Kimera,
2019
WWW Link.
Code, SLAM.
1910
Kimera is implemented in C++, is ROS-compatible, and runs on CPU. It
only uses a camera and an IMU.
The code performs real-time visual-inertial SLAM (including robust
loop closure detection and outlier removal) and builds a semantically
labeled 3D mesh.
Kimera is a hybrid creature and includes state-of-the-art algorithms
for visual-inertial odometry, robust pose graph optimization,
real-time mesh reconstruction, and 3D semantic segmentation.
Ho, K.L.[Kin Leong],
Newman, P.[Paul],
Detecting Loop Closure with Scene Sequences,
IJCV(74), No. 3, September 2007, pp. 261-286.
Springer DOI
0707
Assert that the robot has returned to the original location.
BibRef
Eade, E.D.[Ethan D.],
Drummond, T.W.[Tom W.],
Edge landmarks in monocular SLAM,
IVC(27), No. 5, 2 April 2009, pp. 588-596.
Elsevier DOI
0904
BibRef
Earlier:
BMVC06(I:7).
PDF File.
0609
BibRef
And:
Unified Loop Closing and Recovery for Real Time Monocular SLAM,
BMVC08(xx-yy).
PDF File.
0809
BibRef
Earlier:
Monocular SLAM as a Graph of Coalesced Observations,
ICCV07(1-8).
IEEE DOI
0710
BibRef
Earlier:
Scalable Monocular SLAM,
CVPR06(I: 469-476).
IEEE DOI
0606
SLAM; Monocular SLAM; Structure and motion; Edges; Landmarks; Particle
filter; Edgelet; Partial initialization; Inverse depth; Data
association; Simultaneous localization and mapping; Edge detection;
Monocular vision
Simultaneous Location and Map
BibRef
Avraham, G.,
Zuo, Y.,
Dharmasiri, T.,
Drummond, T.W.[Tom W.],
EMPNet: Neural Localisation and Mapping Using Embedded Memory Points,
ICCV19(8119-8128)
IEEE DOI
2004
convolutional neural nets, image recognition,
learning (artificial intelligence), active vision dataset,
Navigation
BibRef
Williams, B.[Brian],
Klein, G.[Georg],
Reid, I.D.[Ian D.],
Automatic Relocalization and Loop Closing for Real-Time Monocular SLAM,
PAMI(33), No. 9, September 2011, pp. 1699-1712.
IEEE DOI
1109
BibRef
Earlier:
Real-Time SLAM Relocalisation,
ICCV07(1-8).
IEEE DOI
0710
Turn cheap cameras into pose sensors for robotics and augmented reality.
BibRef
Weise, T.[Thibaut],
Wismer, T.[Thomas],
Leibe, B.[Bastian],
Van Gool, L.J.[Luc J.],
Online loop closure for real-time interactive 3D scanning,
CVIU(115), No. 5, May 2011, pp. 635-648.
Elsevier DOI
1103
BibRef
Earlier:
In-hand scanning with online loop closure,
3DIM09(1630-1637).
IEEE DOI
0910
3D modeling; 3D scanning; Registration; Integration; Loop closure
Freely turn object in front of 3D scanner.
BibRef
Meidow, J.[Jochen],
Effcient Multiple Loop Adjustment for Computer Vision Tasks,
PFG(2012), No. 5, 2012, pp. 501-510.
WWW Link.
1211
BibRef
And:
Efficient Video Mosaicking by Multiple Loop Closing,
PIA11(1-12).
Springer DOI
1110
BibRef
Ravari, A.N.,
Taghirad, H.D.,
Loop Closure Detection by Algorithmic Information Theory:
Implemented on Range and Camera Image Data,
Cyber(44), No. 10, October 2014, pp. 1938-1949.
IEEE DOI
1410
cameras
BibRef
Erhan, C.[Can],
Sariyanidi, E.[Evangelos],
Sencan, O.[Onur],
Temeltas, H.[Hakan],
Patterns of approximated localised moments for visual loop closure
detection,
IET-CV(11), No. 3, April 2017, pp. 237-245.
DOI Link
1704
Back to the same location.
BibRef
Esfahani, M.A.[Mahdi Abolfazli],
Wu, K.Y.[Ke-Yu],
Yuan, S.H.[Sheng-Hai],
Wang, H.[Han],
DeepDSAIR: Deep 6-DOF camera relocalization using deblurred
semantic-aware image representation for large-scale outdoor
environments,
IVC(89), 2019, pp. 120-130.
