A quadral-Fuzzy control approach to flight formation by a fleet of unmanned aerial vehicles

• Autor(a) principal: Simões Teixeira, Marco António
• Data de Publicação: 2020
• Outros Autores: Neves Juniór, Flávio, Koubaa, Anis, Ramos de Arruda, Lúcia Valéria, Schneider de Oliveira, André
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.22/16137
• topic: Unmanned aerial vehicles (UAVs); Multi-agent systems; Distance-based formation; Flight-formation control; Autonomous flight

This paper addresses the control of a fleet of unmanned aerial systems (UAVs), termed as drones, for flight formation problems. Getting drones to fly in formation is a relevant problem to be solved when cooperative cargo transportation is desired. A general approach for this problem considers the coordination of a fleet of UAVs, by fusing all information coming from several individual sensors posed on each UAVs. However, this approach induces a high cost as every UAV should have its advanced perception system. As an alternative, this paper proposes the use of a single perception system by a fleet composed of several elementary drones (workers) with primitive low-cost sensors and a leader drone carrying a 3D perception source. We propose a Quadral-Fuzzy approach to ensure that all drones fly in formation and will not collide with each other or with environment obstacles. We also develop a new way to compute potential fields based on possibility fuzzy (fuzziness) measure with the focus of avoiding collisions between the drones. The proposed approach encompasses four high-coupled intelligent controllers that respectively control the leader and worker drones' motion and implement obstacle and collision avoidance procedures. Simulation results using a fleet of four aerial drones are presented, showing the potential for solving usual problems to flights in formation, such as dodging obstacles, avoiding collisions between the drones, among others.