Determining the coordinates of a mobile robot in an industrial space using BLE technology based on RSSI data received from base stations

Authors

DOI:

https://doi.org/10.30837/rt.2022.2.209.18

Keywords:

base stations, RSSI data, local positioning, radio signals, BLE technology, triangulation

Abstract

Existing global positioning technologies cannot be applied indoors, where the signal from satellites or communication towers is significantly reduced or completely absent due to signal weakening in the walls of the building. Wireless network technologies such as Bluetooth or Wi-Fi can also be used in the process of local determining the mobile platforms position in industrial premises. But such methods have a problem with providing the required accuracy. The relevance of these studies is associated with solving the problem of local positioning of mobile robots in a room with an accuracy of ten centimeters. The article presents a comparative analysis of determining coordinates’ principles by the AOA, TOA, TDOA and RSSI methods. It is proposed to use BLE technologies based on the RSSI data received from base stations. Using the triangulation method, formulas are obtained for solving the problem of determining the coordinates of an object moving in space. The software and hardware complex architecture has been developed. It is proposed to use ESP32 modules as base radio stations. The RSSI value is very unstable, so the positioning accuracy will depend on the number of base stations and the additional software tools used.

References

S. Novoselov, "Wireless Sensor Network for Communication Between Base Stations in the Local Positioning System," 2018 International Scientific-Practical Conference Problems of Infocommunications. Science and Technology (PIC S&T), 2018, pp. 383-386, doi: 10.1109/INFOCOMMST.2018.8632140.

S. Novoselov and O. Donskov, "Distributed local positioning system using DWM1000 location chip," 2017 4th International Scientific-Practical Conference Problems of Infocommunications. Science and Technology (PIC S&T), 2017, pp. 489-492, doi: 10.1109/INFOCOMMST.2017.8246445.

M. E. Rusli, M. Ali, N. Jamil and M. M. Din, "An Improved Indoor Positioning Algorithm Based on RSSI-Trilateration Technique for Internet of Things (IOT)," 2016 International Conference on Computer and Communication Engineering (ICCCE), 2016, pp. 72-77, doi: 10.1109/ICCCE.2016.28.

Y. Wang, Xu Yang, Yutian Zhao, Yue Liu and L. Cuthbert, "Bluetooth positioning using RSSI and triangulation methods," 2013 IEEE 10th Consumer Communications and Networking Conference (CCNC), 2013, pp. 837-842, doi: 10.1109/CCNC.2013.6488558.

P. S. Dravya, Ujwal K. Holla, K. N. Pushpalatha. (2020). Indoor Navigation System using BLE and ESP32. 10.22214/irjaset.2020.32089.

M. Golestanian, H. Lu, C. Poellabauer and J. Kenney, "RSSI-Based Ranging for Pedestrian Localization," 2018 IEEE 88th Vehicular Technology Conference (VTC-Fall), 2018, pp. 1-5, doi: 10.1109/VTCFall.2018.8690714.

S. Novoselov and O. Donskov, "Study of mobile device wireless control technology in the visible range of the electromagnetic radiation," 2016 Third International Scientific-Practical Conference Problems of Infocommunications Science and Technology (PIC S&T), 2016, pp. 123-124, doi: 10.1109/INFOCOMMST.2016.7905355.

S. Novoselov, O. Sychova and S. Tesliuk, "Development of the Method Local Navigation of Mobile Robot a Based on the Tags with QR Code and Wireless Sensor Network," 2019 IEEE XVth International Conference on the Perspective Technologies and Methods in MEMS Design (MEMSTECH), 2019, pp. 46-51, doi: 10.1109/MEMSTECH.2019.8817405.

I. Nevludov, O. Sychova, A. Andrusevich, S. Novoselov, D. Mospan and V. Mospan, "Simulation of the Sensor Network of Base Stations in a Local Positioning System in Intelligent Industries," 2020 IEEE Problems of Automated Electrodrive. Theory and Practice (PAEP), 2020, pp. 1-6, doi: 10.1109/PAEP49887.2020.9240842.

