ICRA 2012 Paper Abstract


Paper WeD310.1

Cahier, Louis-Kenzo (Ky˘to University), Ogata, Tetsuya (Kyoto University), Okuno, Hiroshi G. (Kyoto University)

Incremental Probabilistic Geometry Estimation for Robot Scene Understanding

Scheduled for presentation during the Interactive Session "Interactive Session WeD-3" (WeD310), Wednesday, May 16, 2012, 17:30−18:00, Ballroom D

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on June 19, 2018

Keywords Mapping, Range Sensing


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.



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