Abstract
This paper presents and evaluates one approach to the problems of automatic control of a vehicle movement in a large outdoor area. The positioning of the vehicle in the area is provided by iBeacons, located at the edges of the given surface. The iBeacon is a small and low-power device which periodically transmits its UUID (Universally Unique Identifier) number through the interface of a Bluetooth 4.x. The vehicle should be able to calculate its position according to the power of the signal, considering the location of the iBeacons. To be more specific, the triangulation method is applied to determine the position. According to the set of experiments presented at the end of the paper, the position error of a robotic vehicle is mostly less then 1 m.
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References
Sharma, K.R., Honc, D., Dusek, F.: Sensor fusion for prediction of orientation and position from obstacle using multiple IR sensors an approach based on Kalman filter. In: 2014 International Conference on Applied Electronics, Pilsen, pp. 263–266 (2014). https://doi.org/10.1109/AE.2014.7011716
Sharma, K.R., Dusek, F., Honc, D.: Comparitive study of predictive controllers for trajectory tracking of non-holonomic mobile robot. In: 2017 21st International Conference on Process Control (PC), Strbske Pleso, pp. 197–203 (2017). https://doi.org/10.1109/PC.2017.7976213
Guan, Z., Zhang, B., Zhang, Y., Zhang, S., Wang, F.: Delaunay triangulation based localization scheme. In: 2017 29th Chinese Control And Decision Conference (CCDC), Chongqing, pp. 2627–2631 (2017). https://doi.org/10.1109/CCDC.2017.7978958
Mahapatra, R.K., Shet, N.S.V.: Experimental analysis of RSSI-based distance estimation for wireless sensor networks. In: 2016 IEEE Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER), Mangalore, pp. 211–215 (2016). https://doi.org/10.1109/DISCOVER.2016.7806221
Pradeep, B.V., Rahul, E.S., Bhavani, R.R.: Follow me robot using bluetooth-based position estimation. In: 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Udupi, pp. 584–589 (2017). https://doi.org/10.1109/ICACCI.2017.8125903
Schwiegelshohn, F., Wehner, P., Werner, F., Gohringer, D., Hubner, M.: Enabling indoor object localization through Bluetooth beacons on the RADIO robot platform. In: 2016 International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation (SAMOS), Agios Konstantinos, pp. 328–333 (2016). https://doi.org/10.1109/SAMOS.2016.7818366
Zhou, M., Lin, J., Liang, S., Du, W., Cheng, L.: A UAV patrol system based on Bluetooth localization. In: 2017 2nd Asia-Pacific Conference on Intelligent Robot Systems (ACIRS), Wuhan, pp. 205–209 (2017). https://doi.org/10.1109/ACIRS.2017.7986094
Gorovyi, I., Roenko, A., Pitertsev, A., Chervonyak, I., Vovk, V.: Real-time system for indoor user localization and navigation using bluetooth beacons. In: 2017 IEEE First Ukraine Conference on Electrical and Computer Engineering (UKRCON), Kiev, pp. 1025–1030 (2017). https://doi.org/10.1109/UKRCON.2017.8100406
Gu, Y., Ren, F.: Energy-efficient indoor localization of smart hand-held devices using bluetooth. IEEE Access 3, 1450–1461 (2015). https://doi.org/10.1109/ACCESS.2015.2441694
Apple Developer, “iBeacon”. https://developer.apple.com/ibeacon/. Accessed 03 Jan 2018
NORDIC SEMICONDUCTOR, “NRF51822 Bluetooth Smart Beacon Kit”. https://www.nordicsemi.com/eng/Products/Bluetooth-low-energy/nRF51822-Bluetooth-Smart-Beacon-Kit. Accessed 03 Jan 2018
Aman, M.S., Jiang, H., Quint, C., Yelamarthi, K., Abdelgawad, A.: Reliability evaluation of iBeacon for micro -localization. In: 2016 IEEE 7th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), New York, NY, pp. 1–5 (2016). https://doi.org/10.1109/UEMCON.2016.7777904
Hereman, W., Murphy, W.S.: Determination of a Position in Three Dimensions Using Trilateration and Approximate Distances. https://inside.mines.edu/~whereman/papers/Murphy-Hereman-Trilateration-MCS-07-1995.pdf. Accessed 03 Jan 2018
Miao, Z., Jiang, X.: Further properties and a fast realization of the iterative truncated arithmetic mean filter. IEEE Trans. Circuits Syst. II Express Briefs 59(11), 810–814 (2012). https://doi.org/10.1109/TC-SII.2012.2218473
Qi, W., Cong, S., Zhang, P.: Robust steady-state Kalman estimators for discrete-time system with uncertain noise variances. In: 2016 35th Chinese Control Conference (CCC), Chengdu, pp. 2961–2966 (2016). https://doi.org/10.1109/ChiCC.2016.7553814
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The work has been supported by the Funds of University of Pardubice, Czech Republic. This support is very gratefully acknowledged.
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Dvorak, M., Dolezel, P. (2019). An IoT Approach to Positioning of a Robotic Vehicle. In: Silhavy, R. (eds) Software Engineering and Algorithms in Intelligent Systems. CSOC2018 2018. Advances in Intelligent Systems and Computing, vol 763. Springer, Cham. https://doi.org/10.1007/978-3-319-91186-1_12
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DOI: https://doi.org/10.1007/978-3-319-91186-1_12
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