topical Terms:

626642
Computer Science.

Robot controller architecture: Layered mode selection logic with Fuzzy Sensor Fusion Network.
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020 $a 9780549561859
035 $a (UMI)AAI1453495
035 $a AAI1453495
040 $a UMI $c UMI
100 1 $a Born, Traig E. B. $3 1035871
245 1 0 $a Robot controller architecture: Layered mode selection logic with Fuzzy Sensor Fusion Network.
300 $a 150 p.
500 $a Adviser: Andrew B. Wright.
500 $a Source: Masters Abstracts International, Volume: 46-06, page: 3420.
502 $a Thesis (M.S.)--University of Arkansas at Little Rock, 2008.
520 $a A behavior based robot controller was implemented using Layered Mode Selection Logic as a behavior coordination mechanism and a Fuzzy Sensor Fusion Network to provide perception. A series of collision experiments were conducted to create a Fuzzy Sensor Fusion Network capable of detecting collisions using acceleration readings from wheel encoders. An obstacle avoidance behavior was created, and it was demonstrated that the robot could be constrained by movable obstacles. The avoidance behavior was modified to create an obstacle manipulation behavior. This behavior allowed the robot to escape when enclosed by movable obstacles. The fuzzy sensor fusion network was enhanced to allow for the identification of heavy obstacles by adding a force sensor. Fault tolerance was demonstrated by faulting either the force sensor or the acceleration sensor and observing that the system retained its collision detection capabilities. The system was shown to be scalable toward task complexity and robot complexity.
590 $a School code: 1204.
650 4 $a Computer Science. $3 626642
650 4 $a Engineering, Robotics. $3 1018454
690 $a 0771
690 $a 0984
710 2 $a University of Arkansas at Little Rock. $b Applied Science. $3 1025778
773 0 $t Masters Abstracts International $g 46-06.
790 $a 1204
790 1 0 $a Anderson, Gary T. $e committee member
790 1 0 $a Milanova, Mariofanna G. $e committee member
790 1 0 $a Tang, Peiyi $e committee member
790 1 0 $a Wright, Andrew B., $e advisor
790 1 0 $a Ye, Cang $e committee member
791 $a M.S.
792 $a 2008
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1453495