Method
Setting
Code
Translation
Rotation
Runtime
Environment
1
F-SLAM
0.00 %
0.0000 [deg/m]
0.01 s
1 core @ 2.5 Ghz (C/C++)
2
V-LOAM
0.55 %
0.0013 [deg/m]
0.1 s
2 cores @ 2.5 Ghz (C/C++)
J. Zhang and S. Singh: Visual-lidar Odometry and Mapping: Low drift,
Robust, and Fast . IEEE International Conference on Robotics and
Automation(ICRA) 2015.
3
LOAM
0.57 %
0.0013 [deg/m]
0.1 s
2 cores @ 2.5 Ghz (C/C++)
J. Zhang and S. Singh: LOAM: Lidar Odometry and Mapping in Real-
time . Robotics: Science and Systems Conference
(RSS) 2014.
4
IMLS-SLAM++
0.61 %
0.0014 [deg/m]
1.3 s
1 core @ >3.5 Ghz (C/C++)
5
SOFT2
0.65 %
0.0014 [deg/m]
0.1 s
2 cores @ 2.5 Ghz (C/C++)
I. Cvišić, J. Ćesić, I. Marković and I. Petrović: SOFT-SLAM: Computationally Efficient Stereo Visual SLAM for Autonomous UAVs . Journal of Field Robotics 2017.
6
IMLS-SLAM
0.69 %
0.0018 [deg/m]
1.25 s
1 core @ >3.5 Ghz (C/C++)
J. Deschaud: IMLS-SLAM: Scan-to-Model Matching Based
on 3D Data . 2018 IEEE International Conference
on Robotics and Automation (ICRA) 2018.
7
MC2SLAM
0.69 %
0.0016 [deg/m]
0.1 s
4 cores @ 2.5 Ghz (C/C++)
F. Neuhaus, T. Koss, R. Kohnen and D. Paulus: MC2SLAM: Real-Time Inertial Lidar
Odometry
using Two-Scan Motion Compensation . German Conference on Pattern
Recognition 2018.
8
Curvefusion
0.70 %
0.0016 [deg/m]
0.1 s
2 cores @ 2.5 Ghz (C/C++)
9
ESO
0.80 %
0.0026 [deg/m]
0.08 s
4 cores @ 3.0 Ghz (C/C++)
10
sGAN-VO
0.81 %
0.0025 [deg/m]
0.1 s
1 core @ 2.5 Ghz (C/C++)
11
LG-SLAM
0.82 %
0.0020 [deg/m]
0.2 s
4 cores @ 2.5 Ghz (C/C++)
K. Lenac, J. Ćesić, I. Marković and I. Petrović: Exactly sparse delayed state filter on
Lie groups for long-term pose graph SLAM . The International Journal of Robotics
Research 2018.
12
RotRocc+
0.83 %
0.0026 [deg/m]
0.25 s
2 cores @ 2.0 Ghz (C/C++)
M. Buczko and V. Willert: Flow-Decoupled Normalized Reprojection
Error for Visual Odometry . 19th IEEE Intelligent Transportation
Systems Conference (ITSC) 2016. M. Buczko, V. Willert, J. Schwehr and J. Adamy: Self-Validation for Automotive Visual
Odometry . IEEE Intelligent Vehicles Symposium
(IV) 2018. M. Buczko: Automotive Visual Odometry . 2018.
13
LIMO2_GP
code
0.84 %
0.0022 [deg/m]
0.2 s
2 cores @ 2.5 Ghz (C/C++)
J. Graeter, A. Wilczynski and M. Lauer: LIMO: Lidar-Monocular Visual Odometry . arXiv preprint arXiv:1807.07524 2018.
14
UFSF-VLO
0.84 %
0.0023 [deg/m]
0.05 s
4 cores @ 3.0 Ghz (C/C++)
15
CAE-LO
0.86 %
0.0025 [deg/m]
2 s
8 cores @ 3.5 Ghz (Python)
16
GDVO
0.86 %
0.0031 [deg/m]
0.09 s
1 core @ >3.5 Ghz (C/C++)
J. Zhu: Image Gradient-based Joint Direct Visual Odometry for
Stereo Camera . International Joint Conference on Artificial Intelligence,
IJCAI 2017.
