Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREM68280
Volume:
10 |
10 |
Oct 2026
Pages:
1-5
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Electronic & Telecommunication Engineering
JSPM Bhivrabai Sawant polytechnic wagholi pune
Electronic & Telecommunication Engineering
JSPM Bhivrabai Sawant polytechnic wagholi pune
Electronic & Telecommunication Engineering
JSPM Bhivrabai Sawant polytechnic wagholi pune
Electronic & Telecommunication Engineering
JSPM Bhivrabai Sawant polytechnic wagholi pune
Electronic & Telecommunication Engineering
JSPM Bhivrabai Sawant polytechnic wagholi pune
Unmanned Aerial Vehicles (UAVs) have witnessed widespread adoption in civilian and industrial applications ranging from precision agriculture and aerial survey mapping to infrastructure inspection and disaster monitoring. However, conventional multirotor drones heavily depend on continuous manual radio-frequency (RF) teleoperation from a human pilot on the ground. When unexpected operational failures occur—such as radio control link interruption, signal degradation, visual line-of-sight loss, or critically low battery voltage—the aircraft is prone to uncontrolled drift, flyaway incidents, or severe physical crashes. This paper presents the design, hardware implementation, and performance evaluation of an autonomous Return-to-Home (RTH) quadcopter drone using an embedded ESP32 microcontroller and a high-precision NEO-6M GPS navigation module. The proposed system continuously monitors flight attitude via an MPU6050 6-DOF inertial measurement unit and processes real-time geographical coordinates via the NMEA protocol. Prior to takeoff, the flight controller automatically acquires a high-confidence GPS fix and records the precise launch coordinates as the "Home Point". During flight, a dedicated failsafe state machine continuously monitors 2.4 GHz radio link integrity and battery voltage levels. When an RF loss, battery drop below 10.5 V, or manual pilot command is detected, the drone autonomously executes an emergency RTH routine: climbing to a predefined clearance altitude of 15 m to avoid terrain obstacles, computing target bearing and distance using the Haversine navigational formula, cruising back to the home perimeter, loitering to dissipate turbulence, and performing a smooth vertical auto-landing and motor disarm. Field testing across ten simulated emergency scenarios demonstrated reliable failsafe trigger response within 1.2 seconds, autonomous navigation cruise at 5.2 m/s, and landing accuracy within 1.2 to 1.8 meters of the launch site, establishing a dependable and cost-effective embedded safety solution for modern UAV platforms.
KEYWORDS
The developed GPS-Based Return-to-Home Drone provides a reliable, cost-effective embedded failsafe architecture. By combining the ESP32 microcontroller with a NEO-6M GPS receiver and MPU6050 IMU, the system eliminates catastrophic flyaways and delivers dependable recovery across civilian UAV missions.
[1] K. Alexis, G. Nikolakopoulos, and A. Tzes, "Model predictive quadrotor control: attitude, altitude and position experimental studies," IET Control Theory & Applications, vol. 6, no. 12, pp. 1812–1827, 2012. [2] P. Castillo, R. Lozano, and A. E. Dzul, Modelling and Control of Mini-Flying Machines, London: Springer-Verlag, 2005. [3] S. Bouabdallah, P. Murrieri, and R. Siegwart, "Design and control of an indoor micro quadrotor," in Proc. IEEE Int. Conf. Robot. Autom. (ICRA), New Orleans, LA, 2004, pp. 4393–4398. [4] M. W. Mueller, M. Hehn, and R. D'Andrea, "A relaxed barrier function approach to feedforward trajectory generation for quadrocopters," IEEE Trans. Robot., vol. 31, no. 4, pp. 877–889, 2015. [5] H. Chao, Y. Gu, and M. Napolitano, "A survey of optical flow techniques for UAV navigation applications," Prog. Aerosp. Sci., vol. 83, pp. 62–72, 2016. [6] R. Mahony, T. Hamel, and J.-M. Pflimlin, "Nonlinear complementary filters on the special orthogonal group," IEEE Trans. Autom. Control, vol. 53, no. 5, pp. 1203–1218, 2008. [7] J. F. Vasconcelos, R. Cunha, C. Silvestre, and P. Oliveira, "A nonlinear position and heading filter for UAVs using IMU and GPS," in Proc. 47th IEEE Conf. Decis. Control, Cancun, Mexico, 2008, pp. 4040–4045. [8] T. B. Schon, F. Gustafsson, and P.-J. Nordlund, "Marginalized particle filters for mixed linear/nonlinear state-space models," IEEE Trans. Signal Process., vol. 53, no. 7, pp. 2279–2289, 2005. [9] A. Nemra and N. Aouf, "Robust INS/GPS sensor fusion for UAV navigation using RKF," IEEE Trans. Aerosp. Electron. Syst., vol. 46, no. 2, pp. 589–604, 2010. D. Scaramuzza et al., "Vision-controlled micro flying robots: from system design to autonomous navigation," IEEE Robot. Autom. Mag., vol. 21, no. 3, pp. 26–40, 2014.
Publication Date
10/26/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
2
Total views since publication
PDF Downloads
8
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...