. Bibliographie and . Abrate, Experimental ekf-based slam for mini-rovers with ir sensors only, Preceedings of 3rd European Conference on Mobile Robots, European Conference on Mobile Robots, 2007.

K. Agrawal, M. Agrawal, and K. Konolige, Real-time Localization in Outdoor Environments using Stereo Vision and Inexpensive GPS, 18th International Conference on Pattern Recognition (ICPR'06), pp.1063-1068, 2006.
DOI : 10.1109/ICPR.2006.962

. Argiles, Dense multiplanar scene estimation from a sparse set of images, Intelligent Robots and Systems (IROS), pp.4448-4454, 2011.

. Bailey, Consistency of the EKF-SLAM Algorithm, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.3562-3568, 2006.
DOI : 10.1109/IROS.2006.281644

. Berger, Modélisation de l'environnement par facettes planes pour la cartographie et la localisation simultanées par stéréovision, 2007.

. Betge-brezetz, Uncertain map making in natural environments, Proceedings of IEEE International Conference on Robotics and Automation, pp.1048-1053, 1996.
DOI : 10.1109/ROBOT.1996.506847

. Botero, Architecture embarquée pour le slam monoculaire, 2012.

G. Botero, G. Botero, and D. A. , Development of algorithms and architectures for driving assistance in adverse weather conditions using fpgas, 2012.
URL : https://hal.archives-ouvertes.fr/tel-00771869

D. Bulata, H. Bulata, and M. Devy, Incremental construction of a landmark-based and topological model of indoor environments by a mobile robot, Proceedings of IEEE International Conference on Robotics and Automation, pp.1054-1060, 1996.
DOI : 10.1109/ROBOT.1996.506848

. Chapuis, Accurate road following and reconstruction by computer vision, IEEE Transactions on Intelligent Transportation Systems, vol.3, issue.4, 2002.
DOI : 10.1109/TITS.2002.804751

C. , K. Chong, K. S. Kleeman, and L. , Feature-based mapping in real, large scale environments using an ultrasonic array, 1999.

. Civera, Inverse Depth Parametrization for Monocular SLAM, IEEE Transactions on Robotics, vol.24, issue.5, pp.932-945, 2008.
DOI : 10.1109/TRO.2008.2003276

. Civera, 1-point RANSAC for EKF-based Structure from Motion, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.3498-3504, 2009.
DOI : 10.1109/IROS.2009.5354410

D. Conte, G. Conte, and P. Doherty, An Integrated UAV Navigation System Based on Aerial Image Matching, 2008 IEEE Aerospace Conference, pp.1-10, 2008.
DOI : 10.1109/AERO.2008.4526556

C. Csorba, Simultaneous localisation and map building, 2007.

M. Davison, A. Davison, and D. Murray, Mobile robot localisation using active vision, Computer Vision-ECCV'98, pp.809-825, 1998.
DOI : 10.1007/BFb0054781

. Davison, MonoSLAM: Real-Time Single Camera SLAM, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.29, issue.6, pp.1052-1067, 2007.
DOI : 10.1109/TPAMI.2007.1049

K. Dellaert, F. Dellaert, and M. Kaess, Square Root SAM, Robotics: Science and Systems I, pp.177-184, 2005.
DOI : 10.15607/RSS.2005.I.024

[. Marco, Set membership localization and mapping for autonomous navigation, International Journal of Robust and Nonlinear Control, vol.41, issue.7, pp.709-734, 2001.
DOI : 10.1002/rnc.619

. Dissanayake, A solution to the simultaneous localization and map building (SLAM) problem, IEEE Transactions on Robotics and Automation, vol.17, issue.3, pp.229-241, 2001.
DOI : 10.1109/70.938381

B. Ducarouge, Reconstruction 3d infrarouge par perception active, 2011.
URL : https://hal.archives-ouvertes.fr/tel-00681977