17
LIMO2
code
0.86 %
0.0022 [deg/m]
0.2 s
2 cores @ 2.5 Ghz (C/C++)
J. Graeter, A. Wilczynski and M. Lauer: LIMO: Lidar-Monocular Visual Odometry . arXiv preprint arXiv:1807.07524 2018.
18
ICP_LO
0.87 %
0.0036 [deg/m]
0.05 s
1 core @ 2.5 Ghz (C/C++)
19
CPFG-slam
0.87 %
0.0025 [deg/m]
0.03 s
4 cores @ 2.5 Ghz (C/C++)
K. Ji and T. Huiyan Chen: CPFG-SLAM:a robust Simultaneous Localization
and Mapping based on LIDAR in off-road environment . IEEE Intelligent Vehicles Symposium (IV) 2018.
20
CAE- LO 2
0.88 %
0.0029 [deg/m]
2 s
>8 cores @ >3.5 Ghz (Python)
21
MLG-VSLAM+
0.88 %
0.0026 [deg/m]
0.8 s
1 core @ 3.5 Ghz (C/C++)
22
SOFT
0.88 %
0.0022 [deg/m]
0.1 s
2 cores @ 2.5 Ghz (C/C++)
I. Cvišić and I. Petrović: Stereo odometry based on careful feature selection and tracking . European Conference on Mobile Robots (ECMR) 2015.
23
RotRocc
0.88 %
0.0025 [deg/m]
0.3 s
2 cores @ 2.0 Ghz (C/C++)
M. Buczko and V. Willert: Flow-Decoupled Normalized Reprojection Error for Visual Odometry . 19th IEEE Intelligent Transportation Systems Conference (ITSC) 2016.
24
D^3VO
0.88 %
0.0021 [deg/m]
0.1 s
1 core @ 2.5 Ghz (C/C++)
25
scan-to-map PNDT-D2D
0.89 %
0.0030 [deg/m]
0.5 s
4 cores @ >3.5 Ghz (C/C++)
26
DVSO
0.90 %
0.0021 [deg/m]
0.1 s
GPU @ 2.5 Ghz (C/C++)
N. Yang, R. Wang, J. Stueckler and D. Cremers: Deep Virtual Stereo Odometry: Leveraging
Deep Depth Prediction for Monocular Direct Sparse
Odometry . European Conference on Computer
Vision (ECCV) 2018.
27
MLG-VSLAM
0.93 %
0.0028 [deg/m]
0.8 s
1 core @ 3.5 Ghz (C/C++)
28
LIMO
code
0.93 %
0.0026 [deg/m]
0.2 s
2 cores @ 2.5 Ghz (C/C++)
J. Graeter, A. Wilczynski and M. Lauer: LIMO: Lidar-Monocular Visual Odometry . ArXiv e-prints 2018.
29
Stereo DSO
0.93 %
0.0020 [deg/m]
0.1 s
1 core @ 3.4 Ghz (C/C++)
R. Wang, M. Schw\"orer and D. Cremers: Stereo dso: Large-scale direct sparse
visual odometry with stereo cameras . International Conference on Computer
Vision (ICCV), Venice, Italy 2017.
30
MLG-SLAM
0.96 %
0.0034 [deg/m]
0.5 s
1 core @ 3.5 Ghz (C/C++)
31
ROCC
0.98 %
0.0028 [deg/m]
0.3 s
2 cores @ 2.0 Ghz (C/C++)
M. Buczko and V. Willert: How to Distinguish Inliers from Outliers in Visual Odometry for High-speed Automotive Applications . IEEE Intelligent Vehicles Symposium (IV) 2016.
