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"Semantic simulation engine" for mobile robotic applications

Treść / Zawartość
Identyfikatory
Warianty tytułu
PL
System symulacji semantycznej dla aplikacji robotów mobilnych
Konferencja
Konferencja Automation 2011 (06-08.04.2011 ; Warszawa, Polska)
Języki publikacji
EN
Abstrakty
EN
In the paper the "Semantic Simulation Engine" dedicated for mobile robotics applications is shown. Presented software performs mobile robot simulation in virtual environment built from real 3D data that is transformed into semantic map. Data acquisition is done by real mobile robot PIONEER 3AT equipped with 3D laser measurement system. Semantic map building method and its transformation into simulation model (NVIDIA PhysX) is described. The modification of ICP (Iterative Closest Point) algorithm for data registration based on processor GPGPU CUDA (Compute Unified Device Architecture) is shown. The semantic map definition is given including the set of semantic entities and set of relations between them. Methods for localization and identification of semantic entities in 3D cloud of points based on image processing techniques are described. Results and examples of semantic simulation are shown.
PL
W pracy przedstawiono system symulacji semantycznej "Semantic Simulation Engine" dedykowany aplikacjom robotów mobilnych. Oprogramowanie realizuje symulację robota mobilnego poruszającego się w wirtualnym środowisku powstałym na bazie rzeczywistych pomiarów 3D przekształconych w mapę semantyczną. Pomiary dokonane są z wykorzystaniem rzeczywistego autonomicznego robota mobilnego klasy PIONEER 3AT wyposażonego w laserowy system pomiarowy 3D. Przedstawiono metodę budowy mapy semantycznej oraz metodę transformacji tej mapy do modelu symulacyjnego (NVIDIA PhysX). Przedstawiono autorską modyfikację algorytmu ICP (Iterative Closest Point) zastosowaną do dopasowywania dwóch chmur punktów 3D z wykorzystaniem procesora GPGPU CUDA (Compute Unified Device Architecture). Przedstawiono założenia mapy semantycznej, w tym zbiór podstawowych elementów semantycznych oraz relacji między nimi. Omówiono autorskie metody lokalizowania oraz identyfikacji elementów semantycznych w chmurze punktów 3D z zastosowaniem technik przetwarzania obrazów. Pokazano przykłady działania opracowanego systemu symulacji semantycznej.
Rocznik
Strony
333--343
Opis fizyczny
CD, Bibliogr. 35 poz., fot., rys.
Twórcy
  • Instytut Automatyki i Robotyki, Politechnika Warszawska
Bibliografia
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  • 2. A. Nüchter, H. Surmann, J. Hertzberg, Automatic model refinement for 3D reconstruction with mobile robots, in: Fourth International Conference on 3-D Digital Imaging and Modeling 3DIM 03, 2003, p. 394.
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  • 4. A. Nüchter, O. Wulf, K. Lingemann, J. Hertzberg, B. Wagner, H. Surmann, 3D mapping with semantic knowledge, in: IN ROBOCUP INTERNATIONAL SYMPOSIUM, 2005, pp. 335-346.
  • 5. A. Nüchter, J. Hertzberg, Towards semantic maps for mobile robots, Robot. Auton. Syst. 56 (11) (2008), pp. 915-926.
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  • 7. A. Nüchter, H. Surmann, K. Lingemann, J. Hertzberg, Semantic scene analysis of scanned 3D indoor environments, in: Proceedings of the Eighth International Fall Workshop on Vision, Modeling, and Visualization (VMV 03), 2003.
  • 8. H. Cantzler, R. B. Fisher, M. Devy, Quality enhancement of reconstructed 3D models using coplanarity and constraints, in: Proceedings of the 24th DAGM Symposium on Pattern Recognition, Springer-Verlag, London, UK, 2002, pp. 34-41.
  • 9. M. A. Fischler, R. Bolles, Random sample consensus. a paradigm for model fitting with apphcahons to image analysm and automated cartography, in: Proc. 1980 Image Understanding Workshop (College Park, Md., Apr i980) L. S. Baurnann, Ed, Scmnce Apphcatlons, McLean, Va., 1980, pp. 71-88.
  • 10. M. Eich, M. Dabrowska, F. Kirchner, Semantic labeling: Classification of 3D entities based on spatial feature descriptors, in: IEEE International Conference on Robotics and Automation (ICRA2010) in Anchorage, Alaska, May 3, 2010.
  • 11. N. Vaskevicius, A. Birk, K. Pathak, J. Poppinga, Fast detection of polygons in 3D point clouds from noise-prone range sensors, in: IEEE International Workshop on Safety, Security and Rescue Robotics, SSRR, IEEE, Rome, 2007, pp. 1-6.
  • 12. H. Andreasson, R. Triebel, W. Burgard, Improving plane extraction from 3D data by fusing laser data and vision, in: Proceedings of the 20 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2005, pp. 2656-2661.
  • 13. J. Oberlander, K. Uhl, J. M. Zollner, R. Dillmann, A region-based slam algorithm capturing metric, topological, and semantic properties, in: ICRA’08, 2008, pp. 1886-1891.
