Providing resilience to UAV swarms following planned missions

As we experience an unprecedented growth in the field of Unmanned Aerial Vehicles (UAVs), more and more applications keep arising due to the combination of low cost and flexibility provided by these flying devices, especially those of the multirrotor type. Within this field, solutions where several UAVs team-up to create a swarm are gaining momentum as they enable to perform more sophisticated tasks, or accelerate task execution compared to the single-UAV alternative. However, advanced solutions based on UAV swarms still lack significant advancements and validation in real environments to facilitate their adoption and deployment. In this paper we take a step ahead in this direction by proposing a solution that improves the resilience of swarm flights, focusing on handling the loss of the swarm leader, which is typically the most critical condition to be faced. Experiments using our UAV emulation tool (ArduSim) evidence the correctness of the protocol under adverse circumstances, and highlight that swarm members are able to seamlessly switch to an alternative leader when necessary, introducing a negligible delay in the process in most cases, while keeping this delay within a few seconds even in worst-case conditions

Vuelo seguro de enjambres de drones mediante integración de datos topográficos

[ES] Las actuales herramientas de planificación de vuelos para drones no tienen en cuenta los datos de relieve del terreno, lo cual puede derivar en colisiones o en sobrepasar la altura máxima legal del vuelo. En este contexto, este proyecto tiene como objetivo la integración de datos topográficos en una herramienta de simulación de vuelos de drones. Se trata en concreto del simulador/ controlador ArduSim, el cual permite gestionar las comunicaciones entre drones y la creación de enjambres, aunque carece de datos topográficos reales, ofreciendo solo información de mapa que importa de la plataforma Bing. Se realiza la implementación de un protocolo de vuelo integrado en el simulador, el cual, utilizando datos topográficos de un Modelo Digital de Elevación (MDE), obtiene, gracias a la geolocalización del dron, su altura respecto al suelo en tiempo real, teniendo en cuenta tanto elevaciones del terreno como edificios y vegetación. Además, la implementación es suficientemente flexible como para adaptarse a MDEs con diferentes resoluciones. En base al trabajo realizado, la herramienta ArduSim es ahora capaz de funcionar tanto en vuelos simulados como en vuelos reales, incluyendo vuelos en enjambre, siendo capaz de detectar obstáculos con anticipación y actuar en consecuencia, dotando al dron de conciencia situacional de su entorno.[EN] Current drone flight planning tools do not take terrain relief data into account, which can lead to collisions or exceeding the legal maximum flight height. In this context, this project aims to integrate topographic data into a drone flight simulation tool. It is specifically the ArduSim simulator / controller, which allows managing communications between drones and the creation of swarms, although it lacks real topographic data, offering only map information that is imported from the Bing platform. The implementation of a flight protocol integrated into the simulator is carried out, which, using topographic data from a Digital Elevation Model (DEM), obtains, thanks to the geolocation of the drone, its height with respect to the ground in real time, taking into account counts both terrain elevations and buildings and vegetation. Furthermore, the implementation is flexible enough to accommodate DEMs with different resolutions. Based on the work done, the ArduSim tool is now capable of working both in simulated flights and in real flights, including swarm flights, being able to detect obstacles in advance and act accordingly, providing the drone with situational awareness of its surroundings.Morales Guerrero, C. (2021). Vuelo seguro de enjambres de drones mediante integración de datos topográficos. Universitat Politècnica de València. http://hdl.handle.net/10251/173211TFG

Motion Planning of UAV Swarm: Recent Challenges and Approaches

The unmanned aerial vehicle (UAV) swarm is gaining massive interest for researchers as it has huge significance over a single UAV. Many studies focus only on a few challenges of this complex multidisciplinary group. Most of them have certain limitations. This paper aims to recognize and arrange relevant research for evaluating motion planning techniques and models for a swarm from the viewpoint of control, path planning, architecture, communication, monitoring and tracking, and safety issues. Then, a state-of-the-art understanding of the UAV swarm and an overview of swarm intelligence (SI) are provided in this research. Multiple challenges are considered, and some approaches are presented. Findings show that swarm intelligence is leading in this era and is the most significant approach for UAV swarm that offers distinct contributions in different environments. This integration of studies will serve as a basis for knowledge concerning swarm, create guidelines for motion planning issues, and strengthens support for existing methods. Moreover, this paper possesses the capacity to engender new strategies that can serve as the grounds for future work