Method

Direct Sparse Visual–Lidar Odometry and Mapping [la] [DSV-LOAM]
[Anonymous Submission]

Submitted on 28 Nov. 2020 04:27 by
[Anonymous Submission]

Running time:0.1 s
Environment:4 cores @ 3.0 Ghz (C/C++)

Method Description:
In this work we propose a direct visual-lidar pose
estimation system. The visual odometry of our
system applies the direct method, which does not
use the depth association and thus retains the
original precision of point cloud data from lidar.
Parameters:
output frequency of visual odometry: 10Hz
output frequency of lidar odometry: 3Hz
Latex Bibtex:

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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