Komparasi Akurasi Global Posistion System (GPS) Receiver U-blox Neo-6M dan U-blox Neo-M8N pada Navigasi Quadcopter

firdaus firdaus; Ismail Ismail

doi:10.30630/eji.12.1.137

firdaus firdaus politeknik negeri padang
Ismail Ismail Politeknik Negeri Padang

DOI: https://doi.org/10.30630/eji.12.1.137

Keywords: GPS, Ublox, navigasi, quadcopter

Abstract

Quadcopter UAV development is happening very rapidly. One of the most important in the navigation system is the hardware and software or the used algorithm. Improving the accuracy of Quadcopter positioning is one of the most popular topics in the UAV field. This position parameter is determined by the GPS module. GPS modules produce position and speed information with a high degree of precision, but these modules are vulnerable to interference. Thus, GPS signals are often lost. Moreover, GPS measurements also cannot meet the real-time requirements. Both GPS U-Blox variants, Neo-6M, and M8N become the main problem by testing which are more precise and consistent with the actual geographical position indicated by Google map. Data obtained from GPS receivers are parsed and converted to longitude and latitude coordinates by the ATmega328 IC microcontroller then combine with real-time data from RTC DS1370 and stored continuously in a 2 GB SD card. The transferred geographic coordinate data would be retrieved and converted to CSV format so that it can be plotted into a map. The test was conducted where the Neo-6M GPS receiver was carried out

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References

[1] Arya Adi Saputra, Andi Dharmawan. Rancang Bangun Quadcopter untuk Pemantauan Kadar Karbon Monoksida di Udara. IJEIS, Vol.3, No.1, April 2013, pp. 11~22
[2] Gembong Edhi Setyawan, Eko Setiawan, Wijaya Kurniawan.. Sistem Kendali Ketinggian Quadcopter Menggunakan PID. Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK) Vol. 2, No. 2, Oktober 2015, hlm. 125-131
[3] Futuhal Arifin, Ricky Arifandi Daniel, Didit Widiyanto. Autonomous Detection And Tracking Of An Object Autonomously Using Ar.Drone Quadcopter. Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information). 7/1 (2014), 11-17
[4] J. Wang, M. Garratt, A. Lambert, J. Wang, S. Han, and D. Sinclair, Integration of GPS/INS/vision sensors to navigate unmanned aerial vehicles, vol. 37. 2008.
[5] M. Gowda, J. Manweiler, A. Dhekne, R. R. Choudhury, and J. D. Weisz, “Tracking drone orientation with multiple GPS receivers,” Proc. Annu. Int. Conf. Mob. Comput. Networking, MOBICOM, vol. 0, no. 1, pp. 280–293, 2016, doi: 10.1145/2973750.2973768.
[6] W. Li and Z. Fu, “Unmanned aerial vehicle positioning based on multi-sensor information fusion,” Geo-Spatial Inf. Sci., vol. 21, no. 4, pp. 302–310, 2018, doi: 10.1080/10095020.2018.1465209.
[7] R. K. S. Sravan kumar N, “Design And Control Implementation Of Quadcopter,” Int. Adv. Res. J. Sci. Eng. Technol., vol. 3, no. 2, p. 4, 2016.
[8] A. Singh Rajpoot, N. Gadani, and S. Kalathia, “Development of Arduino Based Quadcopter,” Int. Adv. Res. J. Sci. Eng. Technol., vol. 3, no. 6, pp. 252–259, 2016, doi: 10.17148/IARJSET.2016.3649.
[9] A. Koubaa and B. Qureshi, “DroneTrack: Cloud-Based Real-Time Object Tracking Using Unmanned Aerial Vehicles over the Internet,” IEEE Access, vol. 6, pp. 13810–13824, 2018, doi: 10.1109/ACCESS.2018.2811762.
[10] J. Kwak and Y. Sung, “Autonomous UAV Flight Control for GPS-Based Navigation,” IEEE Access, vol. 6, pp. 37947–37955, 2018, doi: 10.1109/ACCESS.2018.2854712.
[11] T. C. Mallick, M. A. I. Bhuyan, and M. S. Munna, “Design & Implementation of an UAV (Drone) with Flight Data Record,” 2016 Int. Conf. Innov. Sci. Eng. Technol. ICISET 2016, 2017, doi: 10.1109/ICISET.2016.7856519.
[12] U-blox, “NEO-6 GPS Modules Data Sheet,” Www.U-Blox.Com, p. 25, 2017.
[13] D. Sheet, “NEO-M8.”