Аннотация. 

Разрабатываемый SLAM-метод навигации внутри помещений на основе определения местоположения маяков Bluetooth обеспечивает навигацию пользователя внутри помещения и одновременно с этим позволяет строить карты радиосигналов и наносить на карту помещения маяки Bluetooth. Навигация пользователя внутри помещения обеспечивается с помощью комбинации методов мультилатерации, радиоотпечатков и метода счисления координат на основе встроенных датчиков смартфона. Для решения задачи определения местоположения маяка Bluetooth используется алгоритм Random forest, использующий в качестве обучающей выборки уровни сигналов, углы поворота пользователя и расстояние до маяка Bluetooth. На основе полученных карт радиосигналов и местоположений маяков Bluetooth происходит оценка геометрических параметров помещения. Данный метод позволяет обойтись без трудоёмкой процедуры предварительной настройки оборудования для навигации внутри помещений.

Ключевые слова: 

определение местоположения внутри помещений, машинное обучение, SLAM-метод, краудсорсинг.

Стр. 70-81.

DOI 10.14357/20718632210307

 

 

Литература

1. Shen J., Huang B., Kang X., Jia B. and Li W. Localization of access points based on the Rayleigh lognormal model // 2018 IEEE Wireless Communications and Networking Conference (WCNC). 2018. pp. 1-6.

2. Guangbing Z., Jing L., Shugong X., Shunqing Z., Shige M., Kui X. An EKF-based multiple data fusion for mobile robot indoor localization // Assembly Automation. 2021.

3. Yucel, H., Elibol, G., Yayan U. Wi-Fi Based Indoor Positioning System For Mobile Robots By Using Particle Filter // ArXiv. 2020.

4. Surmann H., Nüchter A., Hertzberg J. An autonomous mobile robot with a 3D laser range finder for 3D exploration and digitalization of indoor environments // Robotics and Autonomous Systems. 2003. № 45(3-4), pp. 181–198.

5. Yunlei Z., Gong X., Liu K., Shuai Zhang S. Localization and Tracking of an Indoor Autonomous Vehicle Based on the Phase Difference of Passive UHF RFID Signals // Sensors. 2021. № 9.

6. Kuusik A., Roche S., Weis F. SMARTMUSEUM: cultural content recommendation system for mobile users // Proceedings of Fourth International Conference on Computer Sciences and Convergence Information Technology. 2009. pp. 477-482.

7. Indoo.rs official website, Available at: http://indoo.rs/indoorpositioning-

shopping-malls/ (accessed July, 2021).

8. Bluepath official website, Available at:

http://www.bluepath.me/use-cases-indoornavigation/

retail.php (accessed July, 2021)

9. Веб-сайт Navigine, Available at: https://nvgn.ru/ (accessed July, 2021)

10. Meena B.S., Laskar R.U., Hemachandran K. Indoor Localization-Based Office Automation System Using IOT Devices // Intelligent Computing in Engineering. Advances in

Intelligent Systems and Computing. 2020. № 1125.

11. Interact official website, Available at: https://www.interactlighting.

com/global/what-is-possible/interact-office/indoornavigation (accessed July, 2021).

12. Insoft official website, Available at:

https://www.infsoft.com/industries/offices-smart-buildings (accessed July, 2021)

13. Hesslein N., Wesselhöft M., Hinckeldeyn J., Kreutzfeldt J. Industrial Indoor Localization: Improvement of Logistics Processes Using Location Based Services // Advances in Automotive Production Technology – Theory and Application. 2021.

14. Niu, Q., Yang, X., & Yin, Y. IPL: Image-Assisted Person Localization for Underground Coal Mines // Sensors. 2018. № 18(11).

15. Jinyue Z., Jianing G., Haiming X., Xiangchi L., Daxin Z. A Framework for an Intelligent and Personalized Fire Evacuation Management System // Sensors. 2019. № 19.

16. Tang Z., Zhao Y., Yang L., Qi S., Fang D., Chen X., Gong X., Wang Z. Exploiting wireless received signal strength indicators to detect evil-twin attacks in smart homes // Mobile Information Systems. 2017. № 4, pp. 1–14.

17. Cisco official website, Available at:

https://www.cisco.com/c/en/us/solutions/enterprisenetworks/

hyperlocation-solution/index.html (accessed July, 2021).

18. Cisco official website, Available at:

https://www.cisco.com/c/en/us/products/collateral/wireless

/mobility-services-engine/eos-eol-notice-c51-740795.html (accessed July, 2021).

19. Heidari M., Alsindi N. A., Pahlavan K. UDP identification and error mitigation in ToA-Based indoor localization systems using neural network architecture // IEEE Ttranslations on Wireless Communications. 2009. № 7, pp. 3597–3607.

