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Control theory / Cybernetics / Markov models / Robot navigation / Linear filters / Particle filter / Kalman filter / Algorithm / Monte Carlo localization / Estimation theory / Robot control / Statistics


In IEEE International Conference on Robotics and Automation (ICRA 08), Pasadena, CA, May[removed]Negative Information and Line Observations for Monte Carlo Localization Todd Hester and Peter Stone
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Document Date: 2008-01-24 17:07:24


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City

Pasadena / Paris / /

Company

MIT Press / Computer Sciences / A. K. Peters Ltd. / Sony / AI Laboratory / /

Country

United States / /

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Facility

Computer Sciences University of Texas / University of Texas / Eiffel tower / UT Austin Villa / /

IndustryTerm

baseline algorithm / implemented algorithm / localization algorithms / described localization algorithm / river bank / modifications to their algorithm / localization algorithm / /

OperatingSystem

OSE / /

Organization

University of Texas at Austin / National Science Foundation / Computer Sciences University / MIT / /

Person

Michael Quinlan / Peter Stone / Gregory Kuhlmann / Daniel Stronger / Nate Kohl / Mohan Sridharan / Todd Hester / /

Position

observation model for negative information and line observations / head / goal keeper / /

Product

Hoffmann et al. / /

ProgrammingLanguage

R / C / /

ProvinceOrState

Texas / California / /

PublishedMedium

Lecture Notes in Computer Science / /

Technology

baseline algorithm / Monte Carlo localization algorithm / described localization algorithm / localization algorithms / simulation / localization algorithm / /

URL

http /

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