Logo PTI
Polish Information Processing Society
Logo FedCSIS

Annals of Computer Science and Information Systems, Volume 11

Proceedings of the 2017 Federated Conference on Computer Science and Information Systems

Visual simulator for MavLink-protocol-based UAV, applied for search and analyze task

, ,

DOI: http://dx.doi.org/10.15439/2017F184

Citation: Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 11, pages 11771185 ()

Full text

Abstract. In this paper the authors present the results of research to develop the visual system for autonomous flying agent. The core elements of the vision system which were designed and implemented in the earlier stage of the project are brought together. The second aim is to show capabilities of a simulation environment designed and developed by the authors in order to enable testing of the vision systems (dedicated for Unmanned Aerial Vehicles) in the artificial environment. The first section of the paper introduces the testing (simulation) environment for MavLink-protocol-based autonomous flying robots. Next, the core elements of a vision system, designed for Unmanned Aerial Vehicle (UAV), are discussed. This includes pre-processing and vectorization algorithms, object recognition methods and fast three-dimensional model construction. The third part introduces a set of algorithms for robot navigation, solely based on vision and altitude sensor and compass. The paper concludes with the description of the tests and presentation of results where designed simulator was applied to show mentioned vision system elements operating together to execute complex task.

References

  1. D. Cook, A. Vardy, and R. Lewis, “A survey of auv and robot simulators for multi-vehicle operations.” in Proceedings of 2014 IEEE/OES Autonomous Underwater Vehicles (AUV), vol. 2014, pp. 1-8, 2014.
  2. K. Takaya, T. Asai, V. Kroumov, and F. Smarandache, “Simulation environment for mobile robots testing using ros and gazebo.” in Proceedings of 2016 20th International Conference on System Theory, Control and Computing (ICSTCC), vol. 2016, pp. 96-101, 2016.
  3. B. Fuller, J. Kok, N. Kelson, and F. Gonzalez, “Hardware design and implementation of a mavlink interface for an fpga-based autonomous uav flight control system.” in Proceedings of Australasian Conference on Robotics and Automation, vol. 2014, pp. 62-67, 2014.
  4. T. Dietrich, O. Andryeyev, A. Zimmermann, and A. Mitschele-Thiel, “Towards a unified decentralized swarm management and maintenance coordination based on mavlink.” in Proceedings of International Conference on Autonomous Robot Systems and Competitions (ICARSC), vol. 2016, pp. 124-12, 2016.
  5. M. Flasiński, “On the parsing of deterministic graph languages for syntactic pattern recognition.” Pattern Recognition, vol. 26, pp. 1–16, 1993.
  6. R. Tadeusiewicz and M. Flasiński, Pattern Recognition. Warsaw: Polish Scientific Publishers, PWN [in Polish], 1991.
  7. M. Bielecka, M. Skomorowski, and A. Bielecki, “Fuzzy syntactic approach to pattern recognition and scene analysis.” in Proceedings of the 4th International Conference on Informatics in Control, Automatics and Robotics ICINCO07, ICSO Intelligent Control Systems and Optimization, Robotics and Automation, vol. 1, pp. 29-35, 2007.
  8. M. Flasiński, “Parsing of ednlc-graph grammars for scene analysis.” Pattern Recognition, vol. 21, pp. 623–629, 1998.
  9. D. Filliat and J. Mayer, “Map-based navigation in mobile robots. a review of localization strategies.” Journal of Cognitive Systems Research, vol. 4, pp. 243–283, 2003.
  10. L. Muratet, S. Doncieux, Y. Briere, and J. Meyer, “A contribution to vision-based autonomous helicopter flight in urban environments.” Robotics and Autonomous Systems, vol. 50, pp. 195–229, 2005.
  11. A. Bielecki, T. Buratowski, and P. Śmigielski, “Syntactic algorithm for two-dimensional scene analysis for unmanned flying vehicles.” Lecture Notes in Computer Science, vol. 7594, pp. 304–312, 2012.
  12. A. Bielecki, T. Buratowski, and P. Śmigielski, “Recognition of two-dimensional representation of urban environment for autonomous flying agents.” Expert Systems with Applications, vol. 40, pp. 3623–3633, 2013.
  13. A. Bielecki, T. Buratowski, and P. Śmigielski, “Three-dimensional urban-type scene representation in vision system of unmanned flying vehicles.” Lecture Notes in Computer Science, vol. 8467, pp. 662–671, 2014.
  14. A. Bielecki and P. Śmigielski, “Graph representation for two-dimensional scene understanding by the cognitive vision module.” International Journal of Advanced Robotic Systems, vol. 14, pp. 1–14, 2017.
  15. J. Canny, “Finding edges and lines in images.” M.I.T. Artificial Intelligence Lab., Cambridge, MA, Tech. Rep., 1983.
  16. U. Ramer, “An iterative procedure for the polygonal approximation of plane curves.” Computer Graphics and Image Processing, vol. 1, no. 3, pp. 244–256, 1972.
  17. D. Douglas and T. Peucker, “Algorithms for the reduction of the number of points required to represent a digitized line or its caricature.” The Canadian Cartographer, vol. 10, no. 2, pp. 112–122, 1973.
  18. A. Bielecki, T. Buratowski, M. Ciszewski, and P. Śmigielski, “Vision based techniques of 3d obstacle reconfiguration for the outdoor drilling mobile robot.” Lecture Notes in Computer Science, vol. 9693, pp. 602–612, 2016.
  19. F. Bonin-Font, A. Ortiz, and G. Oliver, “Visual navigation for mobile robots: a survey.” Journal of Intelligent and Robotic Systems, vol. 53, pp. 263–296, 2008.
  20. B. Sinopoli, M. Micheli, G. Donato, and T. Koo, “Vision based navigation for an unmanned aerial vehicle.” in Proceedings of the International Conference on Robotics and Automation ICRA, vol. 2, pp. 1757-1764, 2001.