. Estrada, Hierarchical SLAM: real-time accurate mapping of large environments, IEEE Transactions on Robotics, vol.21, issue.4, pp.588-596, 2005.
DOI : 10.1109/TRO.2005.844673

. Folkesson, J. Christensen-]-folkesson, and H. Christensen, SIFT Based Graphical SLAM on a Packbot, Field and Service Robotics, pp.317-328, 2008.
DOI : 10.1007/978-3-540-75404-6_30

URL : https://hal.archives-ouvertes.fr/inria-00194692

. Gifford, Low-cost multi-robot exploration and mapping, 2008 IEEE International Conference on Technologies for Practical Robot Applications, pp.74-79, 2008.
DOI : 10.1109/TEPRA.2008.4686676

. Gonzalez, A C-embedded algorithm for real-time monocular SLAM, 2011 18th IEEE International Conference on Electronics, Circuits, and Systems, 2011.
DOI : 10.1109/ICECS.2011.6122362

. Gonzalez, Slam visuel monoculaire par caméra infrarouge, ORASIS-Congrès des jeunes chercheurs en vision par ordinateur, 2011.

. Hajebi, . Zelek, K. Hajebi, and J. Zelek, Structure from Infrared Stereo Images, 2008 Canadian Conference on Computer and Robot Vision, pp.105-112, 2008.
DOI : 10.1109/CRV.2008.9

P. Harris, C. Harris, and J. Pike, 3D positional integration from image sequences, Image and Vision Computing, vol.6, issue.2, pp.87-90, 1988.
DOI : 10.1016/0262-8856(88)90003-0

S. Harris, C. Harris, and M. Stephens, A Combined Corner and Edge Detector, Procedings of the Alvey Vision Conference 1988, p.50, 1988.
DOI : 10.5244/C.2.23

Z. Hartley, R. Hartley, and A. Zisserman, Multiple view geometry in computer vision, 2000.
DOI : 10.1017/CBO9780511811685

L. Jaulin, A Nonlinear Set Membership Approach for the Localization and Map Building of Underwater Robots, IEEE Transactions on Robotics, vol.25, issue.1, pp.88-98, 2009.
DOI : 10.1109/TRO.2008.2010358

W. Jaulin, L. Jaulin, and E. Walter, Set inversion via interval analysis for nonlinear bounded-error estimation, Automatica, vol.29, issue.4, pp.1053-1064, 1993.
DOI : 10.1016/0005-1098(93)90106-4

A. Jazwinski, Stochastic processes and filtering theory, 1970.

L. Johnson, Do-178b : Software considerations in airborne systems and equipment certification, 1998.

. Julier, . Uhlmann, S. J. Julier, and J. K. Uhlmann, A counter example to the theory of simultaneous localization and map building, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164), pp.4238-4243, 2001.
DOI : 10.1109/ROBOT.2001.933280

J. , L. Jung, I. Lacroix, and S. , High resolution terrain mapping using low attitude aerial stereo imagery, Computer Vision, 2003. Proceedings. Ninth IEEE International Conference on. IEEE, pp.946-951, 2003.

. Kaess, . Dellaert, M. Kaess, and F. Dellaert, Visual slam with a multicamera rig, 2006.

. Kaess, iSAM: Incremental Smoothing and Mapping, IEEE Transactions on Robotics, vol.24, issue.6, pp.1365-1378, 2008.
DOI : 10.1109/TRO.2008.2006706

R. Kalman, A New Approach to Linear Filtering and Prediction Problems, Journal of Basic Engineering, vol.82, issue.1, pp.35-45, 1960.
DOI : 10.1115/1.3662552

. Kim, . Sukkarieh, J. Kim, and S. Sukkarieh, 6DoF SLAM aided GNSS/INS Navigation in GNSS Denied and Unknown Environments, Journal of Global Positioning Systems, vol.4, issue.1&2, pp.1-2, 2005.
DOI : 10.5081/jgps.4.1.120

