Method

Using a General Panoptic Segmentation for a Robust Semantic Landmark SLAM [GenPA-SLAM]
[Anonymous Submission]

Submitted on 28 Feb. 2022 02:57 by
[Anonymous Submission]

Running time:0,1 s
Environment:GPU @ 2.5 Ghz (C/C++)

Method Description:
Semantic Landmarks are extracted with the usage of a general panoptic segmentation. The back-end consists of a graph.
Parameters:
\nr_of_vertices=100
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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