Autopilot Unmanned Smart Boat Vehicle (AUSV) Communication with LoRa RFM95

Afif Zuhri Arfianto - Dept. of Marine Electrical Engineering, Politeknik Perkapalan Negeri Surabaya, Surabaya, Indonesia
Mohammad Basuki Rahmat - Dept. of Marine Electrical Engineering, Politeknik Perkapalan Negeri Surabaya, Surabaya, Indonesia
Fuad Dhiyavia - Dept. of Marine Electrical Engineering, Politeknik Perkapalan Negeri Surabaya, Surabaya, Indonesia
Tri Budi Santoso - Politeknik Elektronika Negeri Surabaya, Surabaya, Indonesia
Nyoman Gunantara - Dept. of Electrical Engineering, Universitas Udayana, Bali, Indonesia
Eko Supriyanto - Dept. of Electrical Engineering, Politeknik Negeri Semarang, Semarang, Indonesia
Valian Yoga Pudya Ardhana - Universitas Qamarul Huda Badaruddin, Lombok Tengah, Indonesia


Citation Format:



DOI: http://dx.doi.org/10.30630/joiv.4.4.492

Abstract


Autopilot is a system control application on moving vehicles such as airplanes, helicopters, or boat, which serves to stabilize the direction of motion in the desired time and the programmed path's direction. the autopilot control system is controlled by a series of microcontrollers and GPS that has the function to be able to determine and the desired object. This control system is designed with electrical system controls that utilize microcontrollers, sensor  and GPS as control media. The development of autopilot prototypes is used for testing new control algorithms and the reliability of other electronic components such as sensors and microprocessors. A control system is needed to control the boat to its destination. The relatively accurate system dynamics model affects the steering performance of the autopilot system. The system in question can be considered a boat with an actuator rudder, which experiences external disturbances. this system is broadly divided into two parts: the control station part and the autonomous boat part. These two parts communicate with each other using LoRa device. The data sent from the control station to the autonomous boat is target latitude and longitude coordinates. The autonomous boat will send feedback in the form of boat latitude and longitude coordinates so that users can find out the current location of the boat. Autonomous Boat also provides feedback to the control station via LoRa in the form of boat coordinates so that users can find out the current location of the boat and whether the boat has reached the specified coordinates. The control station will send feedback from the boat to a database that can be monitored via the website to find out the boat's current condition on the website. Based on the  results that have been obtained in the analysis and testing of the system. GPS sensor used in autonomous boat Ublox NEO-7m has an accuracy level with an average distance value of 3.220921 meters with the lowest cold start time of 7 seconds.  Compass sensor used in autonomous boat CMPS11 has an accuracy level with an average value of 3.041667 degrees. Communication distance between autonomous boat and control station using LoRa with 5dBi antenna can reach 1406.79 meters in condition without obstruction between nodes.  Data delivery system can be successfully sent from user to autonomout boat and sending feedback back to user. Delay update of boat coordinate data on interface has the lowest average of 30.8 seconds. Based on turning circle test results, autonomous boat is able to create imperfect circles with a radius of 8,364 m.

Keywords


Autopilot Unmanned Smart Boat Vehicle ; GPS ; LoRA ;

Full Text:

PDF

References


T. Porathe, Å. Hoem, Ø. J. Rødseth, K. Fjørtoft, and S. O. Johnsen, “At least as safe as manned shipping? Autonomous shipping, safety and ‘human error,’” Saf. Reliab. Soc. a Chang. World. Proc. ESREL 2018, June 17-21, 2018, Trondheim, Norw., 2018.

A. Z. Arfianto et al., “Unmanned Vehicle Using Received Signal Strength Indicator (RSSI) in Instant Beverage Industry,” in 2019 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation (ICAMIMIA), 2019, pp. 340–343, doi: 10.1109/ICAMIMIA47173.2019.9223401.