M. Klein, G. Klein, and D. Murray, Parallel Tracking and Mapping for Small AR Workspaces, 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality, 2007.
DOI : 10.1109/ISMAR.2007.4538852

. Konolige, Large-Scale Visual Odometry for Rough Terrain, Robotics Research, pp.201-212, 2011.
DOI : 10.1007/978-3-642-14743-2_18

. Konolige, A low-cost laser distance sensor, 2008 IEEE International Conference on Robotics and Automation, pp.3002-3008, 2008.
DOI : 10.1109/ROBOT.2008.4543666

S. Lacroix, Brevet : Système d'aide au roulage tout-temps (sart) http://worldwide.espacenet.com/publicationDetails/originalDocument? FT=D&date=20090409&DB=&locale=en_EP&CC=WO&NR=2009044257A2&KC=A2&ND=2. [Lemaire and Lacroix Monocular-vision based slam using line segments, Robotics and Automation IEEE International Conference on, pp.2791-2796, 2007.

B. Leonard, . Feder, J. Leonard, and H. Feder, Decoupled stochastic mapping [for mobile robot amp ; auv navigation]. Oceanic Engineering, IEEE Journal, vol.26, issue.4oct, pp.561-571, 2001.

I. Ligon, A re-evaluation of the practicality of floating-point operations on FPGAs, Proceedings. IEEE Symposium on FPGAs for Custom Computing Machines (Cat. No.98TB100251), pp.206-215, 1998.
DOI : 10.1109/FPGA.1998.707898

. Lim, Real-time image-based 6-dof localization in large-scale environments, Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference, pp.1043-1050, 2012.

A. Lourakis and A. Argyros, The design and implementation of a generic sparse bundle adjustment software package based on the levenbergmarquardt algorithm, 2004.

. Magnenat, Affordable SLAM through the co-design of hardware and methodology, 2010 IEEE International Conference on Robotics and Automation, pp.5395-5401, 2010.
DOI : 10.1109/ROBOT.2010.5509196

D. Marquez-gamez, D. A. Marquez-gamez, and M. Devy, Visual navigation of communicating vehicles in unknown and changing environment, 2011 18th IEEE International Conference on Electronics, Circuits, and Systems, pp.673-676, 2011.
DOI : 10.1109/ICECS.2011.6122364

C. Mei, Laser-augmented omnidirectional vision for 3d localisation and mapping, 2007.
URL : https://hal.archives-ouvertes.fr/pastel-00004652

. Meier, PIXHAWK: A micro aerial vehicle design for autonomous flight using onboard computer vision, Autonomous Robots, vol.61, issue.5, pp.1-19, 2012.
DOI : 10.1007/s10514-012-9281-4

. Montemerlo, Fastslam : A factored solution to the simultaneous localization and mapping problem, Proceedings of the AAAI National Conference on Artificial Intelligence. AAAI, pp.593-598, 2002.

J. M. Montiel, Unified Inverse Depth Parametrization for Monocular SLAM, Robotics: Science and Systems II, 2006.
DOI : 10.15607/RSS.2006.II.011

O. Morrone, M. Morrone, and R. Owens, Feature detection from local energy, Pattern Recognition Letters, vol.6, issue.5, pp.303-313, 1987.
DOI : 10.1016/0167-8655(87)90013-4

. Mouragnon, Generic and real-time structure from motion using local bundle adjustment, Image and Vision Computing, vol.27, issue.8, pp.1178-1193, 2009.
DOI : 10.1016/j.imavis.2008.11.006

C. Moutarlier, P. Moutarlier, and R. Chatila, Stochastic multisensory data fusion for mobile robot localization and environment modelling, Proc. 5th Int. Symp. on Robotics Research (ISRR, pp.207-216, 1989.

. Neira, Mobile robot localization and map building using monocular vision, The 5th Symposium for Intelligent Robotics Systems. Citeseer, 1997.

I. Nikiforov, Module : Théorie de la décision et de l'estimation : approche statistique ch. 2-3 : Théorie de l'estimation et exemples, 2000.

