Open Access
VTOL UAV digital twin for take-off, hovering and landing in different wind conditions
(Elsevier, 2023) Aláez Gómez, Daniel; Olaz Moratinos, Xabier; Prieto Míguez, Manuel; Villadangos Alonso, Jesús; Astrain Escola, José Javier; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Gobierno de Navarra / Nafarroako Gobernua
With UAVs becoming increasingly popular in the industry, vertical take-off and landing (VTOL) convertiplanes are emerging as a compromise between the advantages of planes and multicopters. Due to their large wing surface area, VTOL convertiplanes are subject to a strong wind dependence on critical phases such as take-off, landing, and hovering. Developing a new and improved unmanned aerial vehicle (UAV) is often expensive and associated with failures and accidents. This paper proposes the dynamic characterization of a commercial VTOL convertiplane UAV in copter mode and provides a novel method to estimate the aerodynamic forces and moments for any possible wind speed and direction. Starting from Euler’s equations of rigid body dynamics, we have derived the mathematical formulation to precisely consider aerodynamic forces and moments caused by any wind speed and direction. This unique approach will allow for VTOL convertiplane UAVs to be trained and tested digitally in takeoff, hovering, and landing maneuvers without the cost and hassle of physical testing, and the dependence on existing wind conditions. A digital twin of a VTOL convertiplane UAV in copter mode has been modeled and tested in the Gazebo robotics simulator. Take-off, hovering and landing maneuvers have been compared with and without the wind physics model. Finally, the simulator has been tested against real flight conditions (reproducing the mean wind speed and direction only), showing a natural and realistic behavior.
Embargo
Digital twin development for VTOL UAVs
(2024) Aláez Gómez, Daniel; Villadangos Alonso, Jesús; Astrain Escola, José Javier; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
The use of vertical take-off and landing (VTOL) drones in various industries is becoming increasingly popular. However, the democratization of drones also raíces significant concerns about safety during their operations. Their relatively new technology and growing interest often lead to the use of undertested vehicles in missions where safety is critical. To address these risks and reduce the costs associated with experimental flights of new aircraft, the implementation of high-fidelity emulators is proposed. These advanced emulators, known as digital twins, have seen exponential growth in popularity in recent years. This thesis addresses the complete process of developing digital twins for VTOL unmanned aerial vehicles (UAVs). Initially, we propose a digital twin development model based on a variation of the double diamond design process. After identifying critical systems in two types of VTOL UAVs, a hexacopter and a commercial tiltrotor aircraft, we have developed a mathematical model to characterize aerodynamic, gravitational, and propulsive actions. Propulsive actions are measured through experimental tests on a motor test bench. Gravitational actions are determined using precise computeraided design/computer-aided manufacturing (CAD/CAM) models and experi mental measurements. Finally, aerodynamic actions are obtained through a novel aerodynamic model, which calculates the complete aircraft aerodynamics based on the incident wind direction, relying on numerous computational fluid dynamics (CFD) simulations. To mitigate the costs associated with CFD simulations, we employ surrogate models, developing and validating a surrogate model capable of potentially reducing the number of simulations by up to 50%. Another critical subsystem is the communication system. Based on experimental measurements, we fit and validate a path loss model for Received Signal Strength Indicator (RSSI) to estimate signal losses as a function of the aircraft’s position and attitude. This model allows us to predict and quantify the impact of the UAV’s attitude and position relative to the communication source. Ultimately, the digital twin is successfully implemented and validated using both hardware-in-the-loop and X-Plane for a commercial flight controller, as well as software-in-the-loop and Gazebo for an open-source controller (Ardupilot). This comprehensive validation approach ensures that the digital twin accurately replicates the behavior and performance of the actual UAV systems, regardless of the emulation engine and architecture chosen.
Open Access
Digital twin modelling of open category UAV radio communications: a case study
(Elsevier, 2024) Aláez Gómez, Daniel; López Iturri, Peio; Celaya Echarri, Mikel; Azpilicueta Fernández de las Heras, Leyre; Falcone Lanas, Francisco; Villadangos Alonso, Jesús; Astrain Escola, José Javier; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza; Institute of Smart Cities - ISC; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
The modeling of radio links plays a crucial role in achieving mission success of unmanned aerial vehicles (UAVs). By simulating and analyzing communication performance, operators can anticipate and address potential challenges. In this paper, we propose a full-featured UAV software-in-the-loop digital twin (SITL-DT) for a heavy-lifting hexacopter that integrates a radio link module based on an experimental path loss model for ‘Open’ category Visual Line of Sight (VLOS) conditions and drone-antenna radiation diagrams obtained via electromagnetic simulation. The main purpose of integrating and simulating a radio link is to characterize when the communication link can be conflicting due to distance, the attitude of the aircraft relative to the pilot, and other phenomena. The system architecture, including the communications module, is implemented and validated based upon experimental flight data.
Open Access
UAVradio: Radio link path loss estimation for UAVs
(Elsevier, 2024) Aláez Gómez, Daniel; Celaya Echarri, Mikel; Azpilicueta Fernández de las Heras, Leyre; Villadangos Alonso, Jesús; Estadística, Informática y Matemáticas; Ingeniería Eléctrica, Electrónica y de Comunicación; Institute of Smart Cities - ISC; Estatistika, Informatika eta Matematika; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
The UAVRadio Python module is a comprehensive toolkit designed to facilitate the analysis and prediction of radio signal path loss in Unmanned Aerial Vehicle (UAV) communication scenarios. The module encompasses a range of path loss models referenced from established literature, offering users a powerful and flexible framework for estimating signal attenuation in different UAV communication links. It is a versatile and modular tool that enables simple integration for optimizing UAV communication systems and ensuring reliable wireless connectivity in a variety of operational scenarios. The utility of this package is demonstrated through two relevant examples: an experimentally fit model comparison with other implemented models, and a UAV digital twin implementation example comparing different available models and frequencies. The examples are provided in the code repository along with comprehensive documentation.
