Point Clouds Registration with Probabilistic Data Association, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp.4092-4098, 2016. ,
DOI : 10.1109/IROS.2016.7759602
Maarten Weyn, A survey of rigid 3D pointcloud registration algorithms, in: Fourth International ,
, Conference on Ambient Computing, Applications, Services and Technologies, Proceedings, IARA, 2014, pp.8-13
A Review of Point Cloud Registration Algorithms for Mobile Robotics, Foundations and Trends in Robotics, vol.4, issue.1, pp.1-104 ,
DOI : 10.1561/2300000035
URL : https://hal.archives-ouvertes.fr/hal-01178661
Collar Line Segments for fast odometry estimation from Velodyne point clouds, 2016 IEEE International Conference on Robotics and Automation (ICRA), pp.4486-4495, 2016. ,
DOI : 10.1109/ICRA.2016.7487648
Surface Reconstruction with Sparse Point Clouds of Velodyne Sensor, The 14th IFToMM World Congress, 2015. ,
Evaluation of registration methods for sparse 3D laser scans, 2015 European Conference on Mobile Robots (ECMR), pp.1-7, 2015. ,
DOI : 10.1109/ECMR.2015.7324196
Finding planes in LiDAR point clouds for real-time registration, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.4347-4354, 2013. ,
DOI : 10.1109/IROS.2013.6696980
A Review Paper on Self -Driving Car ' s and its Applications, National Conference on Innovations in Micro-electronics, Signal Processing and Communication Technologies IJIRST, pp.33-35, 2016. ,
The Robot That Won the DARPA Grand Challenge, pp.1-43, 2007. ,
Visual localization within LI- DAR maps for automated urban driving, in: Intelligent Robots and Systems, 2014 IEEE/RSJ International Conference on, pp.176-183, 2014. ,
Monocular camera localization in 3D LiDAR maps, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp.1-6, 2016. ,
DOI : 10.1109/IROS.2016.7759304
Real-time probabilistic fusion of sparse 3D LIDAR and dense stereo, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp.2181-2188, 2016. ,
DOI : 10.1109/IROS.2016.7759342
Registration with the Point Cloud Library PCL, IEEE Robotics & Automation Magazine, vol.22, issue.4, pp.1-13, 2015. ,
Object modeling by registration of multiple range images, Proceedings. 1991 IEEE International Conference on Robotics and Automation, pp.2724-2729, 1991. ,
DOI : 10.1109/ROBOT.1991.132043
A method for registration of 3-D shapes, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.14, issue.2, pp.239-256, 1992. ,
DOI : 10.1109/34.121791
A review of 3D/2D registration methods for image-guided interventions, Medical Image Analysis, vol.16, issue.3, pp.642-661, 2012. ,
DOI : 10.1016/j.media.2010.03.005
A review of recent range image registration methods with accuracy evaluation, Image and Vision Computing, vol.25, issue.5, pp.578-596, 2007. ,
DOI : 10.1016/j.imavis.2006.05.012
URL : https://hal.archives-ouvertes.fr/hal-00578333
Applied registration for robotics, ETH ZURICH, 2013. ,
From point cloud to surface: the modeling and visualization problem, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol.34, issue.11, 2003. ,
A Modified Iterative Closest Point Algorithm for 3D Point Cloud Registration, Computer-Aided Civil and Infrastructure Engineering, vol.27, issue.2, pp.515-534, 2016. ,
DOI : 10.1111/j.1467-8667.2011.00727.x
Fast and robust 3D feature extraction from sparse point clouds, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp.4105-4112, 2016. ,
DOI : 10.1109/IROS.2016.7759604
Robust 3/6 DoF self-localization system with selective map update for mobile robot platforms, Robotics and Autonomous Systems, vol.76, pp.113-140, 2016. ,
DOI : 10.1016/j.robot.2015.09.030
3D feature point extraction from LiDAR data using a neural network, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences-ISPRS Archives, vol.41, pp.41-563, 2016. ,