32
S4-SLAM
0.98 %
0.0044 [deg/m]
0.2 s
2 core @ 3.0 Ghz (C/C++)
33
RIS
0.98 %
0.0026 [deg/m]
0.1 s
2 cores @ 2.5 Ghz (C/C++)
34
KF-SLAM
1.00 %
0.0041 [deg/m]
0.1 s
2 cores @ >3.5 Ghz (C/C++)
35
LiOd
1.01 %
0.0025 [deg/m]
1 s
>8 cores @ 2.5 Ghz (C/C++)
36
IsaacElbrus
code
1.02 %
0.0023 [deg/m]
0.0095 s
AGX Jetson Xavier (0.03s Jetson Nano)
37
DLO
1.02 %
0.0040 [deg/m]
0.1s
1 core @ 2.8 Ghz (C/C++)
38
S4OM
1.03 %
0.0053 [deg/m]
0.15 s
1 core @ 2.5 Ghz (C/C++)
39
NDT_LO
1.05 %
0.0043 [deg/m]
0.15s
1 core @ 2.5 Ghz (C/C++)
40
SuMa++
1.06 %
0.0034 [deg/m]
0.1 s
1 core @ 3.5 Ghz (C/C++)
X. Chen, A. Milioto, E. Palazzolo, P. Gigu\`ere, J. Behley and C. Stachniss: SuMa++: Efficient LiDAR-based Semantic
SLAM . IEEE/RSJ International Conference on
Intelligent Robots and Systems (IROS) 2019.
41
cv4xv1-sc
1.09 %
0.0029 [deg/m]
0.145 s
GPU @ 3.5 Ghz (C/C++)
M. Persson, T. Piccini, R. Mester and M. Felsberg: Robust Stereo Visual Odometry from
Monocular Techniques . IEEE Intelligent Vehicles Symposium 2015.
42
VINS-Fusion
code
1.09 %
0.0033 [deg/m]
0.1s
1 core @ 3.0 Ghz (C/C++)
T. Qin, J. Pan, S. Cao and S. Shen: A General Optimization-based Framework
for Local Odometry Estimation with Multiple
Sensors . 2019.
43
FPVO
1.10 %
0.0023 [deg/m]
0.08 s
4 cores @ 2.3 Ghz (C/C++)
44
MonoROCC
1.11 %
0.0028 [deg/m]
1 s
2 cores @ 2.0 Ghz (C/C++)
M. Buczko and V. Willert: Monocular Outlier Detection for Visual Odometry . IEEE Intelligent Vehicles Symposium (IV) 2017.
45
ISRI_CVH
1.12 %
0.0029 [deg/m]
0.1 s
1 core @ 2.5 Ghz (C/C++)
46
ISRI_VO
1.13 %
0.0030 [deg/m]
0.1 s
1 core @ 2.5 Ghz (C/C++)
47
DEMO
1.14 %
0.0049 [deg/m]
0.1 s
2 cores @ 2.5 Ghz (C/C++)
J. Zhang, M. Kaess and S. Singh: Real-time Depth Enhanced Monocular Odometry . IEEE/RSJ International Conference on
Intelligent Robots and Systems (IROS) 2014.
48
ORB-SLAM2
code
1.15 %
0.0027 [deg/m]
0.06 s
2 cores @ >3.5 Ghz (C/C++)
R. Mur-Artal and J. Tard\'os: ORB-SLAM2: an Open-Source
SLAM System for Monocular, Stereo and
RGB-D Cameras . IEEE Transactions on Robotics 2017.
49
ElbrusFast
1.15 %
0.0032 [deg/m]
0.018 s
1.5 cores @ 3.3 Ghz (C/C++)
D. Slepichev, M. Smirnov, E. Vendrovsky and S. Volodarskiy: Realtime Stereo Visual Odometry . .
50
NOTF
1.17 %
0.0035 [deg/m]
0.45 s
1 core @ 3.0 Ghz (C/C++)
J. Deigmoeller and J. Eggert: Stereo Visual Odometry without Temporal Filtering . German Conference on Pattern Recognition (GCPR) 2016.
51
FSMVO
1.18 %
0.0022 [deg/m]
0.1 s
1 core @ 2.5 Ghz (C/C++)
52
S-PTAM
code
1.19 %
0.0025 [deg/m]
0.03 s
4 cores @ 3.0 Ghz (C/C++)
T. Pire, T. Fischer, G. Castro, P. De Crist\'oforis, J. Civera and J. Jacobo Berlles: S-PTAM: Stereo Parallel
Tracking and Mapping . Robotics and Autonomous
Systems (RAS) 2017. T. Pire, T. Fischer, J. Civera, P. Crist\'{o}foris and J. Jacobo-Berlles: Stereo parallel tracking and
mapping for robot localization . IROS 2015.
