Title:
Curvature Based Cooperative Exploration of Three Dimensional Scalar Fields

dc.contributor.author Wu, Wencen
dc.contributor.author Zhang, Fumin
dc.contributor.corporatename Georgia Institute of Technology. School of Electrical and Computer Engineering
dc.contributor.corporatename Georgia Institute of Technology. Center for Robotics and Intelligent Machines
dc.date.accessioned 2011-05-16T17:18:07Z
dc.date.available 2011-05-16T17:18:07Z
dc.date.issued 2010
dc.description.abstract We develop strategies for controlled motion and filtering performed by a mobile sensor network to cooperatively explore an unknown 3D scalar field. In order to estimate the principal directions and principal curvatures of a desired level surface of the field which are used as feedback by the motion control law, we apply a non-analytic curvature estimation algorithm and prove the sufficient and necessary conditions under which this algorithm can provide reliable estimates. A differential geometric approach is followed in developing provably convergent steering control laws to control the center of the sensor platform formation to track one of the lines of curvature on a detected level surface of the scalar field. en_US
dc.identifier.citation W. Wu and Fumin Zhang, “Curvature Based Cooperative Exploration of Three Dimensional Scalar Fields,” in Proc. 2010 American Control Conference (ACC 2010), 2909-2915, 2010. en_US
dc.identifier.issn 0743-1619
dc.identifier.uri http://hdl.handle.net/1853/38886
dc.language.iso en_US en_US
dc.publisher Georgia Institute of Technology en_US
dc.publisher.original American Automatic Control Council
dc.subject Mobile sensor networks en_US
dc.subject Motion control law en_US
dc.subject Filtering en_US
dc.title Curvature Based Cooperative Exploration of Three Dimensional Scalar Fields en_US
dc.type Text
dc.type.genre Proceedings
dspace.entity.type Publication
local.contributor.author Zhang, Fumin
local.contributor.corporatename Institute for Robotics and Intelligent Machines (IRIM)
relation.isAuthorOfPublication 65d2541f-4ce1-40d0-923b-09e66eb45b33
relation.isOrgUnitOfPublication 66259949-abfd-45c2-9dcc-5a6f2c013bcf
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