A comparative evaluation of 3D keypoint detectors in a RGB-D object dataset, Computer Vision Theory and Applications (VISAPP), 2014 International Conference on, pp.476-483, 2014. ,
Object recognition from local scale-invariant features, Proceedings of the Seventh IEEE International Conference on Computer Vision, pp.1150-1157, 1999. ,
DOI : 10.1109/ICCV.1999.790410
3D is here: Point Cloud Library (PCL), 2011 IEEE International Conference on Robotics and Automation, pp.1-4, 2011. ,
DOI : 10.1109/ICRA.2011.5980567
Comparison of 3D interest point detectors and descriptors for point cloud fusion, ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-3, pp.57-64, 2014. ,
Machine Learning for High-Speed Corner Detection, Computer Vision?ECCV, vol.1, pp.430-443, 2006. ,
DOI : 10.1109/ICNN.1995.489004
Speeded-Up Robust Features (SURF), Computer Vision and Image Understanding, vol.110, issue.3, pp.346-359, 2008. ,
DOI : 10.1016/j.cviu.2007.09.014
ORB: An efficient alternative to SIFT or SURF, 2011 International Conference on Computer Vision, pp.2564-2571, 2011. ,
DOI : 10.1109/ICCV.2011.6126544
Point Feature Extraction on 3D Range Scans Taking into Account Object Boundaries Bastian, IEEE International Conference on Robotics and Automation (ICRA), pp.2601-2608, 2011. ,
Aligning point cloud views using persistent feature histograms, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.3384-3391, 2008. ,
DOI : 10.1109/IROS.2008.4650967
Fast Point Feature Histograms (FPFH) for 3D registration, 2009 IEEE International Conference on Robotics and Automation, pp.3212-3217, 2009. ,
DOI : 10.1109/ROBOT.2009.5152473
Fast 3D recognition and pose using the Viewpoint Feature Histogram, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.2155-2162, 2010. ,
DOI : 10.1109/IROS.2010.5651280
CAD-model recognition and 6DOF pose estimation using 3D cues, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), pp.585-592, 2011. ,
DOI : 10.1109/ICCVW.2011.6130296
Principal Component Analysis for Special Types of Data, pp.199-222, 1986. ,
DOI : 10.1007/978-1-4757-1904-8_11
Intrinsic shape signatures: A shape descriptor for 3d object recognition, in: Computer Vision Workshops, 2009 IEEE 12th International Conference on, pp.689-696, 2009. ,
On the Repeatability and Quality of Keypoints for Local Feature-based 3D Object Retrieval from Cluttered Scenes, International Journal of Computer Vision, vol.46, issue.1, pp.348-361, 2010. ,
DOI : 10.1109/34.765655
Automatic registration of unordered point clouds acquired by Kinect sensors using an overlap heuristic, ISPRS Journal of Photogrammetry and Remote Sensing, vol.102, pp.96-109, 2015. ,
DOI : 10.1016/j.isprsjprs.2014.12.014
NICP: Dense normal based point cloud registration, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp.742-749, 2015. ,
DOI : 10.1109/IROS.2015.7353455
Go-ICP: Solving 3D Registration Efficiently and Globally Optimally, 2013 IEEE International Conference on Computer Vision, pp.1457-1464, 2013. ,
DOI : 10.1109/ICCV.2013.184
Automatic registration of large-scale urban scene point clouds based on semantic feature points, ISPRS Journal of Photogrammetry and Remote Sensing, vol.113, pp.43-58, 2016. ,
DOI : 10.1016/j.isprsjprs.2015.12.005
Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age, IEEE Transactions on Robotics, vol.32, issue.6, p.13091332, 2016. ,
DOI : 10.1109/TRO.2016.2624754
Scan-SLAM: Combining EKF-SLAM and Scan Correlation, Advanced Robotics, vol.25, pp.167-178, 2006. ,
DOI : 10.1007/978-3-540-33453-8_15
Mapping, Planning, and Sample Detection Strategies for Autonomous Exploration, Journal of Field Robotics, vol.25, issue.8, pp.75-106, 2014. ,
DOI : 10.1002/rob.20255
Scan registration for autonomous mining vehicles using 3D-NDT, Journal of Field Robotics, vol.10, issue.10, pp.803-827, 2007. ,
DOI : 10.1002/rob.20204
, Robotics: Science and Systems, vol.5, pp.168-176, 2009.