53
S-LSD-SLAM
code
1.20 %
0.0033 [deg/m]
0.07 s
1 core @ 3.5 Ghz (C/C++)
J. Engel, J. St\"uckler and D. Cremers: Large-Scale Direct SLAM with Stereo Cameras . Int.~Conf.~on Intelligent Robot Systems (IROS) 2015.
54
VoBa
1.22 %
0.0029 [deg/m]
0.1 s
1 core @ 2.0 Ghz (C/C++)
J. Tardif, M. George, M. Laverne, A. Kelly and A. Stentz: A new approach to vision-aided inertial navigation . 2010 IEEE/RSJ International Conference on
Intelligent Robots and
Systems, October 18-22, 2010, Taipei, Taiwan 2010.
55
STEAM-L WNOJ
1.22 %
0.0058 [deg/m]
0.2 s
1 core @ 2.5 Ghz (C/C++)
T. Tang, D. Yoon and T. Barfoot: A White-Noise-On-Jerk Motion Prior for
Continuous-Time Trajectory Estimation on SE (3) . arXiv preprint arXiv:1809.06518 2018.
56
LiViOdo
1.22 %
0.0042 [deg/m]
0.5 s
1 core @ 2.5 Ghz (C/C++)
J. Graeter, A. Wilczynski and M. Lauer: LIMO: Lidar-Monocular Visual Odometry . ArXiv e-prints 2018.
57
SLUP
1.25 %
0.0041 [deg/m]
0.17 s
4 cores @ 3.3 Ghz (C/C++)
X. Qu, B. Soheilian and N. Paparoditis: Landmark based localization in urban
environment . ISPRS Journal of Photogrammetry and
Remote Sensing 2017.
58
STEAM-L
1.26 %
0.0061 [deg/m]
0.2 s
1 core @ 2.5 Ghz (C/C++)
T. Tang, D. Yoon, F. Pomerleau and T. Barfoot: Learning a Bias Correction for Lidar-
only Motion Estimation . 15th Conference on Computer and Robot
Vision (CRV) 2018.
59
FRVO
1.26 %
0.0038 [deg/m]
0.03 s
1 core @ 3.5 Ghz (C/C++)
W. Meiqing, L. Siew-Kei and S. Thambipillai: A Framework for Fast and Robust Visual Odometry . IEEE Transaction on Intelligent Transportation Systems 2017.
60
RTAB-Map
code
1.26 %
0.0026 [deg/m]
0.1 s
1 core @ 2.5 Ghz (C/C++)
M. Labb\'e and F. Michaud: RTAB-Map as an open-source lidar and visual simultaneous localization and mapping library for large-scale and long-term online operation . Journal of Field Robotics 2019.
61
ORBVB
code
1.26 %
0.0029 [deg/m]
0.06 s
2 cores @ >3.5 Ghz (C/C++)
62
A-LOAM
code
1.26 %
0.0034 [deg/m]
0.1 s
1 core @ 2.5 Ghz (C/C++)
63
MIGP
1.28 %
0.0022 [deg/m]
0.2 s
2 cores @ 2.5 Ghz (C/C++)
64
CyberSLAM
1.28 %
0.0040 [deg/m]
0.07 s
1 core @ 2.5 Ghz (C/C++)
65
MFI
1.30 %
0.0030 [deg/m]
0.1 s
1 core @ 2.2 Ghz (C/C++)
H. Badino, A. Yamamoto and T. Kanade: Visual Odometry by Multi-frame Feature Integration . First International Workshop on Computer Vision for Autonomous Driving at ICCV 2013.
