東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

A potential field approach to multip...

Talati, Rohit Santosh.

Linked to FindBook

Google Book

Amazon

博客來

A potential field approach to multiple robot formation control .

Record Type:	Language materials, printed : Monograph/item
Title/Author:	A potential field approach to multiple robot formation control ./
Author:	Talati, Rohit Santosh.
Description:	115 p.
Notes:	Adviser: Dan Popa.
Contained By:	Masters Abstracts International46-01.
Subject:	Engineering, Electronics and Electrical. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1445738
ISBN:	9780549144144

A potential field approach to multiple robot formation control .
Talati, Rohit Santosh.

A potential field approach to multiple robot formation control . - 115 p.

Adviser: Dan Popa.

Thesis (M.S.)--The University of Texas at Arlington, 2007.

A special case of cooperative control for mobile robots is considered---formation control. A potential field based algorithm is developed in which geometric, communication and information centric influences are considered and allowed to deform the formation. Control is accomplished in a leader-follower(s) method. One leader robot defines the overall trajectory and follower nodes individually and autonomously maintain the formation while simultaneously moving toward a goal position. The particular nodes considered are the ARRIbots developed at the Distributed and Intelligence and Autonomy Lab (DIAL) in the Automation and Robotic and Research Institute (ARRI), which are non-holonomic differential-drive wheeled robots. In order to facilitate the above, a kinematic model for the ARRIbot mobile robot that accounts for its non-holonomic constraint and particular inputs is presented. Based on this model, a trajectory tracking controller (LQR based) is detailed assuming a given reference trajectory. Finally additional artificial forces are added to account for additional constraints on the optimal node paths and positions. Obstacle avoidance is added to the formation by repulsive forces and an artificial communications force is added in order to optimize the wireless communications channel between nodes. These results are validated using computer simulations and experiments with the ARRIbots on our mobile robot platform.

ISBN: 9780549144144Subjects--Topical Terms:

626636
Engineering, Electronics and Electrical.

A potential field approach to multiple robot formation control .
LDR:03198nam 2200313 a 45 001 963225
005 20110830
008 110831s2007 ||||||||||||||||| ||eng d
020 $a 9780549144144
035 $a (UMI)AAI1445738
035 $a AAI1445738
040 $a UMI $c UMI
100 1 $a Talati, Rohit Santosh. $3 1286282
245 1 2 $a A potential field approach to multiple robot formation control .
300 $a 115 p.
500 $a Adviser: Dan Popa.
500 $a Source: Masters Abstracts International, Volume: 46-01, page: 0523.
502 $a Thesis (M.S.)--The University of Texas at Arlington, 2007.
520 $a A special case of cooperative control for mobile robots is considered---formation control. A potential field based algorithm is developed in which geometric, communication and information centric influences are considered and allowed to deform the formation. Control is accomplished in a leader-follower(s) method. One leader robot defines the overall trajectory and follower nodes individually and autonomously maintain the formation while simultaneously moving toward a goal position. The particular nodes considered are the ARRIbots developed at the Distributed and Intelligence and Autonomy Lab (DIAL) in the Automation and Robotic and Research Institute (ARRI), which are non-holonomic differential-drive wheeled robots. In order to facilitate the above, a kinematic model for the ARRIbot mobile robot that accounts for its non-holonomic constraint and particular inputs is presented. Based on this model, a trajectory tracking controller (LQR based) is detailed assuming a given reference trajectory. Finally additional artificial forces are added to account for additional constraints on the optimal node paths and positions. Obstacle avoidance is added to the formation by repulsive forces and an artificial communications force is added in order to optimize the wireless communications channel between nodes. These results are validated using computer simulations and experiments with the ARRIbots on our mobile robot platform.
520 $a It was found that the potential field algorithm was successful in maintaining the required node formation. The position error for follower nodes was found to decay as required. In addition, a simulation of mine-field detection scenario was shown to successfully combine the three formation influences. The LQR trajectory tracker was found to satisfy the requirements of the formation control algorithm. The state estimate error was low for both straight line and turning motions while the tracking error was low for straight line and high for turning motions. This was attributed to the short duration of the latter and amplification of calculation and processing delay errors. The accuracy of the state estimate errors was shown to be useful in reducing the tracking error over multiple trajectories.
590 $a School code: 2502.
650 4 $a Engineering, Electronics and Electrical. $3 626636
650 4 $a Engineering, Robotics. $3 1018454
690 $a 0544
690 $a 0771
710 2 $a The University of Texas at Arlington. $b Electrical Engineering. $3 1018571
773 0 $t Masters Abstracts International $g 46-01.
790 $a 2502
790 1 0 $a Lewis, Frank L. $e committee member
790 1 0 $a Popa, Dan, $e advisor
790 1 0 $a Stephanou, Harry $e committee member
791 $a M.S.
792 $a 2007
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1445738