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Predictive and Semantic Layout Estimation for Robotic Applications in Manhattan Worlds
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Predictive and Semantic Layout Estimation for Robotic Applications in Manhattan Worlds
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Paper
Predictive and Semantic Layout Estimation for Robotic Applications in Manhattan Worlds
2018
Overview
This paper describes an approach to automatically extracting floor plans from the kinds of incomplete measurements that could be acquired by an autonomous mobile robot. The approach proceeds by reasoning about extended structural layout surfaces which are automatically extracted from the available data. The scheme can be run in an online manner to build water tight representations of the environment. The system effectively speculates about room boundaries and free space regions which provides useful guidance to subsequent motion planning systems. Experimental results are presented on multiple data sets.
Publisher
Cornell University Library, arXiv.org
Subject
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