Method

[la] STEAM-Lidar [STEAM-L]


Submitted on 10 Sep. 2018 18:43 by
Tim Tang (University of Toronto Institute for Aerospace Studies)

Running time:0.2 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
Lidar odometry with STEAM.
Parameters:
As specified in paper
Latex Bibtex:
@article{tang2018learning,
title={{Learning a Bias Correction for Lidar-
only Motion Estimation}},
author={Tang, Tim Y and Yoon, David J and
Pomerleau, Fran{\c{c}}ois and Barfoot, Timothy
D},
journal={15th Conference on Computer and Robot
Vision (CRV)},
year={2018}
}

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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