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Abstractions, analysis techniques, a...

Berman, Spring Melody.

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Abstractions, analysis techniques, and synthesis of scalable control strategies for robot swarms.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Abstractions, analysis techniques, and synthesis of scalable control strategies for robot swarms./
Author:	Berman, Spring Melody.
Description:	216 p.
Notes:	Source: Dissertation Abstracts International, Volume: 71-12, Section: B, page: .
Contained By:	Dissertation Abstracts International71-12B.
Subject:	Engineering, Mechanical. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3431100
ISBN:	9781124324968

Abstractions, analysis techniques, and synthesis of scalable control strategies for robot swarms.
Berman, Spring Melody.

Abstractions, analysis techniques, and synthesis of scalable control strategies for robot swarms. - 216 p.

Source: Dissertation Abstracts International, Volume: 71-12, Section: B, page: .

Thesis (Ph.D.)--University of Pennsylvania, 2010.

Tasks that require parallelism, redundancy, and adaptation to dynamic, possibly hazardous environments can potentially be performed very efficiently and robustly by a swarm robotic system. Such a system would consist of hundreds or thousands of anonymous, resource-constrained robots that operate autonomously, with little to no direct human supervision. The massive parallelism of a swarm would allow it to perform effectively in the event of robot failures, and the simplicity of individual robots facilitates a low unit cost. Key challenges in the development of swarm robotic systems include the accurate prediction of swarm behavior and the design of robot controllers that can be proven to produce a desired macroscopic outcome. The controllers should be scalable, meaning that they ensure system operation regardless of the swarm size.

ISBN: 9781124324968Subjects--Topical Terms:

783786
Engineering, Mechanical.

Abstractions, analysis techniques, and synthesis of scalable control strategies for robot swarms.
LDR:03275nam 2200301 4500 001 1392689
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008 130515s2010 ||||||||||||||||| ||eng d
020 $a 9781124324968
035 $a (UMI)AAI3431100
035 $a AAI3431100
040 $a UMI $c UMI
100 1 $a Berman, Spring Melody. $3 1671154
245 1 0 $a Abstractions, analysis techniques, and synthesis of scalable control strategies for robot swarms.
300 $a 216 p.
500 $a Source: Dissertation Abstracts International, Volume: 71-12, Section: B, page: .
500 $a Adviser: Vijay Kumar.
502 $a Thesis (Ph.D.)--University of Pennsylvania, 2010.
520 $a Tasks that require parallelism, redundancy, and adaptation to dynamic, possibly hazardous environments can potentially be performed very efficiently and robustly by a swarm robotic system. Such a system would consist of hundreds or thousands of anonymous, resource-constrained robots that operate autonomously, with little to no direct human supervision. The massive parallelism of a swarm would allow it to perform effectively in the event of robot failures, and the simplicity of individual robots facilitates a low unit cost. Key challenges in the development of swarm robotic systems include the accurate prediction of swarm behavior and the design of robot controllers that can be proven to produce a desired macroscopic outcome. The controllers should be scalable, meaning that they ensure system operation regardless of the swarm size.
520 $a This thesis presents a comprehensive approach to modeling a swarm robotic system, analyzing its performance, and synthesizing scalable control policies that cause the populations of different swarm elements to evolve in a specified way that obeys time and efficiency constraints. The control policies are decentralized, computed a priori, implementable on robots with limited sensing and communication capabilities, and have theoretical guarantees on performance. To facilitate this framework of abstraction and top-down controller synthesis, the swarm is designed to emulate a system of chemically reacting molecules. The majority of this work considers well-mixed systems when there are interaction-dependent task transitions, with some modeling and analysis extensions to spatially inhomogeneous systems.
520 $a The methodology is applied to the design of a swarm task allocation approach that does not rely on inter-robot communication, a reconfigurable manufacturing system, and a cooperative transport strategy for groups of robots. The third application incorporates observations from a novel experimental study of the mechanics of cooperative retrieval in Aphaenogaster cockerelli ants. The correctness of the abstractions and the correspondence of the evolution of the controlled system to the target behavior are validated with computer simulations. The investigated applications form the building blocks for a versatile swarm system with integrated capabilities that have performance guarantees.
590 $a School code: 0175.
650 4 $a Engineering, Mechanical. $3 783786
650 4 $a Engineering, Robotics. $3 1018454
690 $a 0548
690 $a 0771
710 2 $a University of Pennsylvania. $3 1017401
773 0 $t Dissertation Abstracts International $g 71-12B.
790 1 0 $a Kumar, Vijay, $e advisor
790 $a 0175
791 $a Ph.D.
792 $a 2010
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3431100