P. Dinnissen, S. N. Givigi, and H. M. Schwartz, Map merging of Multi-Robot SLAM using Reinforcement Learning, 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2012.
DOI : 10.1109/ICSMC.2012.6377676

S. Kohlbrecher, O. V. Stryk, T. U. Darmstadt, J. Meyer, and U. Klingauf, A flexible and scalable SLAM system with full 3D motion estimation, 2011 IEEE International Symposium on Safety, Security, and Rescue Robotics, 2011.
DOI : 10.1109/SSRR.2011.6106777

F. Pomerleau, F. Colas, R. Siegwart, and S. Magnenat, Comparing ICP variants on real-world data sets -open-source library and experimental protocol, Auton. Robots, 2013.
URL : https://hal.archives-ouvertes.fr/hal-01143458

R. Zlot and M. Bosse, Efficient Large-Scale 3D Mobile Mapping and Surface Reconstruction of an Underground Mine in FSR, ser. Springer Tracts in Advanced, 2012.

M. Bosse, R. Zlot, and P. Flick, Zebedee: Design of a Spring-Mounted 3-D Range Sensor with Application to Mobile Mapping, IEEE Transactions on Robotics, vol.28, issue.5, 2012.
DOI : 10.1109/TRO.2012.2200990

J. Zhang and S. Singh, LOAM: Lidar odometry and mapping in realtime, Robotics: Science and Systems, 2014.

J. Jessup, S. N. Givigi, and A. Beaulieu, Merging of octree based 3D occupancy grid maps, 2014 IEEE International Systems Conference Proceedings, 2014.
DOI : 10.1109/SysCon.2014.6819283

A. Hornung, K. M. Wurm, M. Bennewitz, C. Stachniss, and W. Burgard, OctoMap: an efficient probabilistic 3D mapping framework based on octrees, Autonomous Robots, vol.11, issue.3, 2013.
DOI : 10.15607/RSS.2007.III.017

J. Jessup, S. N. Givigi, and A. Beaulieu, Robust and Efficient Multirobot 3-D Mapping Merging With Octree-Based Occupancy Grids, IEEE Systems Journal, vol.11, issue.3, 2015.
DOI : 10.1109/JSYST.2015.2422615

A. Birk and S. Carpin, Merging Occupancy Grid Maps From Multiple Robots, Proceedings of the IEEE, 2006.
DOI : 10.1109/JPROC.2006.876965

R. Dubé, A. Gawel, H. Sommer, J. Nieto, R. Siegwart et al., An online multi-robot SLAM system for 3D LiDARs, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp.1004-1011, 2017.
DOI : 10.1109/IROS.2017.8202268

N. E. Ozkucur and H. L. Akin, Supervised feature type selection for topological mapping in indoor environments, 2013 21st Signal Processing and Communications Applications Conference (SIU), pp.1-4, 2013.
DOI : 10.1109/SIU.2013.6531556

J. Zhang and S. Singh, Aerial and Ground-Based Collaborative Mapping: An Experimental Study, The 11th Intl. Conf. on Field and Service Robotics (FSR), 2017.
DOI : 10.1109/ICRA.2016.7487211

R. I. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, 2004.
DOI : 10.1017/CBO9780511811685

R. Rusu and S. Cousins, 3D is here: Point Cloud Library (PCL), 2011 IEEE International Conference on Robotics and Automation, 2011.
DOI : 10.1109/ICRA.2011.5980567

L. Contreras, O. Kermorgant, and P. Martinet, Efficient Decentralized Collaborative Mapping for Outdoor Environments, 2018 Second IEEE International Conference on Robotic Computing (IRC), 2018.
DOI : 10.1109/IRC.2018.00017
URL : https://hal.archives-ouvertes.fr/hal-01689868

S. Rusinkiewicz and M. Levoy, Efficient variants of the ICP algorithm, Proceedings Third International Conference on 3-D Digital Imaging and Modeling, 2001.
DOI : 10.1109/IM.2001.924423

P. J. Besl and N. D. Mckay, A method for registration of 3-D shapes, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.14, issue.2, 1992.
DOI : 10.1109/34.121791