  • 14. B. Williams, I. Reid, On combining visual slam and visual odometry, in: Proc. International Conference on Robotics and Automation, 2010.
  • 15. L. Pedraza, G. Dissanayake, J. V. Miro, D. Rodriguez-Losada, F. Matia, Bs-slam: Shaping the world, in: Proceedings of Robotics: Science and Systems, Atlanta, GA, USA, 2007.
  • 16. M. Magnusson, H. Andreasson, A. Nüchter, A. J. Lilienthal, Automatic appearancebased loop detection from 3D laser data using the normal distributions transform, Journal of Field Robotics 26 (11–12) (2009), p. 892-914.
  • 17. P. J. Besl, H. D. Mckay, A method for registration of 3-d shapes, Pattern Analysis and Machine Intelligence, IEEE Transactions on 14 (2) (1992), 239-256.
  • 18. D. Hahnel, W. Burgard, Probabilistic matching for 3D scan registration, in: Proc. of the VDI - Conference Robotik 2002 (Robotik), 2002.
  • 19. M. Magnusson, A. Nüchter, C. Lörken, A. J. Lilienthal, J. Hertzberg, Evaluation of 3D registration reliability and speed - a comparison of icp and ndt, in: Proc. IEEE Int. Conf. on Robotics and Automation, 2009, pp. 3907-3912.
  • 20. R. B. Rusu, Z. C. Marton, N. Blodow, M. Dolha, M. Beetz, Towards 3D point cloud based object maps for household environments, Robot. Auton. Syst. 56 (11) (2008), pp. 927-941.
  • 21. J. Craighead, R. Murphy, J. Burke, B. Goldiez, A survey of commercial and open source unmanned vehicle simulators, in: Proceedings of ICRA, 2007.
  • 22. A. Boeing, T. Braunl, Evaluation of real-time physics simulation systems, in: GRAPHITE ‘07: Proceedings of the 5th international conference on Computer graphics and interactive techniques in Australia and Southeast Asia, ACM, New York, NY, USA, 2007, pp. 281-288.
  • 23. J. Wang, M. Lewis, J. Gennari, Usar: A game-based simulation for teleoperation, in: Proceedings of the 47th Annual Meeting of the Human Factors and Ergonomics Society, Denver, CO, Oct. 13-17, 2003.
  • 24. J. Wang, M. Lewis, J. Gennari, A game engine based simulation of the nist urban search and rescue arenas, in: Proceedings of the 35th conference on Winter simulation: driving innovation, December 07-10, New Orleans, Louisiana, 2003.
  • 25. R. B. Rusu, A. Maldonado, M. Beetz, I. A. Systems, T. U. Mnchen, Extending player/stage/gazebo towards cognitive robots acting in ubiquitous sensor-equipped environments, in: Accepted for the IEEE International Conference on Robotics and Automation (ICRA) Workshop for Network Robot System, 2007, April 14, 2007.
  • 26. L. Hohl, R. Tellez, O. Michel, A. J. Ijspeert, Aibo and Webots: Simulation, Wireless Remote Control and Controller Transfer, Robotics and Autonomous Systems 54 (6) (2006), pp. 472-485.
  • 27. T. Petrinic, E. Ivanjko, I. Petrovic, Amorsim a mobile robot simulator for Matlab, in: Proceedings of 15th International Workshop on Robotics in Alpe-Adria-Danube Region, June 15-17, Balatonfred, Hungary, 2006.
  • 28. C. Buckhaults, Increasing computer science participation in the first robotics competition with robot simulation, in: ACMSE 47: Proceedings of the 47th Annual Southeast Regional Conference, ACM, New York, NY, USA, 2009, pp. 1-4.
  • 29. J. Craighead, R. Murphy, J. Burke, B. Goldiez, A robot simulator classification system for hri, in: Proceedings of the 2007 International Symposium on Collaborative Technologies and Systems (CTS 2007), 2007, pp. 93-98.
  • 30. J. Craighead, J. Burke, R. Murphy, Using the unity game engine to develop sarge: A case study, in: Proceedings of the 2008 Simulation Workshop at the International Conference on Intelligent Robots and Systems (IROS 2008), 2008.
  • 31. J. Craighead, Distributed, game-based, intelligent tutoring systems the next step in computer based training?, in: Proceedings of the International Symposium on Collaborative Technologies and Systems (CTS 2008), 2008.
  • 32. http://opencv.willowgarage.com/wiki/
  • 33. S.-W. Lee, Y. J. Kim, Direct extraction of topographic features for gray scale character recognition, IEEE Trans. Pattern Anal. Mach. Intell. 17 (7) (1995) 724-729.
  • 34. L. Wang, T. Pavlidis, Direct gray-scale extraction of features for character recognition, IEEE Trans. Pattern Anal. Mach. Intell. 15 (10) (1993), pp. 1053-1067.
  • 35. J. Bedkowski, M. Kacprzak, A. Kaczmarczyk, P. Kowalski, P. Musialik, A. Maslowski, T. Pichlak, Rise mobile robot operator training design, in: 15th International Conference on Methods and Models in Automation and Robotics (CD-ROM), Miedzyzdroje, Poland, 2010.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BSW1-0098-0023
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