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Non-linear multimodal object tracking based on 2d lidar data

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The contribution introduces a novel approach for tracking objects based on two-dimensional lidar data. As a central tracking engine, we employ a particle-filter-based solution which is capable of modelling non-linear dynamic processes as well as non-Gaussian noise distributions for the underlying process and sensor as well. In contrast to other lidar-based tracking approaches, no newly detected objects have to be associated to already known objects in an explicit manner. Since our weighting function is multi-modal, the association is done by the filter itself.
Słowa kluczowe
Rocznik
Strony
359--369
Opis fizyczny
Bibliogr. 12 poz., rys., wykr., wzory
Twórcy
autor
  • Institut für Industrielle Informationstechnik, Karlsruhe Institute of Technology, Hertzstrasse 16, D-76187 Karlsruhe, Germany, thuy@iiit.uni-karlsruhe.de
Bibliografia
  • [1] C. Hoffman, T. Dang, C. Stiller: “Vehicle detection fusing 2D visual features”. IEEE Intelligent Vehicles Symposium, June 2004, pp. 280-285.
  • [2] T. Dang: “An iterative parameter estimation method for observation models with nonlinear constraints”. Metrol Meas Syst, vol. 15, no. 4, 2008, pp. 421-432.
  • [3] S. Kammel, J. Ziegler, B. Pitzer, M. Werling, T. Gindele, D. Jagzent, J. Schröder, M. Thuy, M. Goebl, F. von Hundelshausen, O. Pink, C. Frese, C. Stiller: “Team Annieway’s autonomous system for the DARPA Urban Challenge 2007”. International Journal of Field Robotics Research, vol. 25, no. 9, 2008, pp. 615-639.
  • [4] M. Thuy, A. Saber Tehrani, F. Puente León: “Bayessche Fusion von Stereobildfolgen und Lidardaten”. Bildverarbeitung in der Mess- und Automatisierungstechnik. VDI-Berichte, VDI Verlag, Düsseldorf, 2007, pp. 67-78.
  • [5] S. Wender K. Dietmayer: “A feature level fusion approach for object classification”. IEEE Intelligent Vehicles Symposium, June 2007, pp. 1132-1137.
  • [6] A. Mendes, L. Bento, U. Nunes: “Multi-target detection and tracking with a laser scanner”. IEEE Intelligent Vehicles Symposium, June 2004, pp. 796-801.
  • [7] M. Thuy, F. Puente León: “Non-linear, shape independent object tracking based on 2D lidar data”. IEEE Intelligent Vehicles Symposium, June 2009, pp. 532-537.
  • [8] M. Marron, J. Garcia, M. Sotelo, D. Fernandez, D. Pizarro: “xpfcp”: An extended particle filter for tracking multiple and dynamic objects in complex environments”. IEEE/RSJ International Conference on Intelligent Robots and Systems, Aug. 2005, pp. 2474-2479.
  • [9] E.B. Koller-Meier, F. Ade: “Tracking multiple objects using the condensation algorithm”. Robotics and Autonomous Systems, vol. 31, 2001, pp. 93-105.
  • [10] M. Marron, J. Garcia, M. Sotelo, M. Cabello, D. Pizarro, F. Huerta, J. Cerro: “Comparing a Kalman filter and a particle filter in a multiple objects tracking application”. IEEE International Symposium on Intelligent Signal Processing, Oct. 2007, pp. 1-6.
  • [11] M. Goebl, M. Althoff, M. Buss, G. Farber, F. Hecker, B. Heissing, S. Kraus, R. Nagel, F. Puente León, F. Rattei, M. Russ, M. Schweitzer, M. Thuy, C. Wang, H. Wuensche: “Design and capabilities of the munich cognitive automobile”. IEEE Intelligent Vehicles Symposium, June 2008, pp. 1101-1107.
  • [12] M. Thuy, M. Althoff, M. Buss, K. Diepold, J. Eberspächer, G. Färber, M. Goebl, B. Heißing, S. Kraus, R. Nagel, Y. Naous, F. Obermeier, F. Puente León, F. Rattei, C. Wang, M. Schweitzer, H.-J. Wünsche: “Cognitive Automobiles - new concepts and ideas of the transregional collaborative research centre TR-28”. Aktive Sicherheit durch Fahrerassistenz, Garching, Germany, April 2008.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BSW1-0059-0002
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