The KITTI Vision Benchmark Suite

Method

ORB-SLAM2 [st][lc] [ORB-SLAM2]
https://github.com/raulmur/ORB_SLAM2

Submitted on 26 Jan. 2016 12:14 by
Raul Mur-Artal (University of Zaragoza)

Running time:		0.06 s
Environment:		2 cores @ >3.5 Ghz (C/C++)

Method Description:

Stereo version of ORB-SLAM. The system
includes Place Recognition for Loop
Detection and Global Relocalisation. Loops
are optimized with 6DoF pose graph and
full bundle adjustment afterwards.

Parameters:

ORBextractor.nFeatures: 2000
ORBextractor.scaleFactor: 1.2
ORBextractor.nLevels: 8
ORBextractor.iniThFAST: 12
ORBextractor.minThFAST: 7

Latex Bibtex:

@article{murORB2,
title={{ORB-SLAM2}: an Open-Source
{SLAM} System for Monocular, Stereo and
{RGB-D} Cameras},
author={Mur-Artal, Ra\'ul and Tard\'os,
Juan D.},
journal={IEEE Transactions on Robotics},
volume={33},
number={5},
pages={1255--1262},
doi = {10.1109/TRO.2017.2705103},
year={2017}
}

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.