Simultaneous Localization and Mapping (SLAM)
Table of Contents:
SLAM
Early efforts towards visual SLAM were solved by filtering. [5], [6]
https://arxiv.org/pdf/1902.03747.pdf
Keyframe-Bases SLAM
Parallel Tracking and Mapping (PTAM) by Klein and Murray introduced idea of splitting camera tracking and mapping in parallel threads
ORB-SLAM
LSD-SLAM
Semi-Direct Visual Odometry (SVO)
Forster et al. [4]
GraphSLAM
VIDEO https://www.youtube.com/playlist?list=PLgnQpQtFTOGQrZ4O5QzbIHgl3b1JHimN_
SLAM methods [2, 10, 13, 14, 21, 30]
M. Bosse, P. Newman, J. Leonard, M. Soika, W. Feiten, and S. Teller. Simultaneous localization and map building in large-scale cyclic envi- ronments using the atlas framework. IJRR, 23(12), 2004.
T. Duckett, S. Marsland, and J. Shapiro. Learning globally consistent maps by relaxation. ICRA 2000.
J. Folkesson and H. I. Christensen. Robust SLAM. ISAV 2004. [14] U. Frese, P. Larsson, and T. Duckett. A multigrid algorithm for simultaneous localization and mapping. IEEE Transactions on Robotics, 2005.
K. Konolige. Large-scale map-making. AAAI, 2004.
S. Thrun and M. Montemerlo. The GraphSLAM algorithm with applications to large-scale mapping of urban structures. IJRR, 25(5/6), 2005.
. Folkesson and H. I. Christensen. Robust SLAM. ISAV 2004.
Monte Carlo Localization
Bundler
Extract focal lengths from Exif tags, call SIFT on the image set focal constraints,
SLAM Code
http://www.robots.ox.ac.uk/~vgg/hzbook/code/ http://ceres-solver.org/ http://www.cs.cornell.edu/~snavely/bundler/ https://github.com/snavely/bundler_sfm http://wp.doc.ic.ac.uk/thefutureofslam/wp-content/uploads/sites/93/2015/12/slides_ajd.pdf http://wp.doc.ic.ac.uk/thefutureofslam/wp-content/uploads/sites/93/2015/12/kerl_etal_iccv2015_futureofslam_talk.pdf https://github.com/tum-vision/lsd_slam https://vision.in.tum.de/research/vslam/lsdslam
LSD SLAM
http://16623.courses.cs.cmu.edu/slides/Lecture_19.pdf
Deep Learning + SLAM
https://arxiv.org/abs/1612.00603 https://www.ci2cv.net/media/papers/AAAI2018_chenhuan.pdf
core idea of optimizing variable in latent space is similar
- Prior for 3D Shape. https://ci2cv.net/media/papers/WACV18.pdf
- Prior for depth map. code slam
https://www.ri.cmu.edu/wp-content/uploads/2018/01/mingfanc_thesis.pdf
http://16623.courses.cs.cmu.edu/slides/Lecture_13.pdf http://16623.courses.cs.cmu.edu/slides/Lecture_12.pdf http://16623.courses.cs.cmu.edu/slides/Lecture_14.pdf http://16623.courses.cs.cmu.edu/slides/Lecture_19.pdf
https://github.com/raulmur/ORB_SLAM2
https://github.com/tum-vision/lsd_slam
https://www.doc.ic.ac.uk/~ajd/Robotics/RoboticsResources/SLAMTutorial1.pdf
https://www.doc.ic.ac.uk/~ajd/Robotics/RoboticsResources/SLAMTutorial2.pdf
References
[1]. Tim Bailey and Hugh Durrant-Whyte. https://www.doc.ic.ac.uk/~ajd/Robotics/RoboticsResources/SLAMTutorial2.pdf
[2]. Tim Bailey and Hugh Durrant-Whyte. https://www.doc.ic.ac.uk/~ajd/Robotics/RoboticsResources/SLAMTutorial1.pdf
[3]. G. Klein and D. Murray, “Parallel tracking and mapping for small AR workspaces,” in IEEE and ACM International Symposium on Mixed and Augmented Reality (ISMAR), Nara, Japan, November 2007, pp. 225–23
[4]. C. Forster, M. Pizzoli, and D. Scaramuzza, “SVO: Fast semi-direct monocular visual odometry,” in Proc. IEEE Intl. Conf. on Robotics and Automation, Hong Kong, China, June 2014, pp. 15–22.
[5]. A. J. Davison, I. D. Reid, N. D. Molton, and O. Stasse, “MonoSLAM: Real-time single camera SLAM,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29, no. 6, pp. 1052–1067, 2007
[6]. A. Chiuso, P. Favaro, H. Jin, and S. Soatto, “Structure from motion causally integrated over time,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 4, pp. 523–535, 2002