An open-source UAV digital twin framework: a case study on remote sensing in the Andean Mountains

The increasing demand for unmanned aerial vehicles (UAVs) in the aerospace industry highlights the need for precise simulation environments, especially in remote regions. This study develops an open-source framework for a customized UAV simulation environment using ROS-Gazebo and Ardupilot. The method includes a realistic reconstruction of the environment based on free satellite information, the ROS-Gazebo scheme for modeling and testing the UAV platform, and Ardupilot for mission design and deployment. The methodology aims to reduce costs in surveillance missions and conduct more efficient operations in high-risk and challenging areas. To evaluate the accuracy of UAV positioning for simulating real missions, an experimental validation of the digital twin was carried out using real flight data records from two self-built UAVs equipped with the open-source Ardupilot autopilot. One of the aircraft, a fixed-wing UAV, was tested near the Antisana volcano (4500 meters above sea level), where wind gusts reached speeds of 9 to 12 m/s. These tests revealed maximum errors of 9% in the Z-axis trajectory (altitude). The other aircraft, a quadcopter, was evaluated in the Parque Carolina in Quito (2800 meters above sea level), with wind gusts between 5 and 7 m/s, showing an error of 8% in the Z-axis trajectory. The presented results demonstrate the suitability of the proposed method for emulating complex missions using digital twin models. In this regard, the main contribution of this work lies in its potential for the precise prediction of flight missions in the Z-axis, a crucial variable for avoiding collisions in mountainous regions.