Comportamento coletivo e bioinspirado para sistemas multirrobô

• Ano de defesa: 2021
• Autor(a) principal: Rohrich, Ronnier Frates
• 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: Robôs industriais; Gás - Medidas de segurança; Robôs - Sistemas de controle; Sensores; Robótica; Sistemas Ciber-Físicos; Olfato - Automação; Robots, Industrial; Gas - Security measures; Robots - Control systems; Sensors; Robotics; Cyber-physical system; Smell - Automation; CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA::ELETRONICA INDUSTRIAL, SISTEMAS E CONTROLES ELETRONICOS::AUTOMACAO ELETRONICA DE PROCESSOS ELETRICOS E INDUSTRIAIS; Engenharia Elétrica
• Link de acesso: http://repositorio.utfpr.edu.br/jspui/handle/1/26357

This work discusses a new collective mapping approach using autonomous mobile robots specially designed to monitor different gas concentration levels. In addition to carrying out a comprehensive mapping of internal environments, approaches involving searching for the gas source and delimitation of safe routes are also presented. Thus, aspects of collectivity in multirobot systems are widely explored, such as information sharing and efficient scalability levels. The group acts as a composite sensor that can move independently to look for an optimal detection zone. Behaviors attributed to the multi-robot system, such as the continuous autonomous search for energy sources for survival, collective decision-making, and knowledge transfer, are bioinspired by cognitive mechanisms observed in bacterial colonies. In this way, individual and collective approaches with variations in robot numbers are widely explored. The method is evaluated in a simulated environment and in a cyber-physical system specially designed to safely experiment with gases and mobile robots while reproducing the realistic dynamic behavior of the gas. Experiments are carried out to clarify the collective contributions of gas mapping, and the gas survey is compared using various mobile robots with and without collective detection. The proposed approach is evaluated in an unhealthy environment to elucidate its effectiveness. In addition to presenting the related differences between collective and individual sensory approaches, this work contributes to scalability analyzes in multi-robot systems for gas detection. Another contribution is evidenced through a simulated cyber-physical experimental system to test the performance of algorithms before applying them to practice. Furthermore, the collective approach using a multi-robot system equipped with gas sensors provides the delimitation of different gaseous regions, assigning them different tasks according to the momentary need. The collective approach seeks to optimize routes to the gas source, offering safer alternatives for accessing the environment.