. Nygårds, Navigation Aided Image Processing in UAV Surveillance: Preliminary Results and Design of an Airborne Experimental System, Journal of Robotic Systems, vol.1, issue.1, pp.63-72, 2004.
DOI : 10.1002/rob.10128

. Rady, A hybrid localization approach for UAV in GPS denied areas, 2011 IEEE/SICE International Symposium on System Integration (SII), pp.1269-1274, 2011.
DOI : 10.1109/SII.2011.6147631

. Rodriguez-losada, Brevet : Enhanced vision system (evs) http://patft.uspto.gov/netacgi/nph-Parser?Sect2=PTO1&Sect2=HITOFF&p= 1&u=/netahtml/PTO/search-bool.html&r=1&f=G&l=50&d=PALL&RefSrch=yes&Query= PN/7605774 Local maps fusion for real time multirobot indoor simultaneous localization and mapping, Robotics and Automation Proceedings. ICRA '04 IEEE International Conference on, pp.1308-1313, 2004.

. Roussillon, RT-SLAM: A Generic and Real-Time Visual SLAM Implementation, Proc. 8th Int. Conf. on Computer Vision Systems (ICVS), 2011.
DOI : 10.1016/j.patrec.2005.03.022

URL : https://hal.archives-ouvertes.fr/hal-00667191

. Roussillon, . Lacroix, R. Roussillon, and S. Lacroix, High rate-localization for high-speed all-terrain robots, CCCA12, 2012.
DOI : 10.1109/CCCA.2012.6417929

URL : https://hal.archives-ouvertes.fr/hal-01019431

. Schröter, Memory-efficient gridmaps in rao-blackwellized particle filters for slam using sonar range sensors, Proceedings of the European Conference on Mobile Robots, pp.138-143, 2007.

. Shi, . Tomasi, J. Shi, and C. Tomasi, Good features to track, Computer Vision and Pattern Recognition Proceedings CVPR'94. IEEE Computer Society Conference on. IEEE, pp.593-600, 1994.

. Smith, Real-Time Monocular SLAM with Straight Lines, Procedings of the British Machine Vision Conference 2006, pp.17-26, 2006.
DOI : 10.5244/C.20.3

. Smith, A stochastic map for uncertain spatial relationships, Proceedings of the 4th international symposium on Robotics Research, pp.467-474, 1988.

J. Solà, Towards visual localization, mapping and moving objects tracking by a mobile robot : a geometric and probabilistic approach, 2007.

J. Sola, Consistency of the monocular EKF-SLAM algorithm for three different landmark parametrizations, 2010 IEEE International Conference on Robotics and Automation, 2010.
DOI : 10.1109/ROBOT.2010.5509518

. Sola, An EKF-SLAM toolbox for MATLAB, 2009.

. Sola, BiCamSLAM: Two times mono is more than stereo, Proceedings 2007 IEEE International Conference on Robotics and Automation, pp.4795-4800, 2007.
DOI : 10.1109/ROBOT.2007.364218

. Sola, Undelayed initialization in bearing only SLAM, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2005.
DOI : 10.1109/IROS.2005.1545392

URL : https://hal.archives-ouvertes.fr/hal-01137845

. Solà, Impact of Landmark Parametrization on Monocular EKF-SLAM with Points and Lines, International Journal of Computer Vision, vol.24, issue.5, pp.339-368, 2012.
DOI : 10.1007/s11263-011-0492-5

. Stefano, ZNCC-based template matching using bounded partial correlation, Pattern Recognition Letters, vol.26, issue.14, pp.2129-2134, 2005.
DOI : 10.1016/j.patrec.2005.03.022

. Strasdat, Real-time monocular SLAM: Why filter?, 2010 IEEE International Conference on Robotics and Automation, 2010.
DOI : 10.1109/ROBOT.2010.5509636

. Tertei, . Piat, D. Tertei, and J. Piat, Implementing a joint pc-fpga platform for perception algorithms prototyping, 2012.

