RESULTS OF TESTING THE POSITIONING ALGORITHM AND DETERMINING THE ORIENTATION OF THE UNDERWATER VEHICLE BASED ON DATA FROM HYDRO-ACOUSTIC BEACONS
Abstract
The article deals with the determination of coordinates and orientation angles of the autonomous underwater vehicle (AUV) relative to the stationary landing platform using high-frequency near-range hydroacoustic system. The navigation task implies maneuvering the vehicle and approaching the underwater station, which is associated with the formation of zones with different acoustic visibility of the station's emitters by the receiving elements of the vehicle. Three zones of acoustic visibility can be distinguished. The first zone is characterized by observation of signals of all beacons of the underwater station. As a consequence, this zone is the most informative for solving the problem of positioning and orientation determination of the AUV. The second zone corresponds to partial reduction of the number of observed beacons, which does not critically influence the possibility of problem solving. The third zone (landing) is defined by essential reduction of a number of observed beacons, that, as consequence, considerably complicates the solution of the positioning problem, taking into account the increased requirements on accuracy at the moment of landing of the device caused by provision of safety. To maintain positioning accuracy and determine the underwater vehicle orientation in the landing zone, it is proposed to use the results obtained in the early stages of approach of the vehicle to the underwater station (the first and second zones). A mathematical statement of the problem is given in the work, and the algorithm of its solution is described. When finding the AUV in the first and second zones, the solution algorithm consists of two subtasks. The first subtask is a rough estimation of location vicinity and angles of vehicle orientation using K-nearest neighbors method; the second subtask is specification of estimations using pseudo-dimensional method by solving system of algebraic equations with Levenberg-Marquardt algorithm. In addition, estimation of beacon emission time is carried out. At finding ANPA in the third zone the algorithm is reduced to solution of system of algebraic equations with use of forecast of time of signal emission by a beacon, received at finding of the device in zones one and two. The results of simulation modeling and results of algorithm approbation obtained using a mockup of the vehicle and a mockup of the underwater station in the test pool are presented.
References
podvodnogo apparata dlya nauchnykh issledovaniy v Arktike [Application of an autonomous
uninhabited underwater vechicle for scientific research int the Arctic], Podvodnye
issledovaniya i robototekhnika [Underwater research and robotics], 2007, No. 2, pp. 5-14.
2. Liguo Tan, Shenmin Song, Xiaoyan Yang and Jianwen Song. An overview of marine recovery
methods of UAV for small ships, Journal of Harbin institute of technology, 2019, 10 (51), pp. 1-10.
3. Kebkal K.G., Mashoshin A.I. Gidroakusticheskie metody pozitsionirovaniya avtonomnykh
neobitaemykh podvodnykh apparatov [Hydroacoustic methods of positioning autonomous uninhabited
underwater vechicles], Giroskopiya i navigatsiya [Gyroscopy and navigation], 2016,
No. 3, pp. 115-130.
4. Matvienko Yu.V. Gidroakusticheskiy kompleks navigatsii podvodnogo robota: dis. … kand.
tekh. nauk [Hydroacoustic navigation complex of an underwater robot: cand. of eng. sc. diss.]:
01.04.06. Vladivostok, 2004, 271 p.
5. Wang J., Xu T. and Wang Z. Adaptive robust unscented Kalman filter for AUV acoustic navigation,
Sensors, 2020, Vol. 20: 60.
6. Popescu Dan & Ichim Loretta. Image Recognition in UAV Application Based on Texture Analysis
// International Conference on Advanced Concepts for Intelligent Vision Systems. – 2015.
– P. 693-704.
7. Pinheiro P.M., Neto A.A., Grando R.B. et al. Trajectory Planning for Hybrid Unmanned Aerial
Underwater Vehicles with Smooth Media Transition // Journal of Intelligent & Robotic Systems.
– 2022. – 104, 46. – https://doi.org/10.1007/s10846-021-01567-z.
8. Vallicrosa G., Bosch J., Palomeras N., Ridao P., Carreras M., Gracias N. Autonomous homing and
docking for AUVs using Range-Only Localization and Light Beacons // IFAC-PapersOnLine.
– 2016. – Vol. 49. – Issue 23. – P. 54-60. https://doi.org/10.1016/j.ifacol.2016.10.321.
9. Fan S., Liu C., Li B., et al. AUV docking based on USBL navigation and vision guidance,
Journal of Marine Science and Technology, 2019, 24, pp. 673-685.
10. Zhong l., Li D, Lin M., Lin R., Yang C. A Fast Binocular Localization Method for AUV Docking,
Sensors (Basel), Apr. 2019, 19 (7), 1735.