Elsevier DOI
1909
Deep Neural Network (DNN), Convolutional Neural Network (CNN),
Camera relocalization, Pose regression, Loop closure, Visual odometry
BibRef
Guclu, O.[Oguzhan],
Can, A.B.[Ahmet Burak],
k-SLAM: A fast RGB-D SLAM approach for large indoor environments,
CVIU(184), 2019, pp. 31-44.
Elsevier DOI
1906
BibRef
Earlier:
A Comparison of Feature Detectors and Descriptors in RGB-D SLAM Methods,
ICIAR15(297-305).
Springer DOI
1507
SLAM, RGB-D, Autocorrelogram, Hierarchical indexing,
Loop closure, Real-time
BibRef
Guclu, O.[Oguzhan],
Can, A.B.[Ahmet Burak],
Integrating global and local image features for enhanced loop closure
detection in RGB-D SLAM systems,
VC(36), No. 6, June 2020, pp. 1271-1290.
WWW Link.
2005
BibRef
Wang, Y.W.[Yu-Wei],
Qiu, Y.Y.[Yuan-Ying],
Cheng, P.T.[Pei-Tao],
Duan, X.C.[Xue-Chao],
Robust Loop Closure Detection Integrating Visual-Spatial-Semantic
Information via Topological Graphs and CNN Features,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Yang, Z.[Zhe],
Pan, Y.[Yun],
Deng, L.[Lei],
Xie, Y.[Yuan],
Huan, R.H.[Ruo-Hong],
PLSAV: Parallel loop searching and verifying for loop closure
detection,
IET-ITS(15), No. 5, 2021, pp. 683-698.
DOI Link
2106
BibRef
Chen, S.B.[Shou-Bin],
Zhou, B.[Baoding],
Jiang, C.H.[Chang-Hui],
Xue, W.X.[Wei-Xing],
Li, Q.Q.[Qing-Quan],
A LiDAR/Visual SLAM Backend with Loop Closure Detection and Graph
Optimization,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link
2107
BibRef
Yuan, Z.[Zhian],
Xu, K.[Ke],
Zhou, X.Y.[Xiao-Yu],
Deng, B.[Bin],
Ma, Y.X.[Yan-Xin],
SVG-Loop: Semantic-Visual-Geometric Information-Based Loop Closure
Detection,
RS(13), No. 17, 2021, pp. xx-yy.
DOI Link
2109
mportant component of visual simultaneous localization and mapping
BibRef
Yu, M.F.[Ming-Fei],
Zhang, L.[Lei],
Wang, W.F.[Wu-Fan],
Huang, H.[Hua],
Loop Closure Detection by Using Global and Local Features With
Photometric and Viewpoint Invariance,
IP(30), 2021, pp. 8873-8885.
IEEE DOI
2111
In SLAM.
Feature extraction, Visualization, Task analysis, Lighting, Shape,
Image color analysis, local feature
BibRef
Karam, S.,
Lehtola, V.,
Vosselman, G.,
Simple loop closing for continuous 6DOF LIDAR&IMU graph SLAM with
planar features for indoor environments,
PandRS(181), 2021, pp. 413-426.
Elsevier DOI
2110
SLAM, Loop closure, Planar features, Indoor, Point clouds,
Mobile mapping, Laser scanner, LIDAR, 6DOF
BibRef
Qin, C.[Cao],
Zhang, Y.Z.[Yun-Zhou],
Liu, Y.D.[Ying-Da],
Lv, G.H.[Guang-Hao],
Semantic loop closure detection based on graph matching in
multi-objects scenes,
JVCIR(76), 2021, pp. 103072.
Elsevier DOI
2104
Loop closure detection, Object detection, Semantic,
Simultaneous localization and mapping (SLAM), Graph matching
BibRef
Zhang, K.N.[Kai-Ning],
Jiang, X.Y.[Xing-Yu],
Ma, J.Y.[Jia-Yi],
Appearance-Based Loop Closure Detection via Locality-Driven Accurate
Motion Field Learning,
ITS(23), No. 3, March 2022, pp. 2350-2365.
IEEE DOI
2203
Feature extraction, Liquid crystal displays, Visualization,
Task analysis, Robots, Simultaneous localization and mapping,
autonomous vehicle
BibRef
Ma, J.Y.[Jia-Yi],
Ye, X.Y.[Xin-Yu],
Zhou, H.[Huabing],
Mei, X.G.[Xiao-Guang],
Fan, F.[Fan],
Loop-Closure Detection Using Local Relative Orientation Matching,
ITS(23), No. 7, July 2022, pp. 7896-7909.
