Advanced Unmanned Aerial Vehicle (UAV) with Hybrid Propulsion and AI-Based Autopilot System

Abstract

This paper presents the design and development of an advanced Unmanned Aerial Vehicle (UAV) equipped with a hybrid propulsion system, combining gasoline engines and solar panels to enhance flight endurance. The UAV integrates cutting-edge navigation technologies, including GPS, gyroscopic stabilization, real-time computer vision, and AI-powered autopilot. The project aims to deliver long-range, high-efficiency aerial operations for applications such as disaster relief, environmental monitoring, military reconnaissance, and smart delivery systems. Key features include real-time telemetry transmission, autonomous obstacle avoidance, payload delivery mechanisms, and robust ground control with video feedback.

Introduction

This project presents a hybrid-powered UAV designed for autonomous navigation and payload delivery in diverse, remote environments. The UAV combines a high-torque gasoline engine with solar panels for extended flight duration and uses AI and advanced sensors for real-time decision-making, mapping, and surveillance.

Key hardware includes gyroscopic and GPS sensors, vision and thermal cameras, long-range RF communication modules, and LiPo batteries. The control system centers on an Arduino Mega flight controller, supported by ground control with joystick input and telemetry displays.

The communication system uses a hybrid setup—LoRa for long-range, low-power links, and Wi-Fi/satellite for video and telemetry—ensuring reliability even in GPS-denied areas. Propulsion is managed by a gasoline engine with brushless electric start and monitored by onboard sensors.

AI integration via Raspberry Pi enables autonomous flight with object recognition, obstacle avoidance, and adaptive routing. Payload delivery is controlled by a servo-operated latch system for precise drops at GPS-specified locations.

Field tests demonstrate stable flight over 2 hours and 3 km range, with accurate payload release within 2 meters. Future enhancements include AI object tracking, swarm coordination, improved solar efficiency, 5G integration, and lighter airframes.

Conclusion

This project showcases the potential of hybrid UAV systems equipped with smart features for autonomous and long-range missions. With modular architecture and scalable design, the UAV can adapt to various civil, military, and industrial applications.

References

[1] Arduino Documentation [2] Raspberry Pi AI Toolkit [3] LoRa Communication Protocols [4] IEEE Journals on UAV Swarm Intelligence [5] Research on Hybrid UAV Systems - Springer, 2023

Copyright

Copyright © 2025 Anand Rawat. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.