11. Lin R., Zhang, F., Li, D., Lin, M., Zhou, G., Yang, C. An Improved Localization Method for
the Transition between Autonomous Underwater Vehicle Homing and Docking, Sensors,
2021, 21, 2468. Available at: https://doi.org/10.3390/s21072468.
12. Li Y., Jiang Y., Cao J., Wang B., and Li Y. AUV docking experiments based on vision positioning
using two cameras, Ocean Engineering, Dec. 2015, Vol. 110, pp. 163-173.
13. Liu S., Ozay M., Okatani T. Detection and Pose Estimation for Short-Range Vision-Based
Underwater Docking, IEEE Access, 2019, Vol. 7, pp. 2720-2749.
14. Fujiyoshi Hironobu, Hirakawa Tsubasa, Yamashita Takayoshi. Deep learning-based image
recognition for autonomous driving, IATSS Research, 2019, 43.
15. Stepanov D.N. Metody i algoritmy opredeleniya polozheniya i orientatsii bespilotnogo
letatel'nogo apparata s primeneniem bortovykh videokamer [Methods and algorithms for determining
the position and orientation of an unmanned aerial vehicle using onboard video cameras],
Programmnye produkty i sistemy [Software products and systems], 2014, No. 1 (105).
16. Gruzlikov A.M. Navigatsiya ANPA v blizhnem pole v interesakh resheniya zadachi
privedeniya k prichal'nomu ustroystvu [Navigation of the AUV in the near field in the interests
of solving the ghost problem to the mooring device], Sb. materialov XXIX SanktPeterburgskoy mezhdunarodnoy konferentsii po integrirovannym navigatsionnym sistemam
[Collection of materials XXIX St. Petersburg International Conference on Integrated Navigation
Systems]. Saint Petersburg, 2022, pp. 138-140.
17. Karaulov V.G., Gruzlikov A.M. Opredelenie marshruta i skorosti dvizheniya ANPA v zadache
privedeniya k bazovoy stantsii [Determining the route and speed of AUV movement in the
problem of driving to the base station], Mater. XXIV KMU. «Navigatsiya i upravlenie
dvizheniem» [Collection XXIV KMU Navigation and motion control»], 2022, pp. 26-29.
18. Koshaev D.A. Otnositel'noe pozitsionirovanie i opredelenie orientatsii avtonomnogo
neobitaemogo podvodnogo apparata po dannym ot gidroakusticheskikh mayakov [AUV relative
position and attitude determination using acoustic beacons], Mater. XXXIII konferentsii
pamyati vydayushchegosya konstruktora giroskopicheskikh priborov N.N. Ostryakova [Collection
XXXIII conference in memory of the outstanding designer of gyroscopic devices
N.N. Ostryakov]. Saint Petersburg, 2022, pp. 70-77.
19. Koshaev D.A. Otnositel'noe pozitsionirovanie i opredelenie orientatsii avtonomnogo
neobitaemogo podvodnogo apparata po dannym ot gidroakusticheskikh mayakov [AUV relative
position and attitude determination using acoustic beacons], Giroskopiya i navigatsiya
[Gyroscopy and navigation], 2022, Vol. 30, No. 4 (119), pp. 122-141.
20. V'yugin V.V. Matematicheskie osnovy teorii mashinnogo obucheniya i prognozirovaniya [Mathematical
foundations of the theory of machine learning and forecasting]. Moscow, 2013, 387 p.
21. Izmailov A.F., Kurennoy A.S., Stetsyuk P.I. Metod Levenberga-Markvardta dlya zadachi
bezuslovnoy optimizatsii [Levenberg-Marquardt method for the problem of unconditional optimization],
Vestnik Tambovskogo universiteta. Seriya: estestvennye i tekhnicheskie nauki
[Vestnik of Tambov University. Series: Natural and Technical sciences], 2019, Vol. 24.
No. 125, pp. 60-74.
22. Prokhortsov A.V., Minina O.V. Analiticheskoe reshenie navigatsionnoy zadachi na osnove
psevdodal'nomernogo metoda [Analitical solution of the navigation problem based on the
pseudo-dimensional method], Izvestiya TulGU. Tekhnicheskie nauki [News of TulSU. Technical
sciences], 2020, Issue 11, pp. 395-398.
23. Barabanov O. O., Barabanova L. P. Matematicheskie zadachi dal'nomernoy navigatsii [Mathematical
problems of rangefinder navigation]. Moscow: Fizmatlit, 2007.
24. Derevyankin A.V., Matasov A.I. O konechnom algoritme opredeleniya mestopolozheniya
ob"ekta po raznostyam izmereniy psevdodal'nostey [On a finite algorithm for determining the
location of an object based on the measurement differences of pseudo-distances], Giroskopiya
i navigatsiya [Gyroscopy and navigation], 2015, No. 2, pp. 106-117.
