AUTOMAÇÃO ROBÓTICA: SOLUÇÕES SUSTENTÁVEIS E INCLUSIVAS: UNIFEOB

Abstract

In the Robotics module of the Computer Science course, the proposal for the Extension is sustainable and inclusive solutions through the use of robotic automation. In this project, we use the sustainable goal (SDG) – from the UN – of Industry, innovation and infrastructure (SDG 9). The objective is to create a “lumberjack” robot, responsible for collecting wood that ideally in addition to collection, it will separate the material in designated spaces, so autonomous, reducing the impact of harmful practices and increasing the efficiency of this type of transