Análise e geração de caminho mínimo aplicado à navegação de veículos terrestres

• Ano de defesa: 2017
• Autor(a) principal: Paiva, Leonardo Silveira
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Lavras; Programa de Pós-Graduação em Engenharia Agrícola; UFLA; brasil; Departamento de Engenharia
• Palavras-chave em Português: Robótica; Veículos terrestres - Otimização; Robôs móveis; Robotics; Land Vehicles - Optimization; Mobile robots; Engenharia Agrícola
• Link de acesso: http://repositorio.ufla.br/jspui/handle/1/12838

The objective of this work was to develop a set of routines that are capable of generating a sub-optimal path for a set of mobile platforms, taking into account the smaller distance between two previously established points, and respecting a set of constraints imposed over the environment, as well as the kinematic constraints of each platform. The study applied to set of optimization algorithms that in an offline way received the map of a static environment, and from the treatment of this image returned the smallest path between two points. The trajectory then traveled by the mobile robot was the one that presented the shortest distance and that satisfied all the restrictions imposed throughout the environment. In conjunction with the optimization techniques, a state estimator, characterized as the Kalman Filter, was used to analyze and control the trajectory along a set of routes previously established by the planner. For control of the system, a Proportional, Integral and Derivative controller was implemented in order to minimize the error generated when the mobile platform moved away from the optimum path. As a computational package formed by a set of optimization algorithms, a didactic module was developed, once the user has access to all the functionalities of this work through a graphical interface of easy manipulation. This interface served as a facilitator of teaching and learning in the area of mobile robotics. The technique explored made use of a large set of optimization algorithms to be able to find an executable path, as well as to develop a set of mobile robots with different architectures to validate the proposed methodology that should be applicable to a wide variety of problems of nonlinear control in agriculture.