Method

BUT-LOAM-online [BLO]


Submitted on 25 Aug. 2017 14:29 by
Martin Veľas (Robo@FIT, BUT)

Running time:0.1 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
LOAM
Parameters:
online
Latex Bibtex:
@ARTICLE{2017arXiv171206352V,
author = {{Velas}, M. and {Spanel}, M. and
{Hradis}, M. and {Herout}, A.
},
title = "{CNN for IMU Assisted Odometry
Estimation using Velodyne LiDAR}",
journal = {ArXiv e-prints},
archivePrefix = "arXiv",
eprint = {1712.06352},
primaryClass = "cs.RO",
keywords = {Computer Science - Robotics},
year = 2017,
month = dec,
adsurl =
{http://adsabs.harvard.edu/abs/2017arXiv171206352
V},
adsnote = {Provided by the SAO/NASA
Astrophysics Data System}
}

Detailed Results

From all test sequences (sequences 11-21), our benchmark computes translational and rotational errors for all possible subsequences of length (5,10,50,100,150,...,400) meters. Our evaluation ranks methods according to the average of those values, where errors are measured in percent (for translation) and in degrees per meter (for rotation). Details for different trajectory lengths and driving speeds can be found in the plots underneath. Furthermore, the first 5 test trajectories and error plots are shown below.

Test Set Average


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Sequence 11


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Sequence 12


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Sequence 13


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Sequence 14


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Sequence 15


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