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On Semantic Support System for USAR operations with mobile robots

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Języki publikacji
EN
Abstrakty
EN
This paper describes the design and the basic implementation of a Semantic Support System (SSS) for Urban Search and Rescue (USAR) operations. The system is intended for use by rescue teams equipped with mobile robots. The goal of the work is to provide the rescue team with a global operational picture that ensures proper information availability. The core of the system is a semantic model of the environment based on Qualitative Spatio-Temporal Representation and Reasoning (QSTRR)[1] framework. Thus, the ontology of the semantic model is described. The ontology is based on Humanitarian Data Model enhanced by the robot`s information. SSS is designed to work with multiple data sources: Geographic Information System (GIS), 3D point clouds, camera images etc. The article describes,as an example, the results of building the semantic model from 3D point clouds. An example of qualitative reasoning based on the semantic model is shown.
Rocznik
Strony
3--8
Opis fizyczny
Bibliogr. 15 poz., rys.
Twórcy
autor
  • Institute of Mathematical Machines, Warsaw
Bibliografia
  • [1] J. Będkowski, Intelligent Mobile Assistant for Spatial Design Support, Journal of Automation in Construction (2013), pp. 177-186 DOI information: 10.1016/ j.autcon.2012.09.009
  • [2] I. Abi-Zeid, J. R. Frost, SARPlan: A decision support system for Canadian Search and Rescue Operations, European Journal of Operational Research, Volume 162, Issue 3, 1 May 2005, Pages 630-653, ISSN 0377-2217, http://dx.doi.org/10.1016/j.ejor.2003.10.029
  • [3] Y. Weihong; X. Jinkai, Intelligent Decision Support System of Maritime Search and Rescue Based on JADE, E-Product E-Service and E-Entertainment (ICEEE), 2010 International Conference on , vol., no., pp.1,4, 7-9 Nov. 2010
  • [4] B. Ott, K. Sauer, A Wägli, SARFOS - Search And Rescue Forward Operation Support System, Proceedings of ENC-GNSS 2005
  • [5] Q. Hamp, O. Gorgis, P. Labenda, M. Neumann, T. Predki, L. Heckes, A. Kleiner, L. M. Reindi, Study of efficiency of USAR operations with assistive technologies, Advanced Robotics, vol. 17(5), 2013
  • [6] A. Nüchter, J. Hertzberg ,Towards semantic maps for mobile robots, Robotics and Autonomous Systems Volume 56 Issue 11, November, 2008 , 915-926
  • [7] J. Będkowski, A. Masłowski, Application of semantic maps for mobile robot simulation, Elektronika 9/2011
  • [8] I. Nourbakhsh, K. Sycara, M. Koes, M. Yong, M. Lewis, S. Burion ,Human-Robot Teaming for Search and Rescue, IEEE Pervasive Computing: Mobile and Ubiquitous Systems, January, 2005, 72-78
  • [9] S. Keshavdas, H. Zender, G.J. Kruijff, M. Liu, F. Colas, FKILT– Functional Mapping: Spatial Inferencing to aid Human-Robot Rescue Efforts in Unstructured Disaster Environments,Proceedings of the 2012 AAAI Spring Symposium on Designing Intelligent Robots, AAAI Press, 2012
  • [10] http://wiki.openstreetmap.org/wiki/Humanitarian_OSM_Tags#HDM_presets
  • [11] Randell, D. A., Cui, Z. and Cohn, A. G.: A spatial logic based on regions and connection, Proc. 3rd Int. Conf. on Knowledge Representation and Reasoning, Morgan Kaufmann, San Ma - teo, pp. 165–176, 1992.
  • [12] Janusz Marian Bedkowski, Andrzej Maslowski, Geert De Cubber, Real time 3D localization and mapping for USAR robotic application, Industrial Robot: An International Journal, Vol. 39 Issue: 5, 2012
  • [13] J. Będkowski, K. Majek, A. Masłowski, P. Kaczmarek: Recognition of 3D objects for walking robot equipped with Multisense- SL sensor head” 16th International Conference on Climbing and Walking Robots, 14-17 July 2013, University of Technology, Sydney, Australia.
  • [14] A.Velizhev, R.Shapovalov, K.Schindler, Implicit shape models for object detection in 3D point clouds, International Society of Photogrammetry and Remote Sensing Congress, 2012
  • [15] B. Siemiatkowska, Coordinating the motion of mobile robots using cellular neural network, Journal of Automation, Mobile Robotics and Intelligent Systems 2 (2) (2008) 65–69.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-3abaa2c7-13c8-4262-bbb8-fecf7e2711f7
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