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A collision avoidance algorithm in Simultaneous Localization and Mapping problem for mobile platforms

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Języki publikacji
EN
Abstrakty
EN
A collision avoidance algorithm applicable in simultaneous localization and mapping (SLAM) has been developed with a prospect of an on-line application for mobile platforms to search and map the operation area and avoid contact with obstacles. The algorithm, which was implemented in MATLAB software, is based on a linear discrete-time state transition model for determination of the platform position and orientation, and a ‘force’ points method for collision avoidance and definition of the next-step of platform motion. The proposed approach may be incorporated into real-time applications with limited on-board computational resources.
Słowa kluczowe
Rocznik
Strony
317--328
Opis fizyczny
Bibliogr 12 poz., rys., tab.
Twórcy
  • Łukasiewicz Research Network – Institute of Aviation, Engineering Design Center, Warsaw, Poland
  • Warsaw University of Technology, Faculty of Power and Aeronautical Engineering, Warsaw, Poland
Bibliografia
  • 1. Bailey T., Durrant-Whyte H., 2006, Simultaneous localization and mapping (SLAM): Part II, IEEE Robotics and Automation Magazine, 13, 3, 108-117.
  • 2. Castellanos J.A., Neira J., Tardós J.D., 2004, Limits to the consistency of EKF-based SLAM, IFAC Proceedings Volumes (IFAC-PapersOnline), 37, 8,.
  • 3. Dissanayake M.W.M.G., Newman P., Clark S., Durrant-Whyte H.F., Csorba M., 2001, A solution to the simultaneous localization and map building (SLAM) problem, IEEE Transactions on Robotics and Automation, 17, 3, 229-241.
  • 4. Durrant-Whyte H., Bailey T., 2006, Simultaneous localization and mapping: Part I, IEEE Robotics and Automation Magazine, 13, 2, 99-110.
  • 5. Fan X., Guo Y., Liu H., Wei B., Lyu W., 2020, Improved artificial potential field method applied for AUV path planning, Mathematical Problems in Engineering, 2020, 1, 1-21.
  • 6. Julier S.J., Uhlmann J.K., 2001, A counter example to the theory of simultaneous localization and map building, Proceedings of the IEEE International Conference on Robotics and Automation, 4, 4238-4243.
  • 7. Leonard J.J., Feder H.J.S., 2001, Decoupled stochastic mapping (for mobile robot and AUV navigation), IEEE Journal of Oceanic Engineering, 26, 4, 561-571.
  • 8. Moreno L., Garrido S., Blanco D., Muñoz M.L., 2009, Differential evolution solution to the SLAM problem, Robotics and Autonomous Systems, 57, 4, 441-450.
  • 9. Siemiątkowska B., Szklarski J., Gnatowski M., 2011, Mobile robot navigation with the use of semantic map constructed from 3D laser range scans, Control and Cybernetics, 40, 1.
  • 10. Sola J., 2013, Simulataneous localization and mapping with the extended Kalman filter, unpublished, Available: http://www.joansola.eu/JoanSol....
  • 11. Tardós J.D., Neira J., Newman P.M., Leonard J.J., 2002, Robust mapping and localization in indoor environments using sonar data, International Journal of Robotics Research, 21, 4, 311-330.
  • 12. Thrun S., Koller D., Ghahramani Z., Durrant-Whyte H., Ng A.Y., 2004, Simultaneous mapping and localization with sparse extended information filters: Theory and initial results, [In:] Algorithmic Foundations of Robotics V. Springer Tracts in Advanced Robotics, J.D. Boissonnat, J. Burdick, K. Goldberg, S. Hutchinson (Edit.), 7, 363-380.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-5c0f771e-a410-49f4-8610-a0944c0391d8
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