Scientific and Technical Journal


ISSN Print 2221-3937
ISSN Online 2221-3805

In this paper the task of creating the effective navigation subsystem of autonomous mobile robot is regarded. The highs and lows of existing schemes, based on local and global navigation methods are noted.  Combined system of navigation of autonomous mobile robot is offered, which is based on global approaches with compensating of part of its lows with the help of functionality of local approaches. The advantage of method by its resourse consumption comparing with both local and global methods, especially in condition of dynamic world with low change frequency, is shown.

  1. Zashchelkin K., Kalinichenko V.V. and Ulchenko N.O. Realization of Combined Means of Navigation of the Autionomous Mobile Robot [Realizatsiya kombinirovannogo sposoba navigatsii avtonomnogo mobil'nogo robota]. Elektrotehnicheskie i Kompjuternie sistemy, Tekhnika Kyiv, Ukraine, 2013, No 09 (85), pp. 102-109 (In Russian).

  2. Russel S. Artificial Intelligence: A Modern Approach. Prentice Hall, New Jersey, 2006, 1407 p. (In English).

  3. Devyatkov V. Systems of Artificial Intelligence [Sistemy iskusstvennogo intellekta] Izdatel'stvo MGTU im. N.E. Baumana, Moscow, Russian Federation, 2001, 352 р. (In Russian)

  4. Kasabov N. Introduction: Hybrid Intelligent Adaptive Systems. International Journal of Intelligent Systems, 1998, Vol. 6, pp. 453-454 (In English).

  5. Fahimi F. Autonomous Robots. Modeling, Path Planning and Control. Springer, New York, 2009, 348 p. (In English).

  6. Hachour O. Path Planning of Autonomous Mobile Robot. International Journal of Systems Applications, Engineering and Development, 2009, Iss. 4, Vol. 2 (In English).

  7. Lumelsky V. Sensing, Intelligence Motion. Wiley-Interscience, New Jersey, 2006, 456 p. (In English).

  8. Siegwart R. and Nourbakhsh I. Introduction to Autonomous Mobile Robots. MIT Press, Boston, 2004, 336 p. (In English).

  9. Juliá, M., Gil A. and Reinoso O.A Comparison of Path Planning Strategies for Autonomous Exploration and Mapping of Unknown Environments. Autonomous Robots, 33 (4), 2012, pp. 427-444 (In English), doi: 10.1007/s10514-012-9298-8.

  10. Lor'er Zh.-Lyu. Systems of Artificial Intelligence [Sistemy iskusstven-nogo intellekta. Perevod s frantsuzskogo i red. V. L. Stefanyuka, Mir, Moscow, Russian Federation, 1991, pp. 238-244 (In Russian).

  11. Nil'son N. Problem-solving Methods in Artificial Intelligence [Problem-solving Methods in Artificial Intelligence], perevod s angl. V. L. Stefanyuka; pod red. S. V. Fomina, Mir, Moscow, Russian Federation, 1973, pp. 70-80 (In Russian).

  12. Pearl J. Heuristics: Intelligent Search Strategies for Computer Problem Solving.Addison-Wesley, 1984 (In English).

  13. Da Costa A.L., Ceonceicao A.G.S, Cerqueira R.G. and others. Omnidirectional Mobile Robots Navigation: A Joint Approach Combining Reinforcement learning and Knowledge-based Systems. ISSNIP Biosignals and Biorobotics Conference, BRC, art. no.6487531, 2013 (In English), doi: 10.1109/BRC.2013.6487531.

  14. Yaonan W., Yimin Y., Xiaofang Y and others. Autonomous Mobile Robot Navigation System Designed in Dynamic Environment Based on Transferable Belief Model. Measurement : Journal of the International Measurement Confederation, 44 (8), 2011, pp. 1389-1405 (In English), doi: 1016/j.measurement.2011.05.010.

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