Robotique mobile


précédentsommaire

VI. Index

Amers (1), (2), (3)

Modèle probabiliste (1), (2)

Braitenberg (1), (2)

Navigation métrique (1)

Carte métrique (1)

Navigation par carte (1)

Carte topologique (1)

Navigation réactive (1)

Cartographie (1), (2)Cartographie

Navigation topologique (1)

Distance de Mahalanobis (1)

Perception/Décision/Action (1), (2), (3)Architectures de contrôle

FastSLAM (1)

Perceptions (1)

Filtre de Kalman (1), (2)Cartographie par filtrage de Kalman étendu

Perceptual aliasing (1), (2), (3), (4)

Filtre de Kalman étendu (1)

Planification (1), (2), (3)Planification

Filtre particulaire (1), (2)Filtrage particulaire, (3)

Politique (1), (2), (3)Calcul de politique

Histogram Filter (1)

Q-Learning (1)

Holonomie (1), (2), (3)

Rao-Blackwellisation (1)

Informations proprioceptives (1)

SLAM (1), (2)Cartographie par filtrage de Kalman étendu

Localisation (1), (2)Localisation

Snapshot Model (1)

MDP (1)

Stratégies de navigation (1)Stratégies de navigation

Modèle métrique (2), (2)

Variabilité perceptuelle (1)

VII. Bibliographie

[1] A. Angeli, D. Filliat, S. Doncieux, and J.-A. Meyer. A fast and incremental method for loopclosure detection using bags of visual words. IEEE Transactions On Robotics, Special Issue on Visual SLAM, 2008.

[2] A. Angeli, D. Filliat, S. Doncieux, and J.-A. Meyer. Visual topological slam and global localization. In Proceedings of the International Conference on Robotics and Automation (ICRA), 2009.

[3] R. Arkin. Towards the unification of navigational planning and reactive control. In Proceedings of the AAAI Spring Symposium on Robot Navigation, pages 1–5, 1989.

[4] Ronald Arkin. Behavior-Based Robotics. The MIP Press, 1998.

[5] A. Arleo, J. del R. Millán, and D. Floreano. Efficient learning of variable-resolution cognitive maps for autonomous indoor navigation. In IEEE Transactions on Robotics and Automation, volume 15, pages 990–1000, 1999.

[6] A. Arleo and W. Gerstner. Spatial cognition and neuro-mimetic navigation : A model of hippocampal place cell activity. Biological Cybernetics, Special Issue on Navigation in Biological and Artificial Systems, 83 :287–299, 2000.

[7] A. Arsenio and M. I. Ribeiro. Absolute localization of mobile robots using natural landmarks. In Proceedings of the International Conference on Electronics, Circuits and Systems, 1998.

[8] N. Ayache and O. Faugeras. Maintaning representations of the environment of a mobile robot. IEEE Transactions on Robotics and Automation, 5(6) :804 – 819, 1989.

[9] I. A. Bachelder and A. M. Waxman. Mobile robot visual mapping and localization : A viewbased neurocomputational architecture that emulates hippocampal place learning. Neural Networks, 7(6/7) :1083–1099, 1994.

[10] I. A. Bachelder and A. M. Waxman. A view-based neurocomputational system for relational map-making and navigation in visual environments. Robotics and Autonomous Systems, 16 :267–298, 1995.

[11] J. E. Baker. Reducing bias and inefficiency in the selection algorithm. In Proceedings of the Second International Conference on Genetic Algorithms, pages 14–21. Lawrence Erlbaum Associates (Hillsdale), 1987.

[12] K. Balakrishnan, O. Bousquet, and V. Honavar. Spatial learning and localization in rodents : A computation model of the hippocampus and its implications for mobile robots. Adaptive Behavior, 7(2) :173–216, 1999.

[13] S. Bazeille and D. Filliat. Incremental topo-metric slam using vision and robot odometry. In Proceedings of the International Conference on Robotics and Automation (ICRA), 2011.

[14] M. Betke and K. Gurvits. Mobile robot localization using landmarks. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA-94), volume 2, pages 135–142, 1994.

[15] G. Blanc, Y. Mezouar, and P. Martinet. Indoor navigation of a wheeled mobile robot along visual routes. In Proceedings of the IEEE International Conference on Robotics and Automation, 2005.