20. Kabir Md. H., Kohno R. A hybrid TOA-fingerprinting based localization of mobile nodes using UWB signaling for non line-of-sight conditions // Sensors. 2012. №12(8), pp. 11187-11204.

21. Liu D., Wang Y., He P., Zhai Y., Wang H. TOA localization for multipath and NLOS environment with virtual station // EURASIP Journal on Wireless Communications and Networking. 2017. pp. 104.

22. Xinrong L., Pahlavan K., Latva-aho M., Ylianttila M. Comparison of indoor geolocation methods in DSSS and OFDM wireless LAN systems sign in or purchase // Vehicular Technology Conference. 2000.

23. Sun Z., Farley R., Kaleas T., Ellis J., Chikkappa K. Cortina: collaborative context-aware indoor positioning employing RSS and RToF techniques // Proceedings IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops). 2011. pp. 340–343.

24. Sivers M., Fokin G., Dmitriev P., Kireev A., Volgushev D., Ali A. A. H. Indoor positioning in WiFi and NanoLOC networks // Proceedings of International Conference on Next Generation Wired/Wireless Networking Conference on Internet of Things and Smart Spaces. 2016.

25. Hanssens B., Plets D., Tanghe E., Oestges C., Gaillot D.P., Liénard M., Martens L., Joseph W. An indoor localization technique based on ultra-wideband AoD/AoA/ToA estimation // Proceedings of IEEE International Symposium on Antennas and Propagation (APSURSI). 2016. pp. 1445–1446.

26. Yang S.-H., Kim H.-S., Son Y.-H., Han S.-K. Threedimensional visible light indoor localization using AOA and RSS with multiple optical receivers // Journal of Lightwave Technology. 2014. №. 32 (14), pp. 2480–2485.

27. Deliang L., Kaihua L., Yongtao M., Jiexiao Y. Joint TOA and DOA localization in indoor environment using virtual stations // IEEE Communications Letters. 2014. № 18(8), pp. 1423–1426.

28. Zhao X., Xiao Z., Markham A., Trigoni N., Ren Y. Does BTLE measure up against WiFi? A Comparison of indoor location performance // Proceedings of the European Wireless 2014: 20th European Wireless Conference. 2014. pp. 1–6.

29. Röbesaat J., Zhang P., Abdelaal M., Theel O. An improved BLE indoor localization with Kalman-based fusion: an experimental study // Sensors. 2017. № 17(5). doi:10.3390/s17050951.30. Alsehly F., Mohd Sabri R., Sevak Z., Arslan T. Improving indoor positioning accuracy through a Wi-Fi handover algorithm // Proceedings of International Technical Meeting of the Institute of Navigation. 2010. pp. 822–829.

31. Wen L., Fu X., Zhongliang D. Coordinate-Based Clustering Method for Indoor Fingerprinting Localization in Dense Cluttered Environments // Sensors. 2016. №16. 10.3390/s16122055.

32. Ferris, B., Fox D., D. Lawrence N. WiFi-SLAM using Gaussian process latent variable models // Proceedings of IJCAI. 2007. №7. pp. 2480-2485.

33. Mirowski P., Tin H., Saehoon Y., William M. SignalSLAM: Simultaneous localization and mapping with mixed WiFi, Bluetooth, LTE and magnetic signals // 2013 International Conference on Indoor Positioning and Indoor Navigation. 2013. pp. 1-10. 10.1109/IPIN.2013.6817853.

34. Luo C., Hong H., Chan M. C., PiLoc: a Self-Calibrating Participatory Indoor Localization System // Proceedings of 13th International Symposium on Information Processing in Sensor Networks. 2014. pp.143-153. doi: 10.1109/IPSN.2014.6846748.

35. Luo C., Hong H., Chan M. C., Li J. Zhang X., Ming Z. MPiLoc: Self-Calibrating Multi-Floor Indoor Localization Exploiting Participatory Sensing // IEEE Transactions on Mobile Computing. 2018. № 17(1), pp. 141 - 154. doi: 10.1109/TMC.2017.2698453\

36. Shchekotov M., Pashkin M., Smirnov A. Indoor Navigation Ontology for Smartphone Semi-Automatic Self-Calibration Scenario // FRUCT. 2019. pp. 388-394. 10.23919/FRUCT.2019.8711902.

37. Goehle, Geoff. Gamification and Web-based Homework // PRIMUS. 2013. № 23. 10.1080/10511970.2012.736451.

38. Scikit-learn website, Available at: https://scikitlearn.org/stable/ (accessed July, 2021).

39. Scikit-learn website, Available at:https://scikitlearn.

org/stable/modules/generated/sklearn.model_selectio

n.RandomizedSearchCV.html (accessed July, 2021).