Skip to main content
SpringerLink
Log in

Estimating Scene Complexity by One and Two Local Observations

  • Intellectual Control Systems, Data Analysis
  • Published:
Automation and Remote Control Aims and scope Submit manuscript

Abstract

The formal problem to estimate the complexity of a scene with numerous obstacles and mobile objects is considered. By assumption there is only limited information on the location of obstacles in a small part of the scene, which is obtained by the sensor systems of one or more objects. Upper and lower bounds for the complexity of the scene are derived for one and two observations of the local domains.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Intellektual’noe planirovanie traektorii podvizhnykh ob”ektov v sredakh s prepyatstviyami (Intelligent Path Planning for Mobile Objects in Environments with Obstacles), Pshikhopov, V.Kh., Ed., Moscow: Fizmatlit, 2014.

    Google Scholar 

  2. Path Planning for Vehicles Operating in Uncertain 2D Environments, Pshikhopov, V.Kh., Ed., Oxford: Elsevier, Butterworth-Heinemann, 2017.

    Google Scholar 

  3. Intellektual’nye tekhnologii planirovaniya peremeshchenii podvizhnykh ob”ektov v trekhmernykh nedeterminirovannykh sredakh (Intelligent Planning Technologies for the Movements of Mobile Objects in Nondeterministic 3D Environments), Pshikhopov, V.Kh., Ed., Moscow: Nauka, 2017.

    Google Scholar 

  4. Pshikhopov, V.Kh. and Medvedev, M.Yu., Upravlenie podvizhnymi ob”ektami v opredelennykh i neopredelennykh sredakh (Control of Mobile Objects in Deterministic and Uncertain Environments), Moscow: Nauka, 2011.

    Google Scholar 

  5. Feixas, M., del Acebo, E., Bekaert, Ph., and Sbert, M., An Information Theory Framework for the Analysis of Scene Complexity, EUROGRAPHICS’ 99, 1999, vol. 18, no. 3.

    Google Scholar 

  6. Niepel, L., Martinka, J., Ferko, A., and Elias, P., On Scene Complexity Definition for Rendering, WSCG’95, Plzen, 1995, pp. 209–217.

    Google Scholar 

  7. Plemenos, D., Sbert, M., and Feixas, M., On Viewpoint Complexity of 3D Scenes, Int. Conf. Graphicon, 2004, Moscow, Russia. http://www.graphicon.ru/

    Google Scholar 

  8. Rigau, J., Feixas, M., and Sbert, M., Visibility Complexity of a Region in Flatland, EUROGRAPHICS, 2000.

    Google Scholar 

  9. Karkishchenko, A.N. and Pshikhopov, V.Kh., On Finding the Complexity of an Environment for the Operation of a Mobile Object on a Plane, Autom. Remote Control, 2019, vol. 80, no. 5, pp. 897–912.

    Article  Google Scholar 

  10. Skvortsov, A.V., Triangulyatsiya Delone i ee primenenie (Delaunay Triangulation and Its Applications), Tomsk: Tomsk. Gos. Univ., 2002.

    Google Scholar 

  11. Qu, Y., Zhang, Yi., and Zhang, Yo., A Global Path Planning Algorithm for Fixed-wing UAVs, J. Intell. Robot Syst., 2018, vol. 91, pp. 691–707.

    Article  Google Scholar 

  12. Kim, D. and Sugihara, K., Voronoi Diagram of a Circle Set from Voronoi Diagram of a Point Set: I. Topology, Comput. Aided Geom. Des., 2001, vol. 18, no. 6, pp. 541–562.

    Article  MathSciNet  MATH  Google Scholar 

  13. Choset, H. and Burdick, J., Sensor-based Exploration: The Hierarchical Generalized Voronoi Graph, Int. J. Robot. Res., 2000, vol. 19, no. 2, pp. 96–125.

    Article  Google Scholar 

  14. Merino, L., Wiklund, J., and Caballero, F., Vision-based Multi-UAV Position Estimation, IEEE Robot. Autom. Mag., 2006, vol. 13, no. 3, pp. 53–62.

    Article  Google Scholar 

  15. Yu, X. and Zhang, Y.M., Sense and Avoid Technologies with Application to Unmanned Aircraft Systems: Review and Prospects, Progress Aeros. Sci., 2015, vol. 74, pp. 152–166.

    Article  Google Scholar 

  16. Borouchaki, H. and Lo, S., Fast Delaunay Triangulation in Three Dimensions, Comput. Methods Appl. Mech. Eng., 1995, vol. 128, pp. 153–167.

    Article  MathSciNet  MATH  Google Scholar 

  17. Nechetkie mnozhestva v modelyakh upravleniya i iskusstvennogo intellekta (Fuzzy Sets in Models of Control and Artificial Intelligence), Pospelov, D.A., Ed., Moscow: Nauka, 1986.

    Google Scholar 

  18. Harary, F., Graph Theory, Boston: Addison-Wesley, 1969. Translated under the title Teoriya grafov, Moscow: Mir, 1973.

    Book  MATH  Google Scholar 

Download references

Acknowledgments

This work was supported by the Russian Science Foundation, project no. 18-19-00621.

Author information

Authors and Affiliations

  1. Research and Design Bureau for Robotics and Control Systems, Taganrog, Russia

    A. N. Karkishchenko

Authors
  1. A. N. Karkishchenko
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to A. N. Karkishchenko.

Additional information

Russian Text © The Author(s), 2019, published in Avtomatika i Telemekhanika, 2019, No. 8, pp. 129–148.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Karkishchenko, A.N. Estimating Scene Complexity by One and Two Local Observations. Autom Remote Control 80, 1471–1486 (2019). https://doi.org/10.1134/S0005117919080083

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0005117919080083

Keywords

Search

Navigation