[16] D. Boley, E. Steinmetz, and K. Sutherland. Robot localization from landmarks using recursive total least squares. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA-96), volume 4, pages 1381–1386, 1996.

[17] J. Borenstein and Y. Koren. The vector field histogram - fast obstacle avoidance for mobile robots. IEEE Journal of Robotics and Automation, 7 :278–288, 1991.

[18] G. Borghi and D. Brugali. Autonomous map learning for a multi-sensor mobile robot using diktiometric representation and negotiation mechanism. In Proceedings of the International Conference on Advanced Robotics (ICAR-95), 1995.

[19] Valentino Braitenberg. Vehicles : Experiments in Synthetic Psychology. The MIT Press, 1986.

[20] R. A. Brooks. Intelligence without representation. Artificial Intelligence, 1(47) :139–159, 1991.

[21] Rodney A. Brooks. How to Build Complete Creatures Rather than Isolated Cognitive Simulators. In Architectures for Intelligence, pages 225–239, 1991.

[22] J. Buhmann, W. Burgard, A. B. Cremers, D. Fox, T. Hofmann, F. Schneider, J. Strikos, and S. Thrun. The mobile robot rhino. AI Magazine, 16(1), 1995.

[23] W. Burgard, A. B. Cremers, D. Fox, D. Hähnel, G. Lakemeyer, D. Schulz, W. Steiner, and S. Thrun. The interactive museum tour-guide robot. In Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI-98). The MIT Press, 1998.

[24] W. Burgard, D. Fox, D. Hennig, and T. Schmidt. Estimating the absolute position of a mobile robot using position probability grids. In Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96), pages 896–901, 1996.

[25] N. Burgess, M. Recce, and J. O’Keefe. A model of hippocampal function. Neural Networks, 7 :1065–1081, 1994.

[26] B. A. Cartwright and T. S. Collett. Landmark maps for honeybees. Biol. Cybern., 57 :85–93, 1987.

[27] A. R. Cassandra, L. P. Kaelbling, and J. A. Kurien. Acting under uncertainty : Discrete bayesian models for mobile-robot navigation. In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, 1996.

[28] J. A. Castellanos, J. M. M. Montiel, J. Neira, , and J. D. Tardos. The SPmap : A probabilistic framework for simultaneous localization and map building. IEEE Transactions on Robotics and Automation, 15(5) :948–953, 1999.

[29] R. Chatila and J. Laumond. Position referencing and consistent world modelling for mobile robots. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA-85), pages 138–170, 1985.

[30] F. Chaumette. La commande des robots manipulateurs, chapter Asservissement visuel. Traité IC2, Hermès, 2002.

[31] I. J. Cox. Blanche - an experiment in guidance and navigation of an autonomous robot vehicle. IEEE Transactions on Robotics and Automation, 7(2) :193–204, 1991.

[32] A. Dalgalarrondo, D. Dufourd, and D. Filliat. Controlling the autonomy of a reconnaissance robot. In SPIE Defense and Security 2004 Symposium. Unmanned Ground Vehicle Technology VI Conference, 2004.

[33] G. Dedeoglu, M. Mataric, and G. S. Sukhatme. Incremental, online topological map building with a mobile robot. In Proceedings of Mobile Robots XIV - SPIE, pages 129–139, 1999.

[34] A. Diosi, S. Segvic, A. Remazeilles, and F. Chaumette. Experimental evaluation of autonomous driving based on visual memory and image based visual servoing. IEEE Trans. on Intelligent Transportation Systems, 2011.

[35] T. Duckett, S. Marsland, and J. Shapiro. Learning globally consistent maps by relaxation. In Proceedings of the International Conference on Robotics and Automation (ICRA’2000), pages 3841 – 3846, 2000.

[36] T. Duckett and U. Nehmzow. Experiments in evidence based localisation for a mobile robot. In D. Corne and J. L. Shapiro, editors, Proceedings of the AISB 97 workshop on Spatial Reasoning in Animals and Robots. Springer, 1997.

[37] T. Duckett and U. Nehmzow. Mobile robot self-localization and measurement of performance in middle scale environments. Robotics and Autonomous Systems, 1-2(24), 1998.

[38] G. Dudek and M. Jenkin. Computational Principles of Mobile Robotics. Cambridge University Press, 2000.

