Presenting a technique for registering images and range data using a topological representation of a path within an environment

• Autorzy: Ferreira F. , Davim L. , Rocha R. , Dias J. , Santos V.
• Języki publikacji: EN

Abstrakty

EN

This article presents a novel method to the utilize topological representation of a path, thatpath that is created from sequences of images from digital cameras and sensor data from range sensors. A topological representation of the environment is created by leading the robot around the environment during a familiarisation phaseLeading the robot around the environment during a familiarisation phase creates a topological representation of the environment. While moving down the same path, the robot is able to localise itself within the topological representation that is has been previously created. The principal contribution to the state of the art is that, by using a topological representation of the environment, individual 3D data sets acquired from a set of range sensors need not be registered in a single, [Global] Coordinate Reference System. Instead, 3D point clouds for small sections of the environment are indexed to a sequence of multi-sensor views, of images and range data. Such a registration procedure can be useful in the construction of 3D representations of large environments and in the detection of changes that might occur within these environments.

Słowa kluczowe

EN

sensor feature integration; binary data; Bernoulli mixture model; dimensionality reduction; robot localisation; change detection

• Wydawca: Łukasiewicz Industrial Research Institute for Automation and Measurements PIAP
• Czasopismo: Journal of Automation Mobile Robotics and Intelligent Systems
• Rocznik: 2007
• Tom: Vol. 1, No. 3
• Strony: 47--56
• Opis fizyczny: Bibliogr. 37 poz., rys.

Twórcy

autor

Ferreira F.

autor

Davim L.

autor

Rocha R.

autor

Dias J.

autor

Santos V.