Open Access
On constructing efficient UAV aerodynamic surrogate models for digital twins
(IEEE, 2024-07-31) Aláez Gómez, Daniel; Prieto Míguez, Manuel; Villadangos Alonso, Jesús; Astrain Escola, José Javier; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Gobierno de Navarra / Nafarroako Gobernua
Aerodynamic modeling and optimization for unmanned aerial vehicles (UAVs) are complex and computationally intensive tasks. Surrogate models have emerged as a powerful tool for increasing efficiency in the aircraft design and optimization process. We review and evaluate some modeling techniques, such as artificial neural networks and support vector regression, showing that Gaussian process regression generally provides a well-performing solution to this type of problem. We propose an active learning algorithm based on the relevance factor, that combines bias estimated from nearest-neighbor Euclidean distance and variance, to achieve higher accuracy with fewer compuational fluid dynamics (CFD) simulations. The obtained performance is evaluated using four 2-D test functions and an experimental CFD case, indicating that the proposed active learning approach outperforms classical random sampling techniques. Thanks to this architecture, the development process of a new commercial UAV can be significantly streamlined by expediting the testing phase through the use of DTs modeled more efficiently.
Open Access
Towards a heat-resistant tethered micro-aerial vehicle for structure fire sensing
(MDPI, 2025-02-23) Aláez Gómez, Daniel; Prieto Míguez, Manuel; Villadangos Alonso, Jesús; Astrain Escola, José Javier; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Gobierno de Navarra / Nafarroako Gobernua
The collapse of structures during firefighter intervention is one of the greatest risks that firefighters must face when entering buildings. To reduce these risks, situational awareness is key. Although many advances have already been developed in wildland and outdoor fires, there is still room for improvement in structure fires. The development of a heat-resistant micro-aerial vehicle for indoor fires poses a series of challenges such as component cooling, battery management, and protection from impacts. In this paper, a heat-resistant tethered micro-aerial vehicle is designed, modeled through thermal analysis, and successfully tested in real-world conditions. This platform has been equipped with a micro-sized thermal sensing camera and first-person-view (FPV) camera, optimized for thermal management, to allow for situational awareness in structure fires.
Open Access
Real-time object geopositioning from monocular target detection/tracking for aerial cinematography
(IEEE, 2023-12-08) Aláez Gómez, Daniel; Mygdalis, Vasileios; Villadangos Alonso, Jesús; Pitas, Ioannis; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
In recent years, the field of automated aerial cinematography has seen a significant increase in demand for real-time 3D target geopositioning for motion and shot planning. To this end, many of the existing cinematography plans require the use of complex sensors that need to be equipped on the subject or rely on external motion systems. This work addresses this problem by combining monocular visual target detection and tracking with a simple ground intersection model. Under the assumption that the targets to be filmed typically stand on the ground, 3D target localization is achieved by estimating the direction and the norm of the look-at vector. The proposed algorithm employs an error estimation model that accounts for the error in detecting the bounding box, the height estimation errors, and the uncertainties of the pitch and yaw angles. This algorithm has been fully implemented in a heavy-lifting aerial cinematography hexacopter, and its performance has been evaluated through experimental flights. Results show that typical errors are within 5 meters of absolute distance and 3 degrees of angular error for distances to the target of around 100 meters.
Open Access
HIL flight simulator for VTOL-UAV pilot training using X-plane
(MDPI, 2022) Aláez Gómez, Daniel; Olaz Moratinos, Xabier; Prieto Míguez, Manuel; Porcellinis Pascau, Pablo de; Villadangos Alonso, Jesús; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC
With the increasing popularity of vertical take-off and landing unmanned aerial vehicles (VTOL UAVs), a new problem arises: pilot training. Most conventional pilot training simulators are designed for full-scale aircrafts, while most UAV simulators are just focused on conceptual testing and design validation. The X-Plane flight simulator was extended to include new functionalities such as complex wind dynamics, ground effect, and accurate real-time weather. A commercial HIL flight controller was coupled with a VTOL convertiplane UAV model to provide realistic flight control. A real flight case scenario was tested in simulation to show the importance of including an accurate wind model. The result is a complete simulation environment that has been successfully deployed for pilot training of the Marvin aircraft manufactured by FuVeX.
Open Access
Quadcopter neural controller for take-off and landing in windy environments
(Elsevier, 2023-09-01) Olaz Moratinos, Xabier; Aláez Gómez, Daniel; Prieto Míguez, Manuel; Villadangos Alonso, Jesús; Astrain Escola, José Javier; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC
This paper proposes the design of a quadcopter neural controller based on Reinforcement Learning (RL) for controlling the complete maneuvers of landing and take-off, even in variable windy conditions. To facilitate RL training, a wind model is designed, and two RL algorithms, Deep Deterministic Policy Gradient (DDPG) and Proximal Policy Optimization (PPO), are adapted and compared. The first phases of the learning process consider extended exploration states as a warm-up, and a novel neural network controller architecture is proposed with the addition of an adaptation layer. The neural network’s output is defined as the forces and momentum desired for the UAV, and the adaptation layer transforms forces and momentum into motor velocities. By decoupling attitude from motor velocities, the adaptation layer enhances a more straightforward interpretation of the neural network output and helps refine the rewards. The successful neural controller training has been tested up to 36 km/h wind speed.