P. Anderson-sprecher, R. Simmons, and D. Huber, Background subtraction and accessibility analysis in evidence grids, Robotics and Automation (ICRA), 2011 IEEE International Conference on, pp.3104-3110, 2011.

A. Asvadi, P. Peixoto, and U. Nunes, Two-stage static/dynamic environment modeling using voxel representation, Robot 2015: Second Iberian Robotics Conference, pp.465-476, 2016.

A. Asvadi, C. Premebida, P. Peixoto, and U. Nunes, 3d lidar-based static and moving obstacle detection in driving environments: An approach based on voxels and multiregion ground planes, Robotics and Autonomous Systems, vol.83, pp.299-311, 2016.

B. Bellekens, V. Spruyt, R. Berkvens, and M. Weyn, A survey of rigid 3d pointcloud registration algorithms, AMBIENT 2014: the Fourth International Conference on Ambient Computing, pp.8-13, 2014.

T. Bouwmans, Traditional and recent approaches in background modeling for foreground detection: An overview, Computer Science Review, vol.11, pp.31-66, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01077140

J. E. Bresenham, Algorithm for computer control of a digital plotter, IBM Systems Journal, vol.4, issue.1, pp.25-30, 1965.

R. J. Campello, D. Moulavi, A. Zimek, and J. Sander, Hierarchical density estimates for data clustering, visualization, and outlier detection, ACM Trans. Knowl. Discov. Data, vol.10, issue.1, 2015.

L. Chen, J. Yang, and H. Kong, Lidar-histogram for fast road and obstacle detection, 2017 IEEE International Conference on, pp.1343-1348, 2017.

W. Churchill and P. Newman, Practice makes perfect? managing and leveraging visual experiences for lifelong navigation, Robotics and Automation (ICRA), 2012 IEEE International Conference on, pp.4525-4532, 2012.

O. Dabeer, W. Ding, R. Gowaiker, S. K. Grzechnik, M. J. Lakshman et al., An end-to-end system for crowdsourced 3d maps for autonomous vehicles: The mapping component, Intelligent Robots and Systems, pp.634-641, 2017.

K. Doherty, J. Wang, and B. Englot, Bayesian generalized kernel inference for occupancy map prediction, IEEE International Conference on Robotics and Automation (ICRA, pp.3118-3124, 2017.

A. Dosovitskiy, G. Ros, F. Codevilla, A. Lopez, and V. Koltun, CARLA: An open urban driving simulator, Proceedings of the 1st Annual Conference on Robot Learning, pp.1-16, 2017.

E. Einhorn, C. Schröter, and H. M. Gross, Finding the adequate resolution for grid mapping-cell sizes locally adapting on-the-fly, Robotics and Automation (ICRA), 2011 IEEE International Conference on, pp.1843-1848, 2011.

G. Elbaz, T. Avraham, and A. Fischer, 3d point cloud registration for localization using a deep neural network auto-encoder, Computer Vision and Pattern Recognition (CVPR), 2017 IEEE Conference on, pp.2472-2481, 2017.

A. Elfes, Using occupancy grids for mobile robot perception and navigation, Computer, vol.22, issue.6, pp.46-57, 1989.

E. Francis, K. Theodora, H. Alexander, and L. Bastian, Exploring spatial context for 3d semantic segmentation of point clouds, IEEE International Conference on Computer Vision, 3DRMS Workshop, ICCV, 2017.

W. S. Grant, R. C. Voorhies, and L. Itti, Finding planes in lidar point clouds for realtime registration, Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on, pp.4347-4354, 2013.

T. Hackel, N. Savinov, L. Ladicky, J. D. Wegner, K. Schindler et al., Semantic3d.net: A new large-scale point cloud classification benchmark, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. vol. IV-1-W1, pp.91-98, 2017.

M. Herbert, C. Caillas, E. Krotkov, I. S. Kweon, and T. Kanade, Terrain mapping for a roving planetary explorer, Proceedings, 1989 International Conference on Robotics and Automation, vol.2, pp.997-1002, 1989.

B. R. Kiran and S. Yogamani, Real-time background subtraction using adaptive sampling and cascade of gaussians, 2017.

J. Levinson, J. Askeland, J. Becker, J. Dolson, D. Held et al., Towards fully autonomous driving: Systems and algorithms, Intelligent Vehicles Symposium (IV), pp.163-168, 2011.

L. Ma, Y. Li, J. Li, C. Wang, R. Wang et al., Mobile laser scanned point-clouds for road object detection and extraction: A review, Remote Sensing, vol.10, issue.10, 2018.

W. Maddern, G. Pascoe, and P. Newman, Leveraging experience for large-scale lidar localisation in changing cities, Robotics and Automation (ICRA), 2015 IEEE International Conference on, pp.1684-1691, 2015.

L. Mcinnes, J. Healy, and S. Astels, hdbscan: Hierarchical density based clustering, The Journal of Open Source Software, vol.2, issue.11, 2017.

,

S. Milz, G. Arbeiter, C. Witt, B. Abdallah, and S. Yogamani, Visual slam for automated driving: Exploring the applications of deep learning, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp.247-257, 2018.

H. Moravec and A. E. Elfes, High resolution maps from wide angle sonar, Proceedings of the 1985 IEEE International Conference on Robotics and Automation, pp.116-121, 1985.
DOI : 10.1109/robot.1985.1087316

E. A. Nelson, Environment model adaptation for autonomous exploration, Robotics Institute, 2015.
DOI : 10.1007/s10514-017-9669-2

A. A. Ortega-jiménez and J. Andrade-cetto, Segmentation of dynamic objects from laser data, ECMR 5th European Conference on Mobile Robots, pp.115-121, 2011.

D. M. Rosen, J. Mason, and J. J. Leonard, Towards lifelong feature-based mapping in semi-static environments, Robotics and Automation (ICRA), 2016 IEEE International Conference on, pp.1063-1070, 2016.
DOI : 10.1109/icra.2016.7487237

A. Sharma, O. Grau, and M. Fritz, Vconv-dae: Deep volumetric shape learning without object labels, European Conference on Computer Vision, pp.236-250, 2016.

M. Siam, H. Mahgoub, M. Zahran, S. Yogamani, M. Jagersand et al., Modnet: Moving object detection network with motion and appearance for autonomous driving, 2017.
DOI : 10.1109/itsc.2018.8569744

M. Simon, S. Milz, K. Amende, and H. M. Gross, Complex-yolo: Real-time 3d object detection on point clouds, 2018.
DOI : 10.1007/978-3-030-11009-3_11

T. Sixta, LIDAR Based Sequential Registration and Mapping for Autonomous Vehicles, 2017.

S. Thrun, W. Burgard, and D. Fox, Probabilistic Robotics (Intelligent Robotics and Autonomous Agents), 2005.

R. Triebel, P. Pfaff, and W. Burgard, Multi-level surface maps for outdoor terrain mapping and loop closing, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.2276-2282, 2006.
DOI : 10.1109/iros.2006.282632

A. K. Ushani, R. W. Wolcott, J. M. Walls, and R. M. Eustice, A learning approach for real-time temporal scene flow estimation from lidar data, 2017 IEEE International Conference on, pp.5666-5673, 2017.

M. Velas, M. Spanel, M. Hradis, and A. Herout, Cnn for very fast ground segmentation in velodyne lidar data, Autonomous Robot Systems and Competitions (ICARSC), 2018 IEEE International Conference on, pp.97-103, 2018.

P. Viola and M. Jones, Rapid object detection using a boosted cascade of simple features, Computer Vision and Pattern Recognition, vol.1, 2001.
DOI : 10.1109/cvpr.2001.990517
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.10.6807

P. Wang, R. Yang, B. Cao, W. Xu, and Y. Lin, Dels-3d: Deep localization and segmentation with a 3d semantic map, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.5860-5869, 2018.
DOI : 10.1109/cvpr.2018.00614
URL : http://arxiv.org/pdf/1805.04949

R. W. Wolcott, Robust localization in 3d prior maps for autonomous driving, 2016.

R. W. Wolcott and R. M. Eustice, Visual localization within lidar maps for automated urban driving, Intelligent Robots and Systems, pp.176-183, 2014.

K. M. Wurm, D. Hennes, D. Holz, R. B. Rusu, C. Stachniss et al., Hierarchies of octrees for efficient 3d mapping, Intelligent Robots and Systems (IROS), pp.4249-4255, 2011.
DOI : 10.1109/iros.2011.6048189

K. M. Wurm, A. Hornung, M. Bennewitz, C. Stachniss, and W. Burgard, Octomap: A probabilistic, flexible, and compact 3d map representation for robotic systems, Proc. of the ICRA 2010 workshop, 2010.

H. Yin and C. Berger, Mastering data complexity for autonomous driving with adaptive point clouds for urban environments, Intelligent Vehicles Symposium (IV, pp.1364-1371, 2017.

X. Yue, B. Wu, S. A. Seshia, K. Keutzer, and A. L. Sangiovanni-vincentelli, A lidar point cloud generator: from a virtual world to autonomous driving, Proceedings of the 2018 ACM on International Conference on Multimedia Retrieval, pp.458-464, 2018.