F. Thomas, Rejeu de chemin et localisation monoculaire : Application du visual slam sur carte peu dense en environnement extérieur contraint, 2011.

. Thrun, Simultaneous Mapping and Localization with Sparse Extended Information Filters: Theory and Initial Results, Algorithmic Foundations of Robotics V, pp.363-380, 2004.
DOI : 10.1007/978-3-540-45058-0_22

S. Thrun and M. Montemerlo, The Graph SLAM Algorithm with Applications to Large-Scale Mapping of Urban Structures, The International Journal of Robotics Research, vol.25, issue.5-6, pp.403-430, 2005.
DOI : 10.1177/0278364906065387

. Triggs, Bundle adjustment -a modern synthesis In Vision algorithms : theory and practice, pp.298-372, 2000.

K. Underwood, FPGAs vs. CPUs, Proceeding of the 2004 ACM/SIGDA 12th international symposium on Field programmable gate arrays , FPGA '04, pp.171-180, 2004.
DOI : 10.1145/968280.968305

. Vidal-calleja, Large scale multiple robot visual mapping with heterogeneous landmarks in semi-structured terrain, Robotics and Autonomous Systems, vol.59, issue.9, pp.654-674, 2011.
DOI : 10.1016/j.robot.2011.05.008

B. Vincke, Architectures pour des systèmes de localisation et de cartographie simultanées, 2012.

. Vincke, Real time simultaneous localization and mapping: towards low-cost multiprocessor embedded systems, EURASIP Journal on Embedded Systems, vol.2012, issue.1, 2012.
DOI : 10.1109/JSEN.2002.806212

P. Viola and M. Jones, Rapid object detection using a boosted cascade of simple features, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, pp.511-518, 2001.
DOI : 10.1109/CVPR.2001.990517

C. Shelton, Slam in large indoor environments with low-cost, noisy, and sparse sonars, ICRA'09. IEEE International Conference on. IEEE, pp.1395-1401, 2009.

. Zhang, Self-adaptive Monte Carlo localization for mobile robots using range sensors, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.1541-1546, 2009.
DOI : 10.1109/IROS.2009.5354298

S. La-problématique, Simultaneous Localization and Mapping) est un thème largement étudié au LAAS depuis plusieurs années. L'application visée concerne le développement d'un système d'aide au roulage sur aéroport des avions de ligne, ce système devant être opérationnel quelques soient les conditions météorologiques et de luminosité (projet SART financé par la DGE en partenariat avec principalement FLIR Systems

. Faible, une seule caméra traditionnelle n'est pas suffisante pour assurer la fonction de localisation Dans un premier temps, on se propose d'étudier l'apport d'une caméra infrarouge thermique Dans un deuxième temps, on s'intéressera à l'utilisation d'une centrale inertielle et d'un GPS dans l'algorithme de SLAM, la centrale aidant à la prédiction du mouvement, et le GPS à la correction des divergences éventuelles. Enfin, on intègrera dans ce même SLAM des pseudoobservations issues de l'appariement entre des segments extraits des images, et ces mêmes segments contenus dans une cartographie stockée dans une base de données. L'ensemble des observations et pseudo-observations a pour but de localiser le porteur à un mètre près. Les algorithmes devant être portés sur un FPGA muni d'un processeur de faible puissance par rapport aux PC standard (400 MHz), un co-design devra donc être effectué entre les éléments logiques du FPGA réalisant le traitement d'images à la volée et le processeur embarquant le filtre de Kalman étendu (EKF) pour le SLAM, de manière à garantir une application temps-réel à 30 Hz, Lors de conditions de visibilité difficile Ces algorithmes spécialement développés pour le co-design et les systèmes embarqués avioniques seront testés sur la plate-forme robotique du LAAS, puis portés sur différentes cartes de développement (Virtex 5, Raspberry, PandaBoard. . .) en vue de l'évaluation des performances