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Mobile sensor guidance for optimal information acquisition under out-of-sequence and soft measurements.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Mobile sensor guidance for optimal information acquisition under out-of-sequence and soft measurements./
Author:	Ramirez Paredes, Juan Pablo Ignacio.
Description:	1 online resource (136 pages)
Notes:	Source: Dissertation Abstracts International, Volume: 77-11(E), Section: B.
Contained By:	Dissertation Abstracts International77-11B(E).
Subject:	Robotics. -
Online resource:	click for full text (PQDT)
ISBN:	9781339769011

Mobile sensor guidance for optimal information acquisition under out-of-sequence and soft measurements.
Ramirez Paredes, Juan Pablo Ignacio.

Mobile sensor guidance for optimal information acquisition under out-of-sequence and soft measurements. - 1 online resource (136 pages)

Source: Dissertation Abstracts International, Volume: 77-11(E), Section: B.

Thesis (Ph.D.)

Includes bibliographical references

This item is not available from ProQuest Dissertations & Theses.

Many applications require a time-efficient location of a target, and these tasks are made more difficult in urban environments. For example, Urban Search and Rescue (USAR) may be time-critical after a natural disaster or an accident calls for the rapid location of survivors. Surveillance tasks are also examples of a search and tracking problem. One of the challenges for multiple agent search is the need for communication and coordination among the agents. A centralized structure with sufficient computing power can plan optimal paths, even though the search problem is known to be NP-hard. However, optimal path planning becomes intractable as the number of agents and the complexity of the map increase. Furthermore, a centralized controller requires a fully connected network. Alternatively, the search can be performed in a distributed manner if each agent has access to the target location estimates of one or more of its peers. However, if the communication network of the agents is not fully connected, they will not have shared access to a target location estimate.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9781339769011Subjects--Topical Terms:

561941
Robotics.
Index Terms--Genre/Form:

554714
Electronic books.

Mobile sensor guidance for optimal information acquisition under out-of-sequence and soft measurements.
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100 1 $a Ramirez Paredes, Juan Pablo Ignacio. $3 1182105
245 1 0 $a Mobile sensor guidance for optimal information acquisition under out-of-sequence and soft measurements.
264 0 $c 2016
300 $a 1 online resource (136 pages)
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500 $a Source: Dissertation Abstracts International, Volume: 77-11(E), Section: B.
500 $a Adviser: Nicholas R. Gans.
502 $a Thesis (Ph.D.) $c The University of Texas at Dallas $d 2016.
504 $a Includes bibliographical references
506 $a This item is not available from ProQuest Dissertations & Theses.
520 $a Many applications require a time-efficient location of a target, and these tasks are made more difficult in urban environments. For example, Urban Search and Rescue (USAR) may be time-critical after a natural disaster or an accident calls for the rapid location of survivors. Surveillance tasks are also examples of a search and tracking problem. One of the challenges for multiple agent search is the need for communication and coordination among the agents. A centralized structure with sufficient computing power can plan optimal paths, even though the search problem is known to be NP-hard. However, optimal path planning becomes intractable as the number of agents and the complexity of the map increase. Furthermore, a centralized controller requires a fully connected network. Alternatively, the search can be performed in a distributed manner if each agent has access to the target location estimates of one or more of its peers. However, if the communication network of the agents is not fully connected, they will not have shared access to a target location estimate.
520 $a We present a framework for distributed mobile sensor guidance to locate and track a target inside an urban environment, with an approach that leverages available communications between the mobile sensor and which also allows them to act independently. Each sensor actively seeks the target using information maximization, and is capable of individually pursuing its goal. The sensors are assumed to be capable of detecting their peers within some distance radius, and each sensor is allowed to have target detection errors of types I and II. Our contributions include an algorithm for information-based target search that uses posterior entropy minimization without directly computing this quantity, a closed-form solution to the sensor placement problem for binary detectors, an augmented particle filter estimator that handles delayed or out-of-sequence measurements, and an optimal information fusion algorithm for discrete probability mass functions. This allows each agent to combine its local information with that of its neighbors, if any. We include simulations and laboratory experiments involving multiple robots searching for a moving target within model cities of different sizes.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Robotics. $3 561941
650 4 $a Electrical engineering. $3 596380
650 4 $a Information science. $3 561178
655 7 $a Electronic books. $2 local $3 554714
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710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a The University of Texas at Dallas. $b Electrical Engineering. $3 1181534
773 0 $t Dissertation Abstracts International $g 77-11B(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10113844 $z click for full text (PQDT)