[39] G. Dudek and P. MacKenzie. Model-based map construction for robot localization. In Proceedings of Vision Interface 1993, 1993.

[40] S. Egerton and V. Callaghan. From mammals to machines : Towards a biologically inspired mapping model for autonomous mobile robots. In Procceding of the 6th International Conference on Intelligent Autonomous Systems (IAS-6), 2000.

[41] T. Einsele. Real-time self-localization in unknown indoor environments using a panorama laser range finder. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-97), pages 697–703, 1997.

[42] S. P. Engelson. Continuous map learning for mobile robots. Extended Abstract for the 3rd French-Israeli Symposium on Robotics, 1995.

[43] S. P. Engelson and D. V. McDermott. Error correction in mobile robot map learning. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA-92), 1992.

[44] H. Feder, J. Leonard, and C. Smith. Adaptive mobile robot navigation and mapping. International Journal of Robotics Research, 18(7) :650–668, 1999.

[45] D. Filliat and J.-A. Meyer. Map-based navigation in mobile robots - i. a review of localisation strategies. Journal of Cognitive Systems Research, submitted for publication, 2001.

[46] D. Fox, W. Burgard, F. Dellaert, and S. Thrun. Monte carlo localization : Efficient position estimation for mobile robots. In Proceedings of the Sixteenth National Conference on Artificial Intelligence (AAAI-99). AAAI, 1999.

[47] D. Fox, W. Burgard, and S. Thrun. The dynamic window approach to collision avoidance. IEEE Robotics and Automation Magazine, 4(1), 1997.

[48] D. Fox, W. Burgard, and S. Thrun. Markov localization for mobile robots in dynamic environments. Journalof Artificial Intelligence Research, 11, 1999.

[49] D. Fox, W. Burgard, S. Thrun, and A. B. Cremers. Position estimation for mobile robots in dynamic environments. In Proceedings of the Fifteenth National Conference on Articial Intelligence (AAAI-98), pages 983–988, 1998.

[50] Dieter Fox. Kld-sampling : Adaptive particle filters and mobile robot localization. In In Advances in Neural Information Processing Systems (NIPS, 2001.

[51] M. Franz, B. Scholkopf, P. Georg, H. Mallot, and H. Bulthoff. Learning view graphs for robot navigation. Autonomous Robots, 5 :111–125, 1998.

[52] A. Garulli, A. Giannitrapani, A. Rossi, and A. Vicino. Mobile robot slam for line-based environment representation. In Decision and Control, 2005 and 2005 European Control Conference. CDC-ECC’05. 44th IEEE Conference on, pages 2041–2046. IEEE, 2005.

[53] J. Gasós and A. Martín. Mobile robot localization using fuzzy maps. In T. Martin and A. Ralescu, editors, Fuzzy Logic in AI - Selected papers from the IJCAI ’95 Workshop, number 1188, pages 207–224. Springer-Verlag, 1997.

[54] P. Gaussier, C. Joulain, J.P. Banquet, S. Lepretre, and A. Revel. The visual homing problem : an example of robotics/biology cross-fertilisation. Robotics and autonomous systems, 30(1-2) :155–180, 2000.

[55] P. Gaussier, S. Leprêtre, C. Joulain, A. Revel, M. Quoy, and Banquet J. P. Animal and robot learning : experiments and models about visual navigation. In Proceedings of the Seventh European Workshop on Learning Robots, 1998.

[56] A. P. Georgopoulos, A. B. Schwartz, and R. E. Kettner. Neuronal population coding of movement direction. Science, (233) :1416–1419, 1986.

[57] J. Gomes-Mota and M. I. Ribeiro. Mobile robot localisation on reconstructed 3d models. Robotics and Autonomous Systems, 31(1-2) :17–30, 2000.

[58] S. Gourichon and J.-A. Meyer. Using colored snapshots for short-range guidance in mobile robots. International Journal of Robotics and Automation, submitted for publication, Special Issue on Biologically Inspired Robots, 2001.

[59] R. Greiner and R. Isukapalli. Learning to select useful landmarks. IEEE Transactions on Systems, Man, and Cybernetics-Part B,Special Issue on Learning Autonomous Robots, 26(3), 1996.

