Method

Lidar Odometry and Mapping [la] [LOAM]


Submitted on 24 Jul. 2017 01:55 by
Ji Zhang (Carnegie Mellon University)

Running time:0.1 s
Environment:2 cores @ 2.5 Ghz (C/C++)

Method Description:
Scan matching based odometry using Velodyne data

Research videos are available at:
www.youtube.com/channel/UCEEqrCpT8lnp0q1HBzS3rtQ

Latest, improved method is commercialized by:
www.kaarta.com
Parameters:
Point to line/plane scan matching
Latex Bibtex:
@inproceedings{Zhang2014RSS,
title = {{LOAM}: Lidar Odometry and Mapping in
Real-time},
author = {Ji Zhang and Sanjiv Singh},
booktitle = {Robotics: Science and Systems
Conference (RSS)},
month = {July},
year={2014},
address={Berkeley, CA}
}

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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