66
FDTAM
1.31 %
0.0023 [deg/m]
0.03 s
4 cores @ 2.5 Ghz (C/C++)
67
G-LOAM
1.36 %
0.0041 [deg/m]
0.1 s
1 core @ 2.5 Ghz (C/C++)
68
TLBBA
1.36 %
0.0038 [deg/m]
0.1 s
1 Core @2.8GHz (C/C++)
W. Lu, Z. Xiang and J. Liu: High-performance visual odometry with two-
stage local binocular BA and GPU . Intelligent Vehicles Symposium (IV),
2013 IEEE 2013.
69
2FO-CC
code
1.37 %
0.0035 [deg/m]
0.1 s
1 core @ 3.0 Ghz (C/C++)
I. Krešo and S. Šegvić: Improving the Egomotion Estimation by
Correcting the Calibration Bias . VISAPP 2015.
70
SALO
1.37 %
0.0051 [deg/m]
0.6 s
1 core @ 2.5 Ghz (C/C++)
D. Kovalenko, M. Korobkin and A. Minin: Sensor Aware Lidar Odometry . 2019 European Conference on Mobile Robots (ECMR) 2019.
71
SuMa
1.39 %
0.0034 [deg/m]
0.1 s
1 core @ 3.5 Ghz (C/C++)
J. Behley and C. Stachniss: Efficient Surfel-Based SLAM using 3D Laser Range Data in Urban Environments . Robotics: Science and Systems (RSS) 2018.
72
ProSLAM
code
1.39 %
0.0035 [deg/m]
0.02 s
1 core @ 3.0 Ghz (C/C++)
D. Schlegel, M. Colosi and G. Grisetti: ProSLAM: Graph SLAM from a
Programmer's Perspective . ArXiv e-prints 2017.
73
JFBVO
1.43 %
0.0038 [deg/m]
0.05 s
1 core @ 3.4 Ghz (C/C++)
74
DQV-SLAM
1.47 %
0.0051 [deg/m]
0.2 s
2 cores @ 2.5 Ghz (C/C++)
S. Bultmann, K. Li and U. Hanebeck: Stereo Visual SLAM Based on Unscented Dual Quaternion Filtering . Proceedings of the 22nd International Conference on Information Fusion (Fusion 2019) 2019.
75
StereoSFM
code
1.51 %
0.0042 [deg/m]
0.02 s
2 cores @ 2.5 Ghz (C/C++)
H. Badino and T. Kanade: A Head-Wearable Short-Baseline Stereo System for the Simultaneous Estimation of Structure and Motion . IAPR Conference on Machine Vision Application 2011.
76
ANM
1.51 %
0.0070 [deg/m]
0.1 s
1 core @ 2.5 Ghz (C/C++)
77
Leso
1.57 %
0.0050 [deg/m]
0.05 s
1 core @ 2.5 Ghz (C/C++)
78
SSLAM
code
1.57 %
0.0044 [deg/m]
0.5 s
8 cores @ 3.5 Ghz (C/C++)
F. Bellavia, M. Fanfani, F. Pazzaglia and C. Colombo: Robust Selective Stereo SLAM without Loop Closure and Bundle Adjustment . ICIAP 2013 2013. F. Bellavia, M. Fanfani and C. Colombo: Selective visual odometry for accurate AUV localization . Autonomous Robots 2015. M. Fanfani, F. Bellavia and C. Colombo: Accurate Keyframe Selection and Keypoint Tracking for Robust Visual Odometry . Machine Vision and Applications 2016.
79
RLCLM
1.59 %
0.0053 [deg/m]
0.08 s
8 core @ 3.4 Ghz (C/C++)
80
ICP SLAM
1.61 %
0.0061 [deg/m]
0.1 s
1 core @ >3.5 Ghz (C/C++)
81
VOLDOR
1.65 %
0.0050 [deg/m]
0.1 s
GPU
82
ORB-SLAM2 Stereo
1.70 %
0.0028 [deg/m]
0.01 s
1 core @ 2.5 Ghz (C/C++)
83
test
1.72 %
0.0054 [deg/m]
0.1 s
test
84
ORB-SLAM2 S(w/oLC)
1.74 %
0.0030 [deg/m]
0.01 s
1 core @ 2.5 Ghz (C/C++)
85
ORB-SLAM2 Stereo (w/
1.74 %
0.0030 [deg/m]
0.01 s
1 core @ 2.5 Ghz (C/C++)
86
vd
1.75 %
0.0056 [deg/m]
1 s
1 core @ 2.5 Ghz (C/C++)
87
eVO
1.76 %
0.0036 [deg/m]
0.05 s
2 cores @ 2.0 Ghz (C/C++)
M. Sanfourche, V. Vittori and G. Besnerais: eVO: A realtime embedded stereo odometry for MAV applications . IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2013.