[60] G. Grisetti, C. Stachniss, and W. Burgard. Improving Grid-based SLAM with RaoBlackwellized Particle Filters by Adaptive Proposals and Selective Resampling. In Robotics and Automation, 2005. ICRA 2005. Proceedings of the 2005 IEEE International Conference on, pages 2432–2437, 2005.

[61] Giorgio Grisetti, Cyrill Stachniss, and Wolfram Burgard. Nonlinear constraint network optimization for efficient map learning. Trans. Intell. Transport. Sys., 10 :428–439, September 2009.

[62] L. J. Guibas, R. Motwani, and P. Raghavan. The robot localization problem. Algorithmic Foundations of Robotics, pages 269–282, 1995.

[63] J. Gutmann and K. Konolige. Incremental mapping of large cyclic environments. In Proceedingsof the IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA-2000), 2000.

[64] J. Gutmann and Kurt Konolige. Incremental mapping of large cyclic environments. In Proc. IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA), page 318–325, Monterey, California, 1999.

[65] J. S. Gutmann and C. Schlegel. Amos : Comparison of scan matching approaches for self-localization in indoor environments,. In Proceedings of the 1st Euromicro Workshop on Advanced Mobile Robots. IEEE Computer Society Press, 1996.

[66] V. V. Hafner. Learning places in newly explored environments. In J. A. Meyer, A. Berthoz, D. Floreano, H. L. Roiblat, and S. W. Wilson, editors, Sixth International Conference on simulation of adaptive behavior : From Animals to Animats (SAB-2000). Proceedings Supplement., pages 111–120. ISAB, 2000.

[67] R. I. Hartley and A. Zisserman. Multiple View Geometry in Computer Vision. Cambridge University Press, ISBN : 0521540518, second edition, 2004.

[68] P. Hébert, S. Betgé-Brezetz, and R. Chatila. Decoupling odometry and exteroceptive perception in building a global world map of a mobile robot : The use of local maps. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA-1996), pages 757–764, 1996.

[69] J. Hertzberg and F. Kirchner. Landmark-based autonomous navigation in sewerage pipes. In Proceedings of the First Euromicro Workshop on Advanced Mobile Robots. IEEE Computer Society Press, 1996.

[70] D. Hähnel, D. Fox, W. Burgard, and S. Thrun. A highly efficient fastslam algorithm for generating cyclic maps of large-scale environments from raw laser range measurements. In Proceedings of the Conference on Intelligent Robots and Systems (IROS), 2003.

[71] Daniel Ichbiah. Robots, Génèse d’un peuple artificiel. Minerva, 2005.

[72] I. Jebari, S. Bazeille, E. Battesti, H. Tekaya, M. Klein, A. Tapus, D. Filliat, C. Meyer, S. Ieng, R. Benosman, E. Cizeron, J.-C. Mamanna, and B. Pothier. Multi-sensor semantic mapping and exploration of indoor environments. In Proceedings of the 3rd International Conference on Technologies for Practical Robot Applications (TePRA), 2011.

[73] P. Jensfelt and S. Kristensen. Active global localisation for a mobile robot using multiple hypothesis tracking. In Proceedings of the IJCAI-99 Workshop on Reasoning with Uncertainty in Robot Navigation, 1999.

[74] S. Julier and J. Uhlmann. A new extension of the Kalman filter to nonlinear systems. In Int. Symp. Aerospace/Defense Sensing, Simul. and Controls, Orlando, FL, 1997.

[75] O. Karch and T. Wahl. Relocalization – theory and practice. Discrete Applied Mathematics : Special Issue on Computational Geometry, 93, 1999.

[76] Hee-Young Kim, Sung-On Lee, and Bum-Jae You. Robust laser scan matching in dynamic environments. In Proceedings of the 2009 international conference on Robotics and biomimetics, ROBIO’09, pages 2284–2289. IEEE Press, 2009.

[77] D. Kirsh. Today the earwig, tomorrow man ? Artificial Intelligence, 47 :161–184, 1991.

[78] Y. Koren and J. Borenstein. Histogramic in-motion mapping for mobile robot obstacle avoidance. IEEE Transaction on Robotics and Automation, 7(4) :535–539, 1991.

[79] D. Kortenkamp, M. Huber, F. Koss, W. Belding, J. Lee, A. Wu, C. Bidlack, and S. Rogers. Mobile robot exploration and navigation of indoor spaces using sonar and vision. In Proceedings of the AIAA/NASA Conference on Intelligent Robots in Field, Factory, Service, and Space (CIRFFSS 94), pages 509–519, 1994.

