Mutual information based tracking with mobile sensors
Name
711000682-MIT.pdf
Description
Full printable version
Size
1.56 MB
Format
Adobe PDF
Checksum (MD5)
11f65db9b7416bc59f3fd4a30fb81462
Author(s)
Russ, John A., S.M. Massachusetts Institute of Technology
Advisor(s)
Daniela Rus and John Fisher.
Date Issued
2010
Publisher
Massachusetts Institute of Technology
Abstract
In order to utilize mobile sensor nodes in a sensing and estimation problem, one must carefully consider the optimal placement of those sensor nodes and simultaneously account for the cost incurred in moving the sensor nodes. We present an approximate dynamic programming approach to a tracking problem with mobile sensor nodes. We utilize mutual information as the objective for optimal sensor placement. We show how a constrained dynamic programming approach allows us to balance estimation quality against mobility costs. However this constrained optimization problem is NP-hard. We present a set of approximations that allow this dynamic program to be solved with polynomial complexity in the number of sensors. We present a greedy multiple time step planning algorithm that greedily selects the most informative paths over a fixed planning horizon. These approximation algorithms are verified via simulation to give a comparative analysis of estimate quality and mobility costs.
Description
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (p. 125-127).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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