F. Amigoni, M. Reggiani, and V. Schiaffonati, An insightful comparison between experiments in mobile robotics and in science, Autonomous Robots, vol.24, issue.5, pp.313-325, 2009.
DOI : 10.1007/s10514-009-9137-8

L. Armesto, J. Minguez, and L. Montesano, A generalization of the metric-based Iterative Closest Point technique for 3D scan matching, 2010 IEEE International Conference on Robotics and Automation, pp.1367-1372, 2010.
DOI : 10.1109/ROBOT.2010.5509371

S. Arya and D. Mount, Approximate nearest neighbor queries in fixed dimensions, Discrete Algorithms Proceedings of the 4th Annual ACM-SIAM Symposium on, pp.271-280, 1993.

S. Baker, D. Scharstein, J. Lewis, S. Roth, M. Black et al., A Database and Evaluation Methodology for Optical Flow, International Journal of Computer Vision, pp.1-8, 2007.

O. Ben-kiki, C. Evans, and I. Döt-net, YAML Ain't Markup Language (YAML TM ) version 1.2, 2009.

P. Besl and H. Mckay, A method for registration of 3-D shapes. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.14, issue.2, pp.239-256, 1992.

Y. Chen and G. Medioni, 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

D. Chetverikov, D. Svirko, D. Stepanov, and P. Krsek, The Trimmed Iterative Closest Point algorithm, Object recognition supported by user interaction for service robots, pp.545-548, 2002.
DOI : 10.1109/ICPR.2002.1047997

J. Elseberg, S. Magnenat, R. Siegwart, and A. Nüchter, Comparison of nearest-neighbor-search strategies and implementations for efficient shape registration, Journal of Software Engineering for Robotics, vol.3, issue.1, pp.2-12, 2012.

A. Geiger, P. Lenz, and R. Urtasun, Are we ready for autonomous driving? The KITTI vision benchmark suite, 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012.
DOI : 10.1109/CVPR.2012.6248074

H. Hugli and C. Schutz, Geometric matching of 3D objects: assessing the range of successful initial configurations In: 3-D Digital Imaging and Modeling, Proceedings of the International Conference on Recent Advances in, pp.101-106, 1997.

D. Q. Huynh, Metrics for 3D Rotations: Comparison and Analysis, Journal of Mathematical Imaging and Vision, vol.19, issue.3, pp.155-164, 2009.
DOI : 10.1007/s10851-009-0161-2

B. Jian and B. C. Vemuri, Robust Point Set Registration Using Gaussian Mixture Models. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.33, issue.8, pp.1633-1645, 2011.

M. Magnusson, A. Lilienthal, and T. Duckett, 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

M. Magnusson, A. Nüchter, C. Lorken, A. Lilienthal, and J. Hertzberg, Evaluation of 3D registration reliability and speed - A comparison of ICP and NDT, 2009 IEEE International Conference on Robotics and Automation, pp.3907-3912, 2009.
DOI : 10.1109/ROBOT.2009.5152538

S. May, D. Droeschel, D. Holz, S. Fuchs, E. Malis et al., Three-dimensional mapping with time-of-flight cameras, Journal of Field Robotics, vol.23, issue.9, pp.11-12, 2009.
DOI : 10.1002/rob.20321

K. Pathak, D. Borrmann, J. Elseberg, N. Vaskevicius, A. Birk et al., Evaluation of the robustness of planar-patches based 3D-registration using marker-based ground-truth in an outdoor urban scenario, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.5725-5730, 2010.
DOI : 10.1109/IROS.2010.5649648

F. Pomerleau, M. Liu, F. Colas, and R. Siegwart, Challenging data sets for point cloud registration algorithms, The International Journal of Robotics Research, vol.29, issue.13, 2012.
DOI : 10.1177/0278364909103911
URL : https://hal.archives-ouvertes.fr/hal-01143454

F. Pomerleau, S. Magnenat, F. Colas, M. Liu, and R. Siegwart, Tracking a depth camera: Parameter exploration for fast ICP. In: Intelligent Robots and Systems, Proceedings of the IEEE/RSJ International Conference on, pp.3824-3829, 2011.
URL : https://hal.archives-ouvertes.fr/hal-01142622

S. Rusinkiewicz and M. Levoy, 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

R. Rusu and S. Cousins, 3D is here: Point Cloud Library (PCL) In: Robotics and Automation, Proceedings of the IEEE International Conference on, pp.1-4, 2011.

D. Scharstein and R. Szeliski, A taxonomy and evaluation of dense two-frame stereo correspondence algorithms, Proceedings IEEE Workshop on Stereo and Multi-Baseline Vision (SMBV 2001), pp.7-42, 2002.
DOI : 10.1109/SMBV.2001.988771

W. Schroeder, K. Martin, and B. Lorensen, The Visualization Toolkit, 2006.
DOI : 10.1016/B978-012387582-2/50032-0

S. M. Seitz, B. Curless, J. Diebel, D. Scharstein, and R. Szeliski, A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 1 (CVPR'06), pp.519-528, 2006.
DOI : 10.1109/CVPR.2006.19

C. H. Tong, T. D. Barfoot, and ´. E. Dupuis, Threedimensional SLAM for mapping planetary work site environments, Journal of Field Robotics, pp.381-412, 2012.

O. Wulf, A. Nüchter, J. Hertzberg, and B. Wagner, Benchmarking urban six-degree-of-freedom simultaneous localization and mapping, Journal of Field Robotics, vol.4, issue.4, pp.148-163, 2008.
DOI : 10.1002/rob.20234