Algoritmo neurogenético com vistas para o planejamento de rotas de robôs móveis autônomos
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Data
2016-04-27
Autores
Bruno, Diego Renan [UNESP]
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Editor
Universidade Estadual Paulista (Unesp)
Resumo
Neste trabalho foi desenvolvido um sistema de controle híbrido bioinspirado para o planejamento de rota com vistas para a robótica móvel autônoma, baseado em redes neurais artificiais e algoritmos genéticos. O controlador tem como principal objetivo auxiliar o robô móvel em sua navegação quando aplicado em ambientes dinâmicos. Para este trabalho, o ambiente dinâmico utilizado é um “chão de fábrica” industrial, em que alguns obstáculos não são fixos e permanecem em movimentação constante. O controlador desenvolvido neste trabalho pode ser adaptado facilmente para operar em outros ambientes dinâmicos. Independentemente do ambiente utilizado, o controlador deve ser capaz de traçar uma rota possível entre o ponto inicial e o ponto de objetivo, tendo o potencial de evitar todo tipo de obstáculo que surgir nessa rota, seja um obstáculo estático ou dinâmico. O algoritmo foi implementado na linguagem C e simulado no software de modelagem e simulação de robôs V-REP (Virtual Robot Experimentation Platform). O controlador neurogenético mostrou ser eficiente para auxiliar o robô em sua navegação quando aplicado em ambientes dinâmicos.
In this work, a bioinspired hybrid control system was developed for route planning, aiming autonomous mobile robots based on artificial neural networks and genetic algorithms. The main objective of the controller is to assist the mobile robot in its navigation when applied in dynamic environments. For this work, the dynamic environment chosen was a " factory floor", in which some industrial obstacles are not fixed and remain in constant movements. The controller developed in this work can easily be adapted to operate in other dynamic environments. Regardless the environment chosen in this work, the controller must be able to map out a possible route between the starting point and the goal point with the potential to avoid all types of obstacles that appear along the routes, either a static or a dynamic one. The algorithm was implemented in C language and simulated on a robots modeling and simulation software called V-REP (Virtual Robot Experimentation Platform). The neurogenetic controller was efficient to assist the mobile robot in its navigation when applied in dynamic environments.
In this work, a bioinspired hybrid control system was developed for route planning, aiming autonomous mobile robots based on artificial neural networks and genetic algorithms. The main objective of the controller is to assist the mobile robot in its navigation when applied in dynamic environments. For this work, the dynamic environment chosen was a " factory floor", in which some industrial obstacles are not fixed and remain in constant movements. The controller developed in this work can easily be adapted to operate in other dynamic environments. Regardless the environment chosen in this work, the controller must be able to map out a possible route between the starting point and the goal point with the potential to avoid all types of obstacles that appear along the routes, either a static or a dynamic one. The algorithm was implemented in C language and simulated on a robots modeling and simulation software called V-REP (Virtual Robot Experimentation Platform). The neurogenetic controller was efficient to assist the mobile robot in its navigation when applied in dynamic environments.
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Palavras-chave
Redes neurais artificiais, Algoritmos genéticos, Robôs móveis, Planejamento de rotas, Artificial neural networks, Genetic algorithm, Mobile robots, Route planning