Imperial College London
Alternate

ProfessorAndrewDavison

Faculty of Engineering, Department of Computing

Professor of Robot Vision
 
 
 
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Contact

 

+44 (0)20 7594 8316a.davison Website

 
 
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Assistant

 

Ms Lucy Atthis +44 (0)20 7594 8259

 
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Location

 

303William Penney LaboratorySouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Lukierski:2017:10.1109/ICRA.2017.7989747,
author = {Lukierski, R and Leutenegger, S and Davison, AJ},
doi = {10.1109/ICRA.2017.7989747},
publisher = {IEEE},
title = {Room layout estimation from rapid omnidirectional exploration},
url = {http://dx.doi.org/10.1109/ICRA.2017.7989747},
year = {2017}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - A new generation of practical, low-cost indoor robots is now using wide-angle cameras to aid navigation, but usually this is limited to position estimation via sparse feature-based SLAM. Such robots usually have little global sense of the dimensions, demarcation or identities of the rooms they are in, information which would be very useful to enable behaviour with much more high level intelligence. In this paper we show that we can augment an omni-directional SLAM pipeline with straightforward dense stereo estimation and simple and robust room model fitting to obtain rapid and reliable estimation of the global shape of typical rooms from short robot motions. We have tested our method extensively in real homes, offices and on synthetic data. We also give examples of how our method can extend to making composite maps of larger rooms, and detecting room transitions.
AU  - Lukierski,R
AU  - Leutenegger,S
AU  - Davison,AJ
DO  - 10.1109/ICRA.2017.7989747
PB  - IEEE
PY  - 2017///
TI  - Room layout estimation from rapid omnidirectional exploration
UR  - http://dx.doi.org/10.1109/ICRA.2017.7989747
UR  - http://hdl.handle.net/10044/1/49081
ER  -
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