Rancang Bangun Low-Budget Autonomous Quadcopter



DOI: https://doi.org/10.25077/metal.5.2.60-66.2021

Author(s)

Budi Hartono (Politeknik Negeri Bandung)

Abstract


Quadcopter is an unstable flying vehicle. The flight controller regulates the rotational speed of the four motors, so that each propeller produces the lift required for the quadcopter to fly stable. It is interesting to know whether the use of generic quadcopter components obtained in the market can be mutually compatible. A stable and controllable quadcopter is a requirement for a quadcopter to fly autonomously. This research focusses on design a low-budget autonomous quadcopter. The research method consists of three main stages. First, the design and build phase of the quadcopter. The main frame and quadcopter arms are designed with a diagonal distance between the rotors of 45 cm. The basic components of the quadcopter are selected which are mutually compatible and assembled on the frame and arms. The flight controller is connected to the GPS, transmitter, and receiver. The autonomous system also involves a ground control system in the form of a Mission Planner. Second, the flight test stage is setting the PID constant so that the quadcopter can fly stable. PID tuning produces proportional constants of 0.088, integrals of 0.016, and derivatives of 0.008. Third, the autonomous flight test stage. The success of autonomous flying is known by analyzing the difference in input waypoint coordinates through the Mission Planner against the results of low-budget GPS receiver readings on autonomous flying missions. GPS accuracy was analyzed by calculating the 2DRMS and CEP values. The best value of 2DRMS = 1.56 meters and CEP = 0.64 meter occurred at Waypoint #2.

Keywords


autonomous quadcopter; low-budget; akurasi GPS

Full Text:

PDF

References


A. R. Krishnan, V. R. Jisha, and K. Gokulnath, “Path Planning of an Autonomous Quadcopter based Delivery System,” in Proceedings of 2018 Conference on Emerging Trends and Innovations in Engineering and Technological Research (ICETIETR), 2018.

R. Kowsalya and P. Eswaran, “Development of Autonomous Quadcopter for Farmland Surveillance,” in ICSCS, 2018, pp.80-87.

A. D. Acharya, S. Bhandari, and Z. Aliyazicioglu, “Autonomous Navigation of a Quadcopter in Indoor Environment,” presented at the AIAA SciTech Forum, California, 2019.

J. D. R. Vivek, M. Mariappan, and M. J. Rickson, “Autonomous Quadcopter for Surveillance and Monitoring,” IJARCET, vol. 7, issue 4, April, 2018.

S. Gururajan and Y. Bay, “Autonomous “Figure-8” Flights of a Quadcopter: Experimental Datasets,” MDPI Data Journal, vol. 4, Isue 1, March, 2019.

Y. Bay and S. Gururajan, “Evaluation of a Baseline Controller for Autonomous “Figure-8” Flights of a Morphing Geometry Quadcopter: Flight Performance,” MDPI Drones Journal, vol. 70, Issue 3, August, 2019.

D. Lakshmanan, et al., “Performance Analysis of Medium Altitude Low-Cost Autonomous Quadcopter,” IOP Conference Series: Materials Science and Engineering, vol. 764, no. 012037, 2020.

F. van Diggelen, “Update: GNSS Accuracy: Lies, Damn Lies, and Statistics,” viewed at April 21, 2020, .

E. D. Kaplan and C. J. Hegarty, “Performance of stand-alone GNSS,” in Understanding GPS/GNSS, Principles and Applications, 3rd ed. Boston, Artech House, 2017, ch. 11, sec. 2.3, pp. 675.

F. El Khoury and A. Zgheib, “GPS Antenna,” in Building a Dedicated GSM GPS Module Tracking System for Fleet Management, Hardware and Software, Boca Raton, CRC Press, 2018, ch. 2, sec. 10, pp. 25.

Y. B. Sebbane, “Modeling,” in Smart Autonomous Aircraft, Flight Control and Planning for UAV, Boca Raton, CRC Press, 2016, ch. 2, sec. 6.1, pp. 80.


StatisticsArticle Metrics

This article has been read : 401 times
PDF file viewed/downloaded : 127 times

Copyright (c) 2021 Budi Hartono

 


View METAL's Stats

 

Creative Commons License

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