Dynamic Resource Allocation for Efficient Sharing of Services from Heterogeneous Autonomous Vehicles

A novel dynamic resource allocation model is introduced for efficient sharing of services provided by ad hoc assemblies of heterogeneous autonomous vehicles. A key contribution is the provision of capability to dynamically select sensors and platforms within constraints imposed by time dependencies, refueling, and transportation services. The problem is modeled as a connected network of nodes and formulated as an integer linear program. Solution fitness is prioritized over computation time. Simulation results of an illustrative scenario are used to demonstrate the ability of the model to plan for sensor selection, refueling, collaboration, and cooperation between heterogeneous resources. Prioritization of operational cost leads to missions that use cheaper resources but take longer to complete. Prioritization of completion time leads to shorter missions at the expense of increased overall resource cost. Missions can be successfully replanned through dynamic reallocation of new requests during a mission. Monte Carlo studies on systems of increasing complexity show that good solutions can be obtained using low time resolutions, with small time windows at a relatively low computational cost. In comparison with other approaches, the developed integer linear program model provides best solutions at the expense of longer computation time

Planificación de una flota homogénea de drones para cobertura audiovisual de prueba deportiva

Una de las aplicaciones más extendidas en el uso de UAVs (unmanned aerial vehicles) es el seguimiento de objetivos, ya que aquellos permiten tomar imágenes desde posiciones remotas o inalcanzables mediante otros métodos. En este proyecto, se desarrolla una aplicación parametrizable de seguimiento automatizado con un sistema de UAVs a un conjunto de objetivos que poseen una trayectoria estimada definida por una serie de puntos y tiempos con incertidumbre. Esta aplicación, mediante el uso de una heurística de asignación secuencial, proporciona dos resultados: una asignación rápida e individualizada de cada UAV a una parte definida de la ruta de cada objetivo y una primera identificación del cruce de trayectorias planificadas como potencial dificultad en llevar a la realidad los planes.One of the most widespread applications in UAVs (unmanned aerial vehicles) usage is objectives tracking, due to their capability of taking images from remote or unreachable positions through other methods. This project develops a UAV system customizable and automated objective tracking application. The objectives’ trajectories are defined by sets of points and timings with uncertainty. This application, through the usage of a sequential task assignment heuristic, provides two results: a fast and individualized assignment of each UAV to a specific part of each objective’s route and a first identification of the planned trajectories crossings as a potential difficulty when it comes to real execution.Universidad de Sevilla. Máster en Organización Industrial y Gestión de Empresa