This research focuses on a novel convertible unmanned aerial vehicle (CUAV) featuring four rotors with tilting capabilities combined with a tapered form. This paper studies the transition motion between multirotor and fixed-wing modes based on the mechanical and aerodynamics design as well as the control strategy. The proposed CUAV involves information about design, manufacturing, operation, modeling, control strategy, and real-time experiments. The CUAV design considers a fixed-wing with tiltrotors and provides the maneuverability to perform take-off, hover flight, cruise flight, and landing, having the characteristics of a helicopter in hover flight and an aircraft in horizontal flight. The manufacturing is based on additive manufacturing, which facilitates the creation of a lattice structure within the wing. The modeling is obtained using the Newton–Euler equations, and the control strategy is a PID controller based on a geometric approach on SE(3). Finally, the real-time experiments validate the proposed design for the complete regime of flight, and the research meticulously evaluates the feasibility of the prototype and its potential to significantly enhance the mission versatility.

This research work addresses the problem of path planning for unmanned aerial vehicles (UAVs) in complex environments such as a maze. A genetic algorithm (GA) with variable chromosomes and gene change conditions is designed when the decision point criteria and a collision with a wall are presented; without considering large chromosomes. Our proposed GA obtains the sequence of minimum movements required to solve the maze. Then, the trajectories are generated by high-order polynomials. Finally, numerical simulations and real-time tests are carried out to validate the proposed algorithm.

This work presents a teaching approach for postgraduate aeronautic engineering students, fo-cusing on the analysis and understanding of structural dynamics in complex, real-world applications rather than simplified models. Using a commercial quadrotor as a case study, students investigate critical issues affecting lateral stability—specifically, abnormal vibrations and unintended sliding during autonomous self-leveling. These stability challenges prompt students to explore whether the issues stem from control limitations or structural deficiencies. Students employ the frequency response function (FRF) through impact hammer testing to characterize the natural frequencies of the quadrotor's arms and propellers, identifying potential resonances caused by the propulsion system. The experimental analysis offers students insights into structural solutions and control system reprogramming to counteract resonance-induced vibrations, improve stability, and enhance autonomous functionality. This hands-on approach allows students to directly apply concepts of structural dynamics to complex aerospace systems, preparing them for advanced prob-lem-solving in real-world engineering environments.

In this work, the structural dynamics of a commercial quadrotor was investigated, which presents problems of lateral stability or sliding instead of remaining self-leveling through its autonomous control system. The possible existence of vibrations motivated the characterization of the frequency response of the arms and propellers by means of the frequency response function (FRF) using the impact hammer technique. The experimental results provided sufficient information for the future implementation of structural solutions or through reprogramming in the autonomous control algorithm that compensates or mitigates the negative effect of vibration levels due to resonance phenomenon and improves the stability in self-leveling condition of the quadrotor.

En esta investigación se presenta el desarrollo e implementación de un algoritmo evolutivo con la capacidad de generar configuraciones óptimas de alas volantes. Este enfoque está basado en el concepto de algoritmos evolutivos, los cuales cuentan con la capacidad de generar soluciones candidatas, evaluar su efectividad, y converger hacia una solución optimizada. En el funcionamiento interno del algoritmo se definen funciones objetivo las cuales evalúan la calidad de la solución, en este caso, se consideran parámetros aerodinámicos como la eficiencia y la distribución de carga; además de las características de estabilidad estática de las alas candidatas. Lo anterior, buscando converger en una solución con distribución de carga aerodinámica de tipo campana, y parámetros de estabilidad estática en rangos estables. Para la validación del algoritmo se realiza un análisis comparativo utilizando como referencia el ala de una aeronave de aviación general, y una solución óptima generada con el algoritmo. Como resultado de esta comparación se demuestra la efectividad de la propuesta por medio de la mejora en los parámetros de referencia en comparación con la aeronave original.