[80] D. Kortenkamp and T. Weymouth. Topological mapping for mobile robots using a combination of sonar and vision sensing. In Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), pages 979–984, Seattle, WA, 1994.

[81] B. J. Kuipers. The spatial semantic hierarchy. Artificial Intelligence, (119) :191–233, 2000.

[82] B. J. Kuipers and Y. T. Byun. A robot exploration and mapping strategy based on a semantic hierarchy of spatial representations. Robotics and Autonomous Systems, 8 :47–63, 1991.

[83] C. Kunz, T. Willeke, and I. Nourbakhsh. Automatic mapping of dynamic office environments. In In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA-97), volume 2, pages 1681–1687, 1997.

[84] A. Kurz. Alef : An autonomous vehicle which learns basic skills and construct maps for navigation. Robotics and Autonomous Systems, 14 :172–183, 1995.

[85] C. Kwok, D. Fox, and M. Meila. Adaptive real-time particle filters for robot localization. In Proc. of the IEEE International Conference on Robotics & Automation, 2003.

[86] D. Lambrinos, R. Möller, T. Labhart, R. Pfeifer, and R. Wehner. A mobile robot employing insect strategies for navigation. Robotics and Autonomous Systems, special issue : Biomimetic Robots, 30 :39–64, 2000.

[87] J.-C. Latombe. Robot Motion Planning. Boston : Kluwer Academic Publishers, Boston, 1991.

[88] J.-P. Laumond. Robot Motion Planning and Control. Lectures Notes in Control and Information Sciences 229. Springer, 1998.

[89] Steven M. Lavalle. Rapidly-exploring random trees : A new tool for path planning. Technical report, 1998.

[90] Steven M. LaValle. Planning Algorithms. Cambridge University Press, May 2006.

[91] J. J. Leonard and H. F. Durrant-Whyte. Simultaneous map building and localization for an autonomous mobile robot. pages 1442–1447, 1991.

[92] J. J. Leonard, H. F. Durrant-Whyte, and I. J. Cox. Dynamic map building for an autonomous mobile robot. International Journal of Robotics Research, 11(4) :89–96, 1992.

[93] T. S. Levitt and D. T. Lawton. Qualitative navigation for mobile robots. Artificial Intelligence, 44 :305–360, 1990.

[94] F. Lu and E. Milios. Globally consistent range scan alignment for environment mapping. Autonomous Robots, 4 :333–349, 1997.

[95] F. Lu and E. Milios. Globally consistent range scan alignment for environment mapping. Auton. Robots, 4 :333–349, October 1997.

[96] C. Madsen, C. Andersen, and J. rensen. A robustness analysis of triangulation-based robot self-positioning. In Proceedings of the 5th Symposium for Intelligent Robotics Systems, 1997.

[97] O. Martínez Mozos, R. Triebel, P. Jensfelt, A. Rottmann, and W. Burgard. Supervised semantic labeling of places using information extracted from sensor data. Robotics and Autonomous Systems, 55(5) :391–402, May 2007.

[98] M. J. Mataric. Integration of representation into goal-driven behaviour-based robots. IEEE Transactions on Robotics and Automation, 8(3) :304–312, 1992.

[99] P. S. Maybeck. Stochastic Models, Estimation and Control. Academic Press, 1979.

[100] M. Montemerlo, S. Thrun, D. Koller, and B. Wegbreit. FastSLAM : A factored solution to the simultaneous localization and mapping problem. In Proceedings of the AAAI National Conference on Artificial Intelligence, Edmonton, Canada, 2002. AAAI.

[101] H. Moravec and A. Elfes. High resolution maps from wide angular sensors. In Proceedings of the IEEE International Conference On Robotics and Automation (ICRA-85), pages 116–121, St. Louis, 1985. IEEE Computer Society Press.

[102] Hans Moravec. ROBOT : mere machine to transcendent mind. Oxford University Press, 1995.

[103] P. Moutarlier and R. Chatila. An experimental system for incremental environment modeling by an autonomous mobile robot. In Experimental Robotics 1, pages 327–346. SpringerVerlag, 1990.

[104] R. R. Murphy. Introduction to AI Robotics. The MIT Press, 2000.

[105] U. Nehmzow and C. Owen. Robot navigation in the real world : Experiments with manchester’s fortytwo in unmodified, large environments,. Robotics and Autonomous Systems, 33(4) :223–242, 2000.

[106] I. Nourbakhsh, R. Powers, and S. Birchfield. Dervish, an office navigating robot. AI Magazine, 16(2) :53–60, 1995.

[107] C. F. Olson. Probabilistic self-localization for mobile robots. IEEE Transactions on Robotics and Automation, 16(1), 2000.

[108] S. Oore, G. Hinton, and G. Dudek. A mobile robot that learns its place. Neural Computation, 9 :683–699, 1997.

[109] D. Gálvez-López P. Piniés, L. M. Paz and J.D. Tardós. Ci-graph slam for 3d reconstruction of large and complex environments using a multicamera system. International Journal of Field Robotics, September/October 2010.

[110] M. Piasecki. Global localization for mobile robots by multiple hypothesis tracking. Robotics and Autonomous Systems, 16 :93–104, 1995.

[111] T. J. Prescott. Spatial representation for navigation in animats. Adaptive Behavior, 4(2), 1995.

[112] Andrzej Pronobis. Semantic Mapping with Mobile Robots. PhD thesis, Royal Institute of Technology (KTH), Stockholm, Sweden, June 2011.

[113] D. Radhakrishnan and I. Nourbakhsh. Topological localization by training a vision-based transition detector. In Proceedings of the 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-99), 1999.

[114] A. Remazeilles and F. Chaumette. Image-based robot navigation from an image memory. Robotics and Autonomous Systems, 55(4), 2007.

[115] Nicholas Roy and Sebastian Thrun. Coastal navigation with mobile robots. In In Advances in Neural Processing Systems 12, pages 1043–1049, 1999.

[116] Thomas Röfer. Building consistent laser scan maps. In In Proc. of the 4th European Workshop on Advanced Mobile Robots (Eurobot 2001), volume 86 of Lund University Cognitive Studies, pages 83 ? 90, pages 83–90, 2001.

[117] A. Saffiotti and L. P. Wesley. Perception-based self-localization using fuzzy locations. In Reasoning with Uncertainty in Robotics, volume 1093 of Lecture Notes in Computer Science. Springer-Verlag, 1995.

[118] S. Schaal, C. G. Atkeson, and S. Vijayakumar. Real-time robot learning with locally weighted statistical learning. In International conference on robotics and automation (icra2000), 2000.

[119] B. Schiele and J. Crowley. A comparison of position estimation techniques using occupancy grids. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA-94), pages 1628–1634, 1994.

[120] B. Scholkopf and H. A. Mallot. View-based cognitive mapping and path planning. Adaptive Behavior, 3(3) :311–348, 1995.

[121] M. J. Schoppers. Universal plans for reactive robots in unpredictable environments. In Proceedings of the 10th International Joint Conference on Artificial Intelligence (IJCAI 87), pages 1039–1046, Milan, Italy, 1987.

[122] A. C. Schultz and W. Adams. Continuous localization using evidence grids. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA-98), pages 2833–2839, 1998.

[123] S. Segvic, A. Remazeilles, A. Diosi, and F. Chaumette. A mapping and localization framework for scalable appearance-based navigation. Computer Vision and Image Understanding, 113(2) :172–187, February 2009.

[124] P. E. Sharp. Computer simulation of hippocampal place cells. Psychobiology, 19(2) :103–115, 1991.

[125] H. Shatkay and L. P. Kaelbling. Learning topological maps with weak local odometric information. In Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, 1997.

[126] R. Sim and G. Dudek. Learning visual landmarks for pose estimation. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA-1999), 1999.

[127] R. Simmons and S. Koenig. Probabilistic navigation in partially observable environments. In S. Mellish, editor, Proccedings of IJCAI’95, Montreal,Canada, 1995. Morgan Kaufman Publishing.

[128] Danijel Skocaj, Horst Bischof, and Ales Leonardis. A robust pca algorithm for building representations from panoramic images. In Proceedings of the 7th European Conference on Computer Vision-Part IV, ECCV ’02, pages 761–775, London, UK, UK, 2002. SpringerVerlag.