Comparing ICP variants on real-world data sets, Autonomous Robots, vol.25, issue.3, pp.133-148, 2013. ,
DOI : 10.1002/rob.20234
URL : https://hal.archives-ouvertes.fr/hal-01143458
Segmatch: Segment based loop-closure for 3d point clouds, arXiv preprint ,
SLAM++: Simultaneous Localisation and Mapping at the Level of Objects, 2013 IEEE Conference on Computer Vision and Pattern Recognition, pp.1352-1359, 2013. ,
DOI : 10.1109/CVPR.2013.178
Scene structure registration for localization and mapping, Robotics and Autonomous Systems, vol.75, pp.649-660, 2016. ,
DOI : 10.1016/j.robot.2015.09.009
Fast place recognition with planebased maps, Robotics and Automation (ICRA), 2013 IEEE International Conference on, pp.2719-2724, 2013. ,
Fast plane extraction in 3D range data based on line segments, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.3808-3815, 2011. ,
DOI : 10.1109/IROS.2011.6094916
Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography, Communications of the ACM, vol.24, issue.6, pp.381-395, 1981. ,
DOI : 10.1145/358669.358692
Mobile robot navigation using the range-weighted Hough transform, IEEE Robotics & Automation Magazine, vol.2, issue.1, pp.18-26, 1995. ,
DOI : 10.1109/100.388295
Visually bootstrapped generalized ICP, 2011 IEEE International Conference on Robotics and Automation, pp.2660-2667, 2011. ,
DOI : 10.1109/ICRA.2011.5980322
URL : http://robots.engin.umich.edu/publications/gpandey-2011b.pdf
Fast planar surface 3D SLAM using LIDAR, Robotics and Autonomous Systems, vol.92, pp.197-220, 2017. ,
DOI : 10.1016/j.robot.2017.03.013
Super 4PCS Fast Global Pointcloud Registration via Smart Indexing, Computer Graphics Forum, vol.3, issue.3, pp.205-215, 2014. ,
DOI : 10.1561/0600000017
URL : https://hal.archives-ouvertes.fr/hal-01538738
Learning the matching of local 3d geometry in range scans ,
Automatic registration of laserscanned point clouds based on planar features, 2nd ISPRS International Conference on Computer Vision in Remote Sensing International Society for Optics and Photonics, p.990103, 2015. ,
, Toward Object-based Place Recognition in Dense RGB-D Maps
Real-Time Scale Invariant 3D Range Point Cloud Registration, International Conference Image Analysis and Recognition, pp.220-229, 2010. ,
DOI : 10.1007/978-3-642-13772-3_23
Efficient variants of the ICP algorithm, Proceedings Third International Conference on 3-D Digital Imaging and Modeling, pp.145-152, 2001. ,
DOI : 10.1109/IM.2001.924423
Improving 3D Lidar Point Cloud Registration Using Optimal Neighborhood Knowledge, ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences I-3, pp.111-116, 2012. ,
Iterative point matching for registration of free-form curves and surfaces, International Journal of Computer Vision, vol.7, issue.3, pp.119-152, 1994. ,
DOI : 10.1007/978-3-642-58148-9
Faster methods for random sampling, Communications of the ACM, vol.27, issue.7, pp.703-718, 1984. ,
DOI : 10.1145/358105.893
Semantic 3D Object Maps for Everyday Manipulation in Human Living Environments, KI - K??nstliche Intelligenz, vol.24, issue.4, p.2009, 2009. ,
DOI : 10.1007/s13218-010-0059-6
How do ICP variants perform when used for scan matching terrain point clouds?, Robotics and Autonomous Systems, vol.87, pp.147-161, 2017. ,
DOI : 10.1016/j.robot.2016.10.011
Comparison of nearest-neighbor-search strategies and implementations for efficient shape registration, Journal of Software Engineering for Robotics (JOSER), vol.3, issue.1, pp.2-12, 2012. ,
M2DP: A novel 3D point cloud descriptor and its application in loop closure detection, in: Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on, pp.231-237, 2016. ,
Comparison of surface normal estimation methods for range sensing applications, 2009 IEEE International Conference on Robotics and Automation, pp.3206-3211, 2009. ,
DOI : 10.1109/ROBOT.2009.5152493
Color-based 3D point cloud reduction, 2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV), pp.1-7 ,
DOI : 10.1109/ICARCV.2016.7838685
URL : https://hal.archives-ouvertes.fr/hal-01877712
Data Handling in Large-Scale Surface Reconstruction, 13th International Conference on Intelligent Autonomous Systems, pp.1-12, 2014. ,
DOI : 10.1007/978-3-319-08338-4_37
The Advantages of Careful Seeding, Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA '07, pp.1027-1035, 2007. ,
Estimating the number of clusters in a data set via the gap statistic, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.63, issue.2, pp.411-423, 2001. ,
DOI : 10.1111/1467-9868.00293
, Robust statistics, 2009.
Robust statistics, pp.45-67, 1981. ,
DOI : 10.1002/0471725250
URL : https://onlinelibrary.wiley.com/doi/pdf/10.1002/0471725250.fmatter
Numerical methods for least squares problems, 1996. ,
DOI : 10.1137/1.9781611971484
Improved Sampling for Terrestrial and Mobile Laser Scanner Point Cloud Data, Remote Sensing, vol.20, issue.4, pp.1754-1773, 2013. ,
DOI : 10.1364/OE.20.007119
URL : http://www.mdpi.com/2072-4292/5/4/1754/pdf