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Robot navigation / Visual effects / Imaging / Artificial intelligence / Expectation–maximization algorithm / Missing data / 3D modeling / Rendering / Occupancy grid mapping / Statistics / 3D computer graphics / Estimation theory


To appear at the Eighteenth International Conference on Machine Learning Williams College, June 28-July 1, 2001 Using EM to Learn 3D Models of Indoor Environments with Mobile Robots Yufeng Liu
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Document Date: 2004-12-16 14:22:19

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City

FREIBURG / /

Company

Hanson / Robotic Systems / MIT Press / ANDREW / /

Country

United States / /

Currency

USD / /

Facility

Machine Learning Williams College / University Freiburg / Carnegie Mellon University / /

IndustryTerm

expectation maximization algorithm / post-processing step / closeform solution / robot systems / real-time algorithm / online algorithm / model estimation algorithm / final post-processing step / /

Organization

Royal Statistical Society / Robotics Institute / National Science Foundation / MIT / Germany Sebastian Thrun School of Computer Science / DE Institut f¨ur Informatik / EDU Center for Automated Learning and Discovery / Carnegie Mellon University / Pittsburgh / Williams College / Department of Physics / /

Person

Rosemary Emery / Figure / Nocera / Percentage / /

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Position

multi-surface model / model / ranger / uIv wB / /

ProvinceOrState

Pennsylvania / /

PublishedMedium

Journal of the Royal Statistical Society / Machine Learning / /

Technology

online algorithm / laser / Terminating Model Components The EM algorithm / real-time algorithm / 3-D / artificial intelligence / virtual reality / existing algorithms / expectation maximization algorithm / Machine Learning / EM algorithm / model estimation algorithm / /

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