Mathematical and Algorithmic Model for Local Navigation of Mobile Platform and UAV Using Radio Beacons

  • Alexander DenisovEmail author
  • Roman Iakovlev
  • Igor Lebedev
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11659)


Robots are used to solve routine, monotonous, difficult and dangerous tasks; therefore, agriculture is one of the largest spheres for using robotic systems. One of the main problems faced by developers of autonomous robotic systems is the navigation of the robot in space. This paper presents a solution to the problem of navigation, based on the maintenance of a constant radio signal between the UAV or mobile platform and control system. Radio communication is maintained by building a mesh network based on LoRa data transmission technology modules throughout the entire path of the robot. Navigation system is a mesh network based on the radio beacon. Three methods for determining the coordinates of additional module location were considered. These methods are intended for organizing mush network from modules that are not connected to each other. Analysis of considered methods was presented. Methods are not designed for arbitrary movement of robotic systems. Each of the presented methods has its advantages and disadvantages, the first two methods have the main advantage being the smallest number of modules used to connect all radio modules to the network, but with a decrease in the number of modules there is a problem of reducing system reliability. The third method solves this problem by clustering and can withstand the failure of a large number of additional modules, and the system itself becomes more like a mesh network.


Robot navigation LoRa Radio communication Mesh network 



The present research was partially supported by project No. RFBR 18-58-76001 ERA_a.


  1. 1.
    Negrete, M., Savage, J., Contreras-Toledo, L.A.: A motion-planning system for a domestic service robot. SPIIRAS Proc. 5, 5–38 (2018)CrossRefGoogle Scholar
  2. 2.
    Popov, S.G., Zaborovsky, V.S., Kurochkin, L.M., Sharagin, M.P., Zhang, L.: Method of dynamic selection of satellite navigation system in the autonomous mode of positioning. SPIIRAS Proc. 18(2), 302–325 (2019)CrossRefGoogle Scholar
  3. 3.
    Merkulov, V.I., Sadovskiy, P.A.: Estimation of distance and its derivatives in the bistatic passive radar location system. SPIIRAS Proc. 1, 122–143 (2018)CrossRefGoogle Scholar
  4. 4.
    Magno, M., Rickli, S., Quack, J., Brunecker, O., Benini, L.: Combining LoRa and RTK to achieve a high precision self-sustaining geo-localization system. In: Proceedings of the 17th ACM/IEEE International Conference on Information Processing in Sensor Networks, pp. 160–161. IEEE Press (2018)Google Scholar
  5. 5.
    Pütz, S., Wiemann, T., Sprickerhof, J., Hertzberg, J.: 3d navigation mesh generation for path planning in uneven terrain. IFAC-PapersOnLine 49(15), 212–217 (2016)CrossRefGoogle Scholar
  6. 6.
    Rabie, T., Suleiman, S.: A novel wireless mesh network for indoor robotic navigation. In: 2016 5th International Conference on Electronic Devices, Systems and Applications (ICEDSA), pp. 1–4. IEEE (2016)Google Scholar
  7. 7.
    Nykorak, A., Hiromoto, R.E., Sachenko, A., Koval, V.: A wireless navigation system with no external positions. In: 2015 IEEE 8th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), vol. 2, pp. 898–901. IEEE (2015)Google Scholar
  8. 8.
    Konieczny, M., Pawłowicz, B., Potencki, J., Skoczylas, M.: Application of RFID technology in navigation of mobile robot. In: 2017 21st European Microelectronics and Packaging Conference (EMPC) & Exhibition, pp. 1–4. IEEE (2017)Google Scholar
  9. 9.
    Malandra, F., Sansò, B.: A Markov-modulated end-to-end delay analysis of large-scale RF-mesh networks with time-slotted ALOHA and FHSS for smart grid applications. IEEE Trans. Wirel. Commun. 17(11), 7116–7127 (2018)CrossRefGoogle Scholar
  10. 10.
    Lavric, A., Popa, V.: Internet of things and LoRa™ low-power wide-area networks: a survey. In: 2017 International Symposium on Signals, Circuits and Systems (ISSCS), pp. 1–5. IEEE (2017)Google Scholar
  11. 11.
    Garrido-Hidalgo, C.: IoT heterogeneous mesh network deployment for human-in-the-loop challenges towards a social and sustainable Industry 4.0. IEEE Access 6, 28417–28437 (2018)CrossRefGoogle Scholar
  12. 12.
    Leon, E., Alberoni, C., Wister, M., Hernández-Nolasco, J.: Flood early warning system by Twitter using LoRa. In: Multidisciplinary Digital Publishing Institute Proceedings, vol. 2, no. 19, p. 1213 (2018)CrossRefGoogle Scholar
  13. 13.
    Cagatan, G.K.B., Magsumbol, J.A.V., Baldovino, R., Sybingco, E., Dadios, E.P.: Connectivity analysis of wireless sensor network in two-dimensional plane using Castalia simulator. In: 2017 IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM), pp. 1–8. IEEE (2017)Google Scholar
  14. 14.
    Lavric, A., Popa, V.: A LoRaWAN: long range wide area networks study. In: 2017 International Conference on Electromechanical and Power Systems (SIELMEN), pp. 417–420. IEEE (2017)Google Scholar
  15. 15.
    Barriquello, C.H., et al.: Performance assessment of a low power wide area network in rural smart grids. In: 2017 52nd International Universities Power Engineering Conference (UPEC), pp. 1–4 (2017)Google Scholar
  16. 16.
    SHakhnovich, I.: Mif o zatukhanii svobodnogo prostranstva: chego ne pisal GT Friis [The Myth about Free Space Damping: What didn’t GT write Friis]. Pervaya milya [First Mile] 2, 40–45 (2014). (in Russian)Google Scholar
  17. 17.
    Kalinin, A.I., CHerenkova, E.L.: Rasprostranenie radiovoln i rabota radiolinij [The propagation of radio waves and the work of radio lines]. Svyaz’. Moskva [Connection Moscow] (1971). (in Russian)Google Scholar
  18. 18.
    Heltec Automation: WiFi LoRa 32. Accessed 01 Apr 2019

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences (SPIIRAS)St. PetersburgRussia

Personalised recommendations