88
Stereo DWO
code
1.76 %
0.0026 [deg/m]
0.1 s
4 cores @ 2.5 Ghz (C/C++)
J. Huai, C. Toth and D. Grejner-Brzezinska: Stereo-inertial odometry using nonlinear optimization . Proceedings of the 27th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2015) 2015.
89
BVO
1.76 %
0.0036 [deg/m]
0.1 s
1 core @ 2.5GHz (Python)
F. Pereira, J. Luft, G. Ilha, A. Sofiatti and A. Susin: Backward Motion for Estimation Enhancement in Sparse Visual Odometry . 2017 Workshop of Computer Vision (WVC) 2017.
90
D6DVO
2.04 %
0.0051 [deg/m]
0.03 s
1 core @ 2.5 Ghz (C/C++)
A. Comport, E. Malis and P. Rives: Accurate Quadrifocal Tracking for Robust 3D Visual Odometry . ICRA 2007. M. Meilland, A. Comport and P. Rives: Dense visual mapping of large scale environments for real-time localisation . ICRA 2011.
91
PMO / PbT-M2
2.05 %
0.0051 [deg/m]
1 s
1 core @ 2.5 Ghz (Python + C/C++)
N. Fanani, A. Stuerck, M. Ochs, H. Bradler and R. Mester: Predictive monocular odometry (PMO): What is possible without RANSAC and multiframe bundle adjustment? . Image and Vision Computing 2017.
92
GFM
code
2.12 %
0.0056 [deg/m]
0.03 s
2 cores @ 1.5 Ghz (C/C++)
Y. Zhao and P. Vela: Good Feature Matching: Towards Accurate,
Robust VO/VSLAM with Low Latency . submitted to IEEE Transactions on
Robotics 2019.
93
SSLAM-HR
code
2.14 %
0.0059 [deg/m]
0.5 s
8 cores @ 3.5 Ghz (C/C++)
F. Bellavia, M. Fanfani, F. Pazzaglia and C. Colombo: Robust Selective Stereo SLAM without Loop Closure and Bundle Adjustment . ICIAP 2013 2013. F. Bellavia, M. Fanfani and C. Colombo: Selective visual odometry for accurate AUV localization . Autonomous Robots 2015. M. Fanfani, F. Bellavia and C. Colombo: Accurate Keyframe Selection and Keypoint Tracking for Robust Visual Odometry . Machine Vision and Applications 2016.
94
FTMVO
2.24 %
0.0049 [deg/m]
0.11 s
1 core @ 2.5 Ghz (C/C++)
H. Mirabdollah and B. Mertsching: Fast Techniques for Monocular Visual
Odometry . Proceeding of 37th
German Conference on Pattern Recognition (GCPR)
2015 .
95
PbT-M1
2.38 %
0.0053 [deg/m]
1 s
1 core @ 2.5 Ghz (Python + C/C++)
N. Fanani, M. Ochs, H. Bradler and R. Mester: Keypoint trajectory estimation using propagation based tracking . Intelligent Vehicles Symposium (IV) 2016. N. Fanani, A. Stuerck, M. Barnada and R. Mester: Multimodal scale estimation for monocular visual odometry . Intelligent Vehicles Symposium (IV) 2017.
96
VISO2-S
code
2.44 %
0.0114 [deg/m]
0.05 s
1 core @ 2.5 Ghz (C/C++)
A. Geiger, J. Ziegler and C. Stiller: StereoScan: Dense 3d Reconstruction in
Real-time . IV 2011.
97
MLM-SFM
2.54 %
0.0057 [deg/m]
0.03 s
5 cores @ 2.5 Ghz (C/C++)
S. Song and M. Chandraker: Robust Scale Estimation in Real-Time
Monocular SFM for Autonomous Driving . CVPR 2014. S. Song, M. Chandraker and C. Guest: Parallel, Real-time Monocular Visual
Odometry . ICRA 2013.