I. Nevliudov, S. Novoselov, O. Sychova and S. Tesliuk, "Development of the Architecture of the Base Platform Agricultural Robot for Determining the Trajectory Using the Method of Visual Odometry," 2021 IEEE XVIIth International Conference on the Perspective Technologies and Methods in MEMS Design (MEMSTECH), 2021, pp. 64-68, doi: 10.1109/MEMSTECH53091.2021.9468008.

I. Nevludov, S. Novoselov, O. Sychova, S. Tesliuk. Production Workspace Obstacle Avoidance Mobile Robot Trajectory Modeling 2021: Fifth International Scientific and Technical Conference "COMPUTER AND INFORMATION SYSTEMS AND TECHNOLOGIES" pp.61-62.

I. Nevludov, O. Sychova, O. Reznichenko, S. Novoselov, D. Mospan and V. Mospan, "Control System for Agricultural Robot Based on ROS," 2021 IEEE International Conference on Modern Electrical and Energy Systems (MEES), 2021, pp. 1-6, doi: 10.1109/MEES52427.2021.9598560.

L. Li, Y. Wu, Y. Ren and N. Yu, "A RSSI Localization Algorithm Based on Interval Analysis for Indoor Wireless Sensor Networks," 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, 2013, pp. 434-437, doi: 10.1109/GreenCom-iThings-CPSCom.2013.90.

N. N. Sümer, N. Ataklı and O. Kucur, "Using RSSI-Based Bluetooth Low Energy for Indoor Location Detection," 2020 5th International Conference on Computer Science and Engineering (UBMK), 2020, pp. 83-87, doi: 10.1109/UBMK50275.2020.9219422.

A. Golestani, N. Petreska, D. Wilfert and C. Zimmer, "Improving the precision of RSSI-based low-energy localization using path loss exponent estimation," 2014 11th Workshop on Positioning, Navigation and Communication (WPNC), 2014, pp. 1-6, doi: 10.1109/WPNC.2014.6843302.

J. Wisanmongkol, L. Klinkusoom, T. Sanpechuda, L. Kovavisaruch and K. Kaemarungsi, "Multipath Mitigation for RSSI-Based Bluetooth Low Energy Localization," 2019 19th International Symposium on Communications and Information Technologies (ISCIT), 2019, pp. 47-51, doi: 10.1109/ISCIT.2019.8905164.

S. Saxena, A. Pandey and S. Kumar, "A Multistage RSSI-based Scheme for Node Compromise Detection in IoT Networks," 2019 IEEE 16th India Council International Conference (INDICON), 2019, pp. 1-4, doi: 10.1109/INDICON47234.2019.9029092.

S. Cortesi, M. Dreher and M. Magno, "Design and Implementation of an RSSI-Based Bluetooth Low Energy Indoor Localization System," 2021 17th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), 2021, pp. 163-168, doi: 10.1109/WiMob52687.2021.9606272.

P. Sthapit, H. -S. Gang and J. -Y. Pyun, "Bluetooth Based Indoor Positioning Using Machine Learning Algorithms," 2018 IEEE International Conference on Consumer Electronics – Asia (ICCE-Asia), 2018, pp. 206-212, doi: 10.1109/ICCE-ASIA.2018.8552138.

S. Subedi, G. -R. Kwon, Seokjoo Shin, Suk-seung Hwang and Jae-Young Pyun, "Beacon based indoor positioning system using weighted centroid localization approach," 2016 Eighth International Conference on Ubiquitous and Future Networks (ICUFN), 2016, pp. 1016-1019, doi: 10.1109/ICUFN.2016.7536951.

A. Noertjahyana, I. A. Wijayanto and J. Andjarwirawan, "Development of Mobile Indoor Positioning System Application Using Android and Bluetooth Low Energy with Trilateration Method," 2017 International Conference on Soft Computing, Intelligent System and Information Technology (ICSIIT), 2017, pp. 185-189, doi: 10.1109/ICSIIT.2017.64.

Published

2022-06-24

How to Cite

Nevliudov, I. ., Novoselov, S. ., Sychova, O. ., & Tesliuk, S. . (2022). Determining the coordinates of a mobile robot in an industrial space using BLE technology based on RSSI data received from base stations. Radiotekhnika, 2(209), 185–191. https://doi.org/10.30837/rt.2022.2.209.18

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Articles