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Incremental probabilistic geometry estimation for robot scene understanding

Louis-Kenzo Cahier, Tetsuya Ogata, Hiroshi G. Okuno

Year
2012
Citations
2

Abstract

Our goal is to give mobile robots a rich representation of their environment as fast as possible. Current mapping methods such as SLAM are often sparse, and scene reconstruction methods using tilting laser scanners are relatively slow. In this paper, we outline a new method for iterative construction of a geometric mesh using streaming time-of-flight range data. Our results show that our algorithm can produce a stable representation after 6 frames, with higher accuracy than raw time-of-flight data.

Keywords

Computer visionComputer scienceProbabilistic logicMobile robotRepresentation (politics)Artificial intelligenceRange (aeronautics)Simultaneous localization and mappingRobotIterative method

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