IEEE DOI
2207
Liquid crystal displays, Feature extraction, Visualization,
Task analysis, Neural networks, ASMK
BibRef
Jin, J.[Jie],
Bai, J.[Jiale],
Xu, Y.[Yan],
Huang, J.[Jiani],
Unifying Deep ConvNet and Semantic Edge Features for Loop Closure
Detection,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link
2210
BibRef
Tsintotas, K.A.[Konstantinos A.],
Bampis, L.[Loukas],
Gasteratos, A.[Antonios],
The Revisiting Problem in Simultaneous Localization and Mapping:
A Survey on Visual Loop Closure Detection,
ITS(23), No. 11, November 2022, pp. 19929-19953.
IEEE DOI
2212
Visualization, Robots, Simultaneous localization and mapping,
Robot sensing systems, Task analysis, Feature extraction,
visual-based navigation
BibRef
Memon, A.R.[Azam Rafique],
Liu, Z.[Zhe],
Wang, H.S.[He-Sheng],
Viewpoint-Invariant Loop Closure Detection Using Step-Wise Learning
With Controlling Embeddings of Landmarks,
ITS(23), No. 11, November 2022, pp. 20148-20159.
IEEE DOI
2212
Feature extraction, Liquid crystal displays, Visualization,
Lighting, Training, Deep learning,
step-wise learning
BibRef
Wang, G.[Gang],
Wei, X.M.[Xiao-Meng],
Chen, Y.[Yu],
Zhang, T.Z.[Tong-Zhou],
Hou, M.H.[Ming-Hui],
Liu, Z.[Zhaohan],
A Multi-Channel Descriptor for LiDAR-Based Loop Closure Detection and
Its Application,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Wang, G.[Gang],
Jiang, X.D.[Xu-Dong],
Zhou, W.[Wei],
Chen, Y.[Yu],
Zhang, H.[Hao],
3PCD-TP: A 3D Point Cloud Descriptor for Loop Closure Detection with
Twice Projection,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link
2301
BibRef
Zhang, K.N.[Kai-Ning],
Li, Z.Z.[Zi-Zhuo],
Ma, J.Y.[Jia-Yi],
Loop Closure Detection With Bidirectional Manifold Representation
Consensus,
ITS(24), No. 4, April 2023, pp. 3949-3962.
IEEE DOI
2304
Liquid crystal displays, Feature extraction, Task analysis,
Databases, Navigation, Visualization, Manifolds,
feature matching
BibRef
Chen, Z.H.[Zhi-Hong],
Zhao, J.Q.[Jun-Qiao],
Feng, T.T.[Tian-Tian],
Ye, C.[Chen],
Xiong, L.[Lu],
Robust Loop Closure Selection Based on Inter-Robot and Intra-Robot
Consistency for Multi-Robot Map Fusion,
RS(15), No. 11, 2023, pp. 2796.
DOI Link
2306
BibRef
Wang, S.[Shuai],
Zhang, J.Z.[Jia-Zhong],
Tan, X.J.[Xiao-Jun],
PDLC-LIO: A Precise and Direct SLAM System Toward Large-Scale
Environments With Loop Closures,
ITS(25), No. 1, January 2024, pp. 626-637.
IEEE DOI
2402
Laser radar, Simultaneous localization and mapping, Odometry,
Point cloud compression, Autonomous vehicles, Robustness,
simultaneous localization and mapping
BibRef
Chng, C.K.[Chee-Kheng],
Parra, A.[Alvaro],
Chin, T.J.[Tat-Jun],
Latif, Y.[Yasir],
Monocular Rotational Odometry with Incremental Rotation Averaging and
Loop Closure,
DICTA20(1-8)
IEEE DOI
2201
Visualization, Tracking, Estimation, Cameras, Trajectory,
Task analysis, Visual odometry
BibRef
Zheng, J.J.[Jian-Jie],
Zhang, H.T.[Hai-Tao],
Kong, W.D.[Wei-Di],
Tang, K.[Kai],
A SLAM Loop Closure Algorithm of BoW Incorporating the Gray Level of
Pixel,
CVIDL20(360-363)
IEEE DOI
2102
image matching, mobile robots, pattern clustering,
robot vision, SLAM (robots), trees (mathematics), Gray Level
BibRef
Ryohei, Y.,
Kanji, T.,
Koji, T.,
Invariant Spatial Information for Loop-Closure Detection,
MVA19(1-6)
DOI Link
1911
feature extraction, mobile robots, robot vision, SLAM (robots),
query/mapped image, invariant coordinate system,
Task analysis
BibRef
Tsintotas, K.A.[Konstantinos A.],
Giannis, P.[Panagiotis],
Bampis, L.[Loukas],
Gasteratos, A.[Antonios],
Appearance-based Loop Closure Detection with Scale-restrictive Visual
Features,
CVS19(75-87).