98
GT_VO3pt
2.54 %
0.0078 [deg/m]
1.26 s
1 core @ 2.5 Ghz (C/C++)
C. Beall, B. Lawrence, V. Ila and F. Dellaert: 3D reconstruction of underwater structures . IROS 2010.
99
PeNet
2.54 %
0.0089 [deg/m]
0.1 s
GPU @ 2.0 Ghz (C/C++)
100
RMCPE+GP
2.55 %
0.0086 [deg/m]
0.39 s
1 core @ 2.5 Ghz (C/C++)
M. Mirabdollah and B. Mertsching: On the Second Order Statistics of
Essential Matrix Elements . Proceeding of 36th German Conference
on Pattern Recognition 2014.
101
LKNMVO
2.66 %
0.0079 [deg/m]
0.3 s
GPU @ 3.0 Ghz (C/C++)
102
VO3pt
2.69 %
0.0068 [deg/m]
0.56 s
1 core @ 2.0 Ghz (C/C++)
P. Alcantarilla: Vision Based Localization: From Humanoid Robots to Visually Impaired People . 2011. P. Alcantarilla, J. Yebes, J. Almazán and L. Bergasa: On Combining Visual SLAM and Dense Scene Flow to Increase the Robustness of Localization and Mapping in Dynamic Environments . ICRA 2012.
103
TGVO
2.94 %
0.0077 [deg/m]
0.06 s
1 core @ 2.5 Ghz (C/C++)
B. Kitt, A. Geiger and H. Lategahn: Visual Odometry based on Stereo Image Sequences
with RANSAC-based Outlier Rejection Scheme . IV 2010.
104
OISEL
3.02 %
0.0132 [deg/m]
0.2 s
1 core @ 2.5 Ghz (C/C++)
105
VO3ptLBA
3.13 %
0.0104 [deg/m]
0.57 s
1 core @ 2.0 Ghz (C/C++)
P. Alcantarilla: Vision Based Localization: From Humanoid Robots to Visually Impaired People . 2011. P. Alcantarilla, J. Yebes, J. Almazán and L. Bergasa: On Combining Visual SLAM and Dense Scene Flow to Increase the Robustness of Localization and Mapping in Dynamic Environments . ICRA 2012.
106
PLSVO
3.26 %
0.0095 [deg/m]
0.20 s
2 cores @ 2.5 Ghz (C/C++)
R. Gomez-Ojeda and J. Gonzalez- Jimenez: Robust Stereo Visual Odometry through a
Probabilistic Combination of Points and Line
Segments . Robotics and Automation (ICRA), 2016
IEEE International Conference on 2016.
107
NO_OISEL
3.45 %
0.0144 [deg/m]
0.1 s
1 core @ 2.5 Ghz (C/C++)
108
BLF
3.49 %
0.0128 [deg/m]
0.7 s
1 core @ 2.5 Ghz (C/C++)
M. Velas, M. Spanel, M. Hradis and A. Herout: CNN for IMU Assisted Odometry
Estimation using Velodyne LiDAR . ArXiv e-prints 2017.
109
CFORB
3.73 %
0.0107 [deg/m]
0.9 s
8 cores @ 3.0 Ghz (C/C++)
D. Mankowitz and E. Rivlin: CFORB: Circular FREAK-ORB Visual Odometry . arXiv preprint arXiv:1506.05257 2015.
110
VOFS
3.94 %
0.0099 [deg/m]
0.51 s
1 core @ 2.0 Ghz (C/C++)
M. Kaess, K. Ni and F. Dellaert: Flow separation for fast and robust stereo odometry . ICRA 2009. P. Alcantarilla, L. Bergasa and F. Dellaert: Visual Odometry priors for robust EKF-SLAM . ICRA 2010.
111
UnDFVO
4.03 %
0.0096 [deg/m]
1 s
1 core @ 2.5 Ghz (Python)
112
VOFSLBA
4.17 %
0.0112 [deg/m]
0.52 s
1 core @ 2.0 Ghz (C/C++)
M. Kaess, K. Ni and F. Dellaert: Flow separation for fast and robust stereo odometry . ICRA 2009. P. Alcantarilla, L. Bergasa and F. Dellaert: Visual Odometry priors for robust EKF-SLAM . ICRA 2010.
