CBL - Campus del Baix Llobregat

Projecte llegit

Títol: Sistema anticolisión cooperativo 3D entre tráficos UAVs

Estudiants que han llegit aquest projecte:

Director/a: VALERO GARCÍA, MIGUEL

Departament: DAC

Títol: Sistema anticolisión cooperativo 3D entre tráficos UAVs

Data inici oferta: 13-07-2023     Data finalització oferta: 13-03-2024


Estudis d'assignació del projecte:
    GR ENG SIS TELECOMUN
    GR ENG SIST AEROESP
    GR ENG TELEMÀTICA
Tipus: Individual
 
Lloc de realització: EETAC
 
Paraules clau:
Anticolisión, UAVs, Algoritmos, Planificación de rutas, Cooperativo, Comunicación, Software, 3D, DEE
 
Descripció del contingut i pla d'activitats:
 
Overview (resum en anglès):
This document outlines the conception, development, and implementation of a system dedicated to managing conflicts among drones (UAVs). Throughout the course of this work, solutions to various problems that may arise in environments with multiple flying aircraft are presented. In response to these issues, two algorithms have been developed, along with a communication structure/protocol between agents, which combined are capable of handling a vast array of possible real-world scenarios.

The system proposes the use of dedicated software and hardware through which all drones carrying it can establish vehicle-to-vehicle communication. Through this communication, it is expected that necessary data, including flight plans, can be exchanged, enabling each involved agent to locally initiate the execution of the proposed algorithms. These algorithms will provide a conflict-free 3D solution for the flight plans of all drones in the network. For the calculation of this solution, the use of priorities has been suggested, aligning with real-life situations and providing the system with a means of discerning which of the involved drones should have more or fewer restrictions.

The first algorithm involves, given the routes to be followed by all connected agents, determining if these routes meet the requirements to be treated as high-conflict routes. If so, the drones executing them will have their routes altered based on their priority by the "Reciprocal heading obstacle" (RHO) algorithm. Once a solution has been found for this type of high-conflict route, the "Traffic Lights" algorithm is executed. This second algorithm, based on the modified routes by RHO and the defined priorities, calculates at which points the aircraft should wait in the air to yield the right of way to higher-priority traffic.

Once these algorithms provide a local solution for each drone, this solution is communicated to the rest of the swarm to determine if each one's solution is compatible with others. This way, the system gains flexibility in finding a more optimal solution. Once the most optimal solution has been communicated and accepted by all, the network members execute the solution, resulting in new routes, always respecting the original waypoints and maintaining specified minimum distances between drones.
For the development of the communication block between agents and the simulation part, this work utilizes the solution proposed by the Drone Engineering Ecosystem (DDE). It includes a study of the solutions calculated by the algorithm and the routes followed by simulated drones in various scenarios. Additionally, it features the implementation of a graphical interface, combined with simulation software, allowing the user to observe in real-time the processes of the algorithm and communications.

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