[129] R. Smith, M. Self, and P. Cheeseman. Estimating uncertain spatial relationships in robotics. In J. F. Lemmer and L. N. Kanal, editors, Uncertainty in Artificial Intelligence, pages 435–461. Elsevier, 1988.

[130] G. Theocharous, K. Rohanimanesh, and S. Mahadevan. Learning hierarchical partially observable markov decision processes for robot navigation. In Proceedings of the IEEE Conference on Robotics and Automation, 2001.

[131] S. Thrun. Learning metric-topological maps for indoor mobile robot navigation. Artificial Intelligence, 99(1) :21–71, 1999.

[132] S. Thrun. Probabilistic algorithms in robotics. AI Magazine, 21(4) :93–109, 2000.

[133] S. Thrun, M. Bennewitz, W. Burgard, A. B. Cremers, F. Dellaert, D. Fox, D. Haehnel, C. Rosenberg, N. Roy, J. Schulte, and D. Schulz. Minerva : A second generation mobile tourguide robot. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA-1999), 1999.

[134] S. Thrun, W. Burgard, and D. Fox. A real-time algorithm for mobile robot mapping with applications to multi-robot and 3d mapping. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA-2000), 2000.

[135] Sebastian Thrun, Wolfram Burgard, and Dieter Fox. Probabilistic Robotics (Intelligent Robotics and Autonomous Agents series). Intelligent robotics and autonomous agents. The MIT Press, 2005.

[136] Nicola Tomatis, Illah R. Nourbakhsh, and Roland Siegwart. Hybrid simultaneous localization and map building : a natural integration of topological and metric. Robotics and Autonomous Systems, 44(1) :3–14, 2003.

[137] D. S. Touretzky, H. S. Wan, and A. D. Redish. Neural representations of space in rats and robots. In J. M. Zurada, R. J. Marks, and C. J. Robinson, editors, Computational Intelligence : Imitating Life, pages 57–68. IEEE Press, 1994.

[138] O. Trullier and J. A. Meyer. Biomimetic navigation models and strategies in animats. AI Communications, 10 :79–92, 1997.

[139] O. Trullier and J. A. Meyer. Animat navigation using a cognitive graph. Biological Cybernetics, 83(3) :271–285, 2000.

[140] O. Trullier, S. Wiener, A. Berthoz, and J. A. Meyer. Biologically-based artificial navigation systems : Review and prospects. Progress in Neurobiology, 51 :483–544, 1997.

[141] I. Ulrich and I. Nourbakhsh. Appearance-based place recognition for topological localization. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA-2000), 2000.

[142] G. Von Wichert. Mobile robot localization using a self-organised visual environment representation. Robotics and Autonomous Systems, 25 :185–194, 1998.

[143] Chieh-Chih Wang, Charles Thorpe, Sebastian Thrun, Martial Hebert, and Hugh DurrantWhyte. Simultaneous localization, mapping and moving object tracking. The International Journal of Robotics Research, 26(9) :889–916, September 2007.

[144] O. Wijk and H. I. Christensen. Localization and navigation of a mobile robot using natural point landmarks extracted from sonar data. Robotics and Autonomous Systems, 31(1-2) :31–42, 2000.

[145] B. Yamauchi and R. Beer. Spatial learning for navigation in dynamic environments. IEEE Transactions on Systems, Man, and Cybernetics-Part B,Special Issue on Learning Autonomous Robots, 26(3) :496–505, 1996.

[146] B. Yamauchi and P. Langley. Place recognition in dynamic environments. Journal of Robotic Systems, Special Issue on Mobile Robots, 14(2) :107–120, 1997.

[147] B. Yamauchi, A. Schultz, and W. Adams. Integrating exploration and localization for mobile robots. Adaptive Behavior, 7(2) :217–230, 1999.


précédentsommaire

Vous avez aimé ce tutoriel ? Alors partagez-le en cliquant sur les boutons suivants : Viadeo Twitter Facebook Share on Google+   

  

Licence Creative Commons
Le contenu de cet article est rédigé par David Filliat et est mis à disposition selon les termes de la Licence Creative Commons Attribution - Pas d'Utilisation Commerciale - Partage dans les Mêmes Conditions 3.0 non transposé.
Les logos Developpez.com, en-tête, pied de page, css, et look & feel de l'article sont Copyright © 2016 Developpez.com.