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A real-time expectation-maximization algorithm for acquiring multiplanar maps of indoor environments with mobile robots

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7 Author(s)
Thrun, S. ; Comput. Sci. Dept., Stanford Univ., CA, USA ; Martin, C. ; Yufeng Liu ; Hahnel, D.
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This paper presents a real-time algorithm for acquiring compact three-dimensional 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 multisurface 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.

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Robotics and Automation, IEEE Transactions on  (Volume:20 ,  Issue: 3 )