Método bioinspirado para exploração e mapeamento de ambientes internos com múltiplos VANT

• Ano de defesa: 2020
• Autor(a) principal: Rosa, Ricardo da
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Tecnológica Federal do Paraná; Curitiba; Brasil; Programa de Pós-Graduação em Engenharia Elétrica e Informática Industrial; UTFPR
• Palavras-chave em Português: Drone; Espaços topológicos lineares; Mapeamentos (Matemática) - Simulação por computador; Métodos de simulação; Drone aircraft; Linear topological spaces; Mappings (Mathematics) - Computer simulation; Simulation methods; CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::METODOLOGIA E TECNICAS DA COMPUTACAO; Engenharia Elétrica
• Link de acesso: http://repositorio.utfpr.edu.br/jspui/handle/1/5024

The use of autonomous unmanned aerial vehicles appears as an option to support various activities carried out by the human being, specially when the execution of these activities can be dangerous. An example of this is the search and rescue of victims in environments affected by catastrophes such as earthquakes or hurricanes, once there is no prior knowledge of the state of space. The exploration and mapping of the environment with multiple Unmanned Aerial Vehicles (UAV) can assist these teams in identifying the conditions of the place. The construction of maps from data provided by several autonomous UAVs requires a method for exploring the environment só that plausible results of the mapping are visible to the rescue staff within an acceptable period of time. The proposed exploration and mapping method uses a topological structure for the map representation inspired by the hexagonal structure that the bee hives present. Therefor each UAV has a behavior, in the mapping activities of new spaces, similar to that of bees in the beehive construction process. Three strategies for the allocation of hexagons to be explored were developed: First In First Out, Euclidean Distance and Relative Euclidean Distance. The Relative Euclidean Distance (DER) strategy showed satisfactory results in traffic intensity of UAVs leading to lesser total time for the exploration and the mapping of the environment. Experiments were carried out using simulation environments to validate the proposed method, varying the number of scenarios and the strategies adopted. The reduction of UAV displacements directly influences the exploration execution time. The bioinspired topological mapping proposed in this thesis presents itself as a viable option for teams of aerial robots in the activity of exploration and mapping of unknown internal environments.