Springer DOI
1912
For autonomous robots.
BibRef
Miraldo, P.[Pedro],
Saha, S.[Surojit],
Ramalingam, S.[Srikumar],
Minimal Solvers for Mini-Loop Closures in 3D Multi-Scan Alignment,
CVPR19(9691-9700).
IEEE DOI
2002
BibRef
Fu, Z.H.[Zhi-Heng],
Guo, Y.L.[Yu-Lan],
An, W.[Wei],
Simultaneous Context Feature Learning and Hashing for Large Scale
Loop Closure Detection,
ICPR18(1689-1694)
IEEE DOI
1812
Feature extraction, Visualization, Learning systems, Convolution,
Dimensionality reduction, Training, Robots
BibRef
Bellavia, F.[Fabio],
Fanfani, M.[Marco],
Robust Selective Stereo SLAM without Loop Closure and Bundle Adjustment,
CIAP13(I:462-471).
Springer DOI
1311
BibRef
Patra, S.,
Aggarwal, H.,
Arora, H.,
Banerjee, S.,
Arora, C.,
Computing Egomotion with Local Loop Closures for Egocentric Videos,
WACV17(454-463)
IEEE DOI
1609
BibRef
Chen, X.Y.[Xie-Yuanli],
Lu, H.M.[Hui-Min],
Xiao, J.H.[Jun-Hao],
Zhang, H.[Hui],
Wang, P.[Pan],
Robust Relocalization Based on Active Loop Closure for Real-Time
Monocular SLAM,
CVS17(131-143).
Springer DOI
1711
BibRef
Chen, J.B.[Jian-Bin],
Li, J.[Jun],
Xu, Y.[Yang],
Shen, G.T.[Guang-Tian],
Gao, Y.J.[Yang-Jian],
A compact loop closure detection based on spatial partitioning,
ICIVC17(371-375)
IEEE DOI
1708
Image segmentation, Robots, Visualization, BoW, K-mean,
Loop closure detection, Scene, segmentation
BibRef
Laskar, Z.,
Huttunen, S.,
Herrera, D.,
Rahtu, E.,
Kannala, J.,
Robust loop closures for scene reconstruction by combining odometry
and visual correspondences,
ICIP16(2603-2607)
IEEE DOI
1610
Cameras
BibRef
Fei, X.O.[Xia-Ohan],
Tsotsos, K.[Konstantine],
Soatto, S.[Stefano],
A Simple Hierarchical Pooling Data Structure for Loop Closure,
ECCV16(III: 321-337).
Springer DOI
1611
BibRef
Zeng, M.[Ming],
Zheng, J.X.[Jia-Xiang],
Cheng, X.[Xuan],
Liu, X.G.[Xin-Guo],
Templateless Quasi-rigid Shape Modeling with Implicit Loop-Closure,
CVPR13(145-152)
IEEE DOI
1309
3d modeling; depth camera; human modeling; nonrigid deformation
BibRef
Khan, S.,
Wollherr, D.,
Buss, M.,
PIRF 3D: Online spatial and appearance based loop closure,
ICARCV12(335-340).
IEEE DOI
1304
BibRef
Chapoulie, A.[Alexandre],
Rives, P.[Patrick],
Filliat, D.[David],
A spherical representation for efficient visual loop closing,
OMNIVIS11(335-342).
IEEE DOI
1201
Did the robot return to the starting point.
BibRef
Pradeep, V.[Vivek],
Medioni, G.[Gerard],
Weiland, J.[James],
Visual loop closing using multi-resolution SIFT grids in
metric-topological SLAM,
CVPR09(1438-1445).
IEEE DOI
0906
Simultaneous Localization and Mapping.
Build 3-D model of the world to use in navigation.
BibRef
Kumar, A.[Ankita],
Tardif, J.P.[Jean-Philippe],
Anati, R.[Roy],
Daniilidis, K.[Kostas],
Experiments on visual loop closing using vocabulary trees,
VisLoc08(1-8).
IEEE DOI
0806
Initial from GPS. Long sequence in urban environment.
BibRef
Triebel, R.[Rudolph],
Pfaff, P.,
Burgard, W.[Wolfram],
Multi level surface maps
for outdoor terrain mapping and loop closing,
IROS06(xx-yy).
BibRef
0600
Chapter on Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following continues in
Vision-Language Navigation .