Method

Combining LIDAR scan matching with Stereo Visual Odometry using Curvefusion[st][la] [Curvefusion]


Submitted on 20 Oct. 2019 07:18 by
Shitong Du (Harbin Engineering University)

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

Method Description:
A deformation-based multi-sensor fusion
method, namely curvefusion is applied to combine
LiDAR scan matching with Stereo Visual Odometry.
our method regards these two trajectories as two
curves which represent the same shape. The fusion
optimization
problem of two trajectories is considered as the
problem of deforming one curved shape to the other
in a deformation space. The proposed fusion
method does not rely on a sensor model. As long as
the trajectories of the sensors to be fused are
given, we obtain an optimized fusion trajectory,
which greatly improves the computational
efficiency compared with filter-based on fusion
method.
Parameters:
n=50
\lambda=49
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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