Method

LIDAR SLAM using ORB Features from Rasterized Images of 3D LIDAR Point Cloud[la][st][lc] [OFL-SLAM]
[Anonymous Submission]

Submitted on 8 Jan. 2021 06:58 by
[Anonymous Submission]

Running time:0.1 s
Environment:4 cores @ 2.5 Ghz (C/C++)

Method Description:
The method is based on the rasterization of the 3D
point cloud using a pinhole camera model and then
ORB features are extracted from these images.
These features are used to estimate pose and
detect loop closure.
Parameters:
Image size = 750x750
Camera translation = [−25; −25; 70]
ORB fastThreshold = 20
ORB scaleFactor = 12
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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