• Institute of Systems and Robotics, University of Coimbra, 3030-290 Portugal,

Bibliografia

• [1] H. Andreasson and T. Duckett, "Topological Localization For Mobile Robots Using Omni-Directional Vision And Local Features". In: 5th IFAC/EURON Symposium on Intelligent Autonomous Vehicles, Instituto Superior Tenico, Lisboa, Portugal, July 2004. IFAC/EURON.
• [2] N. Vlassis, Y. Motomura, and B. Kröse, "Supervised linear feature extraction for mobile robot localization". In: Proc. IEEE Int. Conf. on Robotics and Automation, 2000, pages 2979-2984.
• [3] A. Tapus, N. Tomatis, and R. Siegwart, "Topological Global Localization and Mapping with Fingerprints and Uncertainty". In: 9th International Symposium on Experimental Robotics, ISER, 2004.
• [4] A. Elfes, "Sonar-based real-world mapping and navigation", IEEE Journal of Robotics and Automation, vol. 3, issue. 3, June 1987, pp. 249-265.
• [5] R. Rocha, Building Volumetric Maps with Cooperative Mobile Robots and Useful Information Sharing. PhD thesis, University of Porto, Department of Engineering, 2005.
• [6] M. Drumheller, "Mobile robot localisation using sonar", IEEE Transactions On Pattern Analysis And Machine Intelligence, vol. 9, issue 2, March 1987, 325332.
• [7] B. J. Kuipers, "The Spatial Semantic Hierarchy", Artificial Intelligence, no. 119, 2000, pp. 191233. Available at: http://www.cs.utexas.edu/users/qr/papers/ Kuipers-aij-00.html.
• [8] S. Thrun, "Learning metric-topological maps for indoor mobile robot localization", Artificial Intelligence, issue 99(1), 1998, pp. 21-71.
• [9] I.J Cox. Blanche-an experiment in guidance and navigation of an autonomous robot vehicle. IEEE Transactions on Robotics and Automation, vol. 7, issue 2, April 1991, 193-204.
• [10] V. Nguyen, A. Martinelli, N. Tomatis, and R. Siegwart, "A comparison of line extraction algorithms using 2d laser rangefinder for indoor mobile robotics". In: International Conference on Intelligent Robots and Systems, 2005.
• [11] D. Sack and W. Burgard, "A comparison of methods for line extraction from range data". In: IAV 2004, 2004.
• [12] D. Manandhar and R. Shibasaki, "Feature extraction from range data". In: ACRS 2001 - 22nd Asian Conference on Remote Sensing, Singapore, November 2001, volume 2, pages 1113-1118.
• [13] Z. Xiang, V.M. F. Santos, and J. Liu, "Locating And Crossing Doors And Narrow Passages For A Mobile Robot". In: First Int. Conf. on Informatics in Control, Automation and Robotics (ICINCO), 2004.
• [14] J, Fellers, S, Lee, N, M. Amato, "Localization based on Visibility Sectors using Range Sensors". In: Procceedings of the IEEE Int. Conference Robot. Autom. (ICRA),January 2000, pages 3505-3511.
• [15] R. C. Gonzalez and R. E. Woods, Digital Image Processing, Addison-Wesley Pub. Co, 2002.
• [16] S. Baker, Design and Evaluation of Feature Detectors. PhD thesis, Columbia University, 1998.
• [17] J. J. Koenderink, "The Structure Of Images", Biological Cybernetics, vol. 50, no. 5, 1984, pp. 363-370.
• [18] A.P. Witkin, "Scale-space filtering". In: Proc. 8th Joint conference on Artificial Intelligence, Karlsruhe, W. Germany, 1983, pages 1019-1023.
• [19] T. Lindeberg, Scale-Space Theory in Computer Vision, Kluwer Academic Press, 1994.
• [20] D. G. Lowe, "Object Recognition from Local Scale-Invariant Features". In: Proc. of the International Conference on Computer Vision, Corfu, 1999, pages 1150-1157.
• [21] A. Pope and D. G. Lowe, "Probabilistic Models of Appearance for 3-D Object Recognition", International Journal of Computer Vision, vol. 40, no. 2, 2000, pp.149-167.
• [22] D. G. Lowe, "Local Feature View Clustering for 3D Object Recognition". In: Proceeding of the IEEE Conference on Computer Vision and Pattern Recognition, Kauai, Hawaii, 2001, pages 682-688.
• [23] M. Brown and D. G. Lowe, "Recognising Panoramas". In: 10th International Conference on Computer Vision (ICCV 2003), October 2003.
• [24] Y. Ke, R. Sukthankar, and L. Huston, "An efficient partsbased near-duplicate and sub-image retrieval system". In: MULTIMEDIA'04: Proceedings of the 12th annual ACM international conference on Multimedia, New York, USA, 2004. ACM Press, pages 869-876.
• [25] D. M. Bradley, R. Patel, N. Vandapel, and S. M. Thayer, "Real-Time Image-Based Topological Localization in Large Outdoor Environments". In: Proceedings of the 2005 IEEE Conf. on Intelligent Robotics and Systems, August 2005.
• [26] M. B. Kennel, KDTREE 2: Fortran 95 and C++ software to efficiently search for near neighbors in a multi-dimensional Euclidean space, 2004.
• [27] T. G. Dietterich, Machine learning for sequential data: A review. Technical report, Oregon State University, 2002.
• [28] F. Ferreira, V. Santos, and J. Dias, "A topological path layout for autonomous navigation of multi-sensor robots",International Journal of Factory Automation,Robotics and Soft Computing, no. 1, 2007, pp. 203-215.
• [29] Sajama and Alon Orlitsky, "Supervised dimensionality reduction using mixture models". In: Proceedings of the 22 nd International Conference on Machine Learning,Bonn, Germany, 2005.
• [30] G. McLachlan and D. Peel, Finite Mixture Models, John Wiley and Sons, 2000.
• [31] A. Kaban and M. Girolami, "Initialized and Guided EMClustering of Sparse Binary Data with Application to Text Based Documents". In: Proceedings of the 15th International Conference on Pattern Recognition (ICPR'00), volume 2, 2000.
• [32] X. Wang and A. Kaban, "Finding Uninformative Features in Binary Data". In: Sixth International Conference on Intelligent Data Engineering and Automated Learning (IDEAL '05), 2005.
• [33] A. Juan and E. Vidal, "Bernoulli Mixture Models for Binary Images". In: International Conference on Pattern Recognition (ICPR'04), volume 3, 2004, pages 367-370.
• [34] J. García-Hernández, V. Alabau, A. Juan, and E. Vidal, "Bernoulli mixture-based classification". In: A. R. Figueiras- Vidal , ed., , ISBN 84-688-8453-7, Elche (Spain), October 2004.
• [35] J. Pylkkönen and M. Kurimo, "Duration modeling techniques for continuous speech recognition". In: 8th International Conference on Spoken Language Processing (Interspeech 2004), Jeju Island, Korea, 2004, pages 385-388.
• [36] B. Juang, L. Rabiner, and S. Levinson M. Sondhi, "Recent developments in the application of hidden markov models to speaker-independent isolated word recognition". In: IEEE International Conference on Acoustics,Speech, and Signal Processing, ICASSP '85, vol. 10, 1985, pages 9-12.
• [37] M. Kaess, R.C. Arkin, and J. Rossignac, "Compact encoding of robot-generated 3D maps for efficient wireless transmission". In: IEEE Intl. Conf. on Advanced Robotics,ICAR, Coimbra, Portugal, June 2003, pages 324-331.