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A Real-Time Expectation Maximization Algorithm for Acquiring Multi-Planar Maps of Indoor Environments with Mobile Robots

by Sebastian Thrun, Christian Martin, Yufeng Liu, Dirk H\"{a}hnel, Rosemary Emery-Montemerlo, Deepayan Chakrabarti, and Wolfram Burgard

Abstract: This paper presents a real-time algorithm for acquiring compact 3D maps of indoor environments, using a mobile robot equipped with range and imaging sensors. Building on previous work on real-time pose estimation during mapping, our approach extends the popular expectation maximization algorithm to multi-surface models, and makes it amenable to real-time execution. Maps acquired by our algorithm consist of compact sets of textured polygons that can be visualized interactively. Experimental results obtained in corridor-type environments illustrate that compact and accurate maps can be acquired in real-time and in a fully automated fashion.

Available for download in


@ARTICLE{Thrun02h,
  AUTHOR	= {Thrun, S. and Martin, C. and Liu, Y. and H\"{a}hnel, D. 
                   and Emery-Montemerlo, R. and Chakrabarti, D. and Burgard, W.},
  TITLE		= {A Real-Time Expectation Maximization Algorithm for 
                   Acquiring Multi-Planar Maps of Indoor Environments 
                   with Mobile Robots},
  JOURNAL	= {{IEEE} Transactions on Robotics and Automation},
  YEAR		= {2003},
  NOTE          = {To Appear}
}