113
CUDA-EgoMotion
4.36 %
0.0052 [deg/m]
.001 s
GPU @ 2.5 Ghz (Matlab)
A. Aguilar-González, M. Arias- Estrada, F. Berry and J. Osuna-Coutiño: The Fastest Visual Ego-motion Algorithm
in the West . Microprocessors and Microsystems 2019.
114
BCC
4.59 %
0.0175 [deg/m]
1 s
1 core @ 2.5 Ghz (C/C++)
M. Velas, M. Spanel, M. Hradis and A. Herout: CNN for IMU Assisted Odometry
Estimation using Velodyne LiDAR . ArXiv e-prints 2017.
115
EB3DTE+RJMCM
5.45 %
0.0274 [deg/m]
1 s
1 core @ 2.5 Ghz (Matlab)
Z. Boukhers, K. Shirahama and M. Grzegorzek: Example-based 3D Trajectory
Extraction of Objects from 2D Videos . Circuits and Systems for Videos
Technology (TCSVT), IEEE Transaction on 2017. Z. Boukhers, K. Shirahama and M. Grzegorzek: Less restrictive camera odometry estimation
from monocular camera . Multimedia Tools and Applications 2017.
116
LVT
5.80 %
0.0065 [deg/m]
0.02 s
2 cores @ 2.5 Ghz (C/C++)
117
Self-M
code
6.42 %
0.0109 [deg/m]
0.1 s
1 core @ 2.5 Ghz (Python + C/C++)
118
FDVLO
7.10 %
0.0215 [deg/m]
0.15 s
GPU @ 2.5 Ghz (Python)
119
Long-term SfM
7.40 %
0.0142 [deg/m]
0.1 s
1 core @ 2.5 Ghz (C/C++)
120
VISO2-M + GP
7.46 %
0.0245 [deg/m]
0.15 s
1 core @ 2.5 Ghz (C/C++)
A. Geiger, J. Ziegler and C. Stiller: StereoScan: Dense 3d Reconstruction in
Real-time . IV 2011. S. Song and M. Chandraker: Robust Scale Estimation in Real-Time
Monocular SFM for Autonomous Driving . CVPR 2014.
121
unscene
8.68 %
0.0227 [deg/m]
0.1 s
GPU @ 2.5 Ghz (C/C++)
122
BLO
9.21 %
0.0163 [deg/m]
0.1 s
1 core @ 2.5 Ghz (C/C++)
M. Velas, M. Spanel, M. Hradis and A. Herout: CNN for IMU Assisted Odometry
Estimation using Velodyne LiDAR . ArXiv e-prints 2017.
123
PJ-test
11.79 %
0.0069 [deg/m]
0.1 s
1 core @ 2.5 Ghz (C/C++)
124
VISO2-M
code
11.94 %
0.0234 [deg/m]
0.1 s
1 core @ 2.5 Ghz (C/C++)
A. Geiger, J. Ziegler and C. Stiller: StereoScan: Dense 3d Reconstruction in
Real-time . IV 2011.
125
MonoDepth2
code
12.59 %
0.0312 [deg/m]
1 s
1 core @ 2.5 Ghz (C/C++)
126
MTL
14.95 %
0.0115 [deg/m]
0.1 s
1 core @ 2.5 Ghz (C/C++)
127
CC
code
16.06 %
0.0320 [deg/m]
0.1 s
1 core @ 2.5 Ghz (C/C++)
128
OABA
20.95 %
0.0135 [deg/m]
0.5 s
1 core @ 3.5 Ghz (C/C++)
D. Frost, O. Kähler and D. Murray: Object-Aware Bundle Adjustment for
Correcting Monocular Scale Drift . Proceedings of the International
Conference on Robotics and Automation (ICRA) 2012.
129
3DC-VO
21.00 %
0.0394 [deg/m]
0.04 s
1 core @ 2.5 Ghz (Python + C/C++)
130
DeepVO
24.55 %
0.0489 [deg/m]
1 s
1 core @ 2.5 Ghz (Python)