M. Rifai, A. Z. Arfianto, and A. T. Muzazanah, “Radio Frequency-based Smart Control for Lighting in Public Service,” in Journal of Physics: Conference Series, 2020, vol. 1595, no. 1, doi: 10.1088/1742-6596/1595/1/012026.

M. B. Rahmat, A. Z. Arfianto, T. B. Santoso, T. Santoso, and N. Gunantara, “Development of Autopilot Unmanned Smartboat Vehicle (AUSV) Based on Fishing Zone Prediction Map,” in Journal of Physics: Conference Series, 2020, vol. 1595, no. 1, doi: 10.1088/1742-6596/1595/1/012036.

B. E. Putra et al., “Multi Automated Guided Vehicle (AGV) cardboard carrier using wireless communication,” IOP Conf. Ser. Earth Environ. Sci., vol. 340, p. 012009, Oct. 2019, doi: 10.1088/1755-1315/340/1/012009.

R. A. Atmoko, D. Yang, M. I. Abas, A. Z. Arfianto, and R. Rahim, “Teleoperation cloud industrial robot using XMPP protocol,” Int. J. Recent Technol. Eng., vol. 8, pp. 6280–6284, 2019.

T. A. Putra et al., “KOMUNIKASI DATA BLUETOOTH UNTUK PERANGKAT INFORMASI PERSEBARAN IKAN (PORTABLE VIRTUAL ASSISTANT) PADA KAPAL NELAYAN TRADISIONAL,” J. Teknol. Marit., vol. 1, no. 2, pp. 45–52, 2018.

L. R. Ribeiro and N. M. F. Oliveira, “UAV autopilot controllers test platform using Matlab/Simulink and X-Plane,” in 2010 IEEE Frontiers in Education Conference (FIE), 2010, pp. S2H-1.

E. Capello, G. Guglieri, and G. Ristorto, “Guidance and control algorithms for mini UAV autopilots,” Aircr. Eng. Aerosp. Technol., 2017.

S. Melnychuk, W. Foote, Z. Q. Zhao, and F. C. Moore, “Target acquisition and tracking system.” Google Patents, Oct. 22, 2009.

T. Li, A. M. Esteban, and S. Zhang, “Enhanced disturbance rejection control based test rocket control system design and validation,” ISA Trans., vol. 84, pp. 31–42, 2019.

C. Yan, W. Xu, and J. Liu, “Can you trust autonomous vehicles: Contactless attacks against sensors of self-driving vehicle,” DEF CON, vol. 24, no. 8, p. 109, 2016.

M. Liu, G. K. Egan, and F. Santoso, “Modeling, autopilot design, and field tuning of a UAV with minimum control surfaces,” IEEE Trans. Control Syst. Technol., vol. 23, no. 6, pp. 2353–2360, 2015.

R. K. Kodali, K. Y. Borra, S. S. GN, and H. J. Domma, “An IoT based smart parking system using LoRa,” in 2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), 2018, pp. 151–1513.

A. M. Yousuf, E. M. Rochester, B. Ousat, and M. Ghaderi, “Throughput, coverage and scalability of LoRa LPWAN for internet of things,” in 2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS), 2018, pp. 1–10.

M. K. Hasin, “DETEKSI LOKASI PESEBARAN IKAN PADA PETA DIGITAL UNTUK PORTABLE VIRTUAL ASSISTANCE (PVA) NELAYAN TRADISIONAL,” 2017.




Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

__________________________________________________________________________
JOIV : International Journal on Informatics Visualization
ISSN 2549-9610  (print) | 2549-9904 (online)
Organized by Department of Information Technology - Politeknik Negeri Padang, and Institute of Visual Informatics - UKM and Soft Computing and Data Mining Centre - UTHM
Published by Department of Information Technology - Politeknik Negeri Padang
W : http://joiv.org
E : joiv@pnp.ac.id, hidra@pnp.ac.id, rahmat@pnp.ac.id

View JOIV Stats

Creative Commons License is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.