The rapid expansion of Advanced Air Mobility (AAM) and Urban Air Mobility (UAM) poses significant challenges for the integration of Unmanned Aircraft Systems (UAS) into dense urban environments, where safety risks and population exposure are particularly high. This study proposes and applies a methodology based on probabilistic assessment of both ground and air risk, grounded in the principles of safety management and the use of geospatial data from OpenStreetMap (OSM), official aeronautical charts, and digital urban models. The urban area is discretized into a spatial grid on which independent risks are calculated per cell and later combined through a cumulative probabilistic fusion model. The resulting risk estimates enable the construction of cost matrices compatible with path-search algorithms. The methodology is applied to a case study in Medellín, Colombia, connecting the Oviedo and San Diego shopping centers through Beyond Visual Line of Sight (BVLOS) operations of a DJI FlyCart 30 drone. Results show that planning with the A* algorithm produces safe routes that minimize exposure to critical areas such as hospitals and restricted air corridors, while maintaining operational efficiency metrics. This approach demonstrates a practical bridge between regulatory theory and operational practice in UAM corridor design, offering a replicable solution for risk management in urban scenarios.

This research aims to present an analysis of the behavior of multiple Remotely Piloted Aircraft Systems (multi-RPAS) flying in formation, a key aspect of advanced aerial mobility in the aerospace industry. This involves the positioning and relative distance in three dimensions (3D) of two RPAS, taking into account their operational requirements and limitations, recognizing the operating states, and addressing potential situations encountered during formation flight. For this study, the “Conformance and Fault Injection—CoFI” methodology is employed. This methodology guides the user towards a comprehensive understanding of the system and enables the creation of a set of finite state machines representing the system’s behavior under study. Consequently, models and requirements for the behavior of multi-RPAS flying in formation are presented. By applying the CoFI methodology to inject faults into the operation and predict behavior in anomalous situations, both normal and abnormal behavior models, as well as the flight behavior requirements of the multi-RPAS formation, are outlined. This analysis is expected to facilitate the identification of formation flight behavior in multi-RPAS, thereby reducing associated operational risks.

Un banco de pruebas para cohetería es una plataforma estructural que tiene como propósito realizar ensayos mediante instrumentos de medición, permitiendo la comprobación, análisis, comportamiento y resultados del elemento a estudiar (Cohete). Existen ciertos componentes del banco de pruebas para cohete como lo son los sensores, dispositivos electrónicos, tableros, relojes, deflector de llama, que permiten el funcionamiento y acceso a los conocimientos ingenieriles en sistemas de propulsión. Entidades gubernamentales, privadas y universidades trabajan en la realización de bancos de pruebas de bajo costo, que permitan aportar en la investigación e industria con grandes desarrollos, y así generar un amplio interés en los estudiantes e investigadores del país. El diseño conceptual a describir, da a conocer las técnicas que se utilizaron como lo son el despliegue de función de calidad, metodología utilizada y análisis funcional, la cual ayudó a evaluar los diferentes conceptos generados durante la investigación, donde finalmente se escogió el diseño dominante.

In recent years, there has been a notable increase in the adoption of artificial intelligence, particularly due to the growing implementation of Industry 4.0 and the massive generation of data across various industrial sectors. The aviation industry has not lagged behind in this technological advancement, and multiple studies have been conducted to explore the applications of artificial intelligence in this field. The objective of this study is to carry out a comprehensive and up-to-date analysis of the current state of artificial intelligence utilization in aviation operations, with a special focus on flight planning processes, trajectory prediction, and resource optimization. Through this analysis, the aim is to delve into the latest research and advancements in this field, identifying the main methodologies, algorithms, and techniques employed. Furthermore, the study seeks to provide an integrated view of the diverse applications of artificial intelligence in the aviation industry, highlighting its potential to enhance operational efficiency, safety, and decision-making. Additionally, it aims to identify the most relevant areas for future research and development, with the goal of contributing to progress and innovation in this promising field.

This paper presents the design, optimization, and performance evaluation of a Satellite-Based Augmentation System (SBAS) ground segment tailored to Colombia’s air navigation infrastructure, with emphasis on ionospheric anomalies in equatorial latitudes. The configuration comprises six Reference Stations (RIMS), strategically sited via geometric dilution of precision (GDOP) minimization and airspace demand models from ADS-B data. A simulation suite—integrating STK^®, Radio Mobile™, and Stanford-ESA certified monitors—quantifies service volume, link margins, and protection level compliance. Ionospheric threat characterization uses regional scintillation datasets (σln ≈ 0.36, ROTI₉₅ ≈ 85 mm/km), informing GIVE inflation and dual-frequency pseudorange integrity validation. Simulations confirm the system sustains ≥ 99.8% APV-I availability over the CAR/SAM FIR, with Horizontal and Vertical Protection Levels (HPL/VPL) bounded below 28 m and 46 m. Uplink integrity and GEO broadcast continuity are modelled under worst-case masking and multipath, confirming ICAO Annex 10 SARPs compliance. The architecture achieves a high performance-to-cost ratio, enabling nationwide SBAS coverage with a 65% cost reduction versus legacy navaids. The system is forward-compatible with dual-frequency multi-constellation SBAS (DFMC), supporting future APV-II scalability. These results position Colombia as a regional node for GNSS augmentation, fostering safety, efficiency, and procedural harmonization.

Flapping-wing micro air vehicles (FWMAVs) have gained increasing attention due to their manoeuvrability, low acoustic signature, and suitability for confined or cluttered environments. Despite considerable progress, existing reviews treat actuation mechanisms and mechanical transmissions in isolation, leaving a gap in the comparative assessment of pulley-based and alternative flapping systems. This study provides a comprehensive and quantitative synthesis of the literature on FWMAV mechanical architectures, with particular emphasis on pulley-driven transmissions used in platforms such as the Nano Hummingbird and the Robotic Hummingbird. A structured review methodology was applied, incorporating a systematic database search, extraction of performance parameters, and cross-platform comparison of flapping frequency, lift generation, power consumption, lift-to-weight ratio, and material choices. The analysis identifies consistent scaling trends across motor-driven, piezoelectric, and hybrid actuation families and highlights the efficiency and stroke-amplification advantages of pulley-based mechanisms for centimetre-scale hovering MAVs. The review also identifies unresolved challenges, including durability of transmission materials, standardisation of performance metrics, and the need for high-fidelity aerodynamic characterisation. Overall, this work offers an integrated framework for understanding the trade-offs among actuation and transmission strategies and provides a roadmap to guide future research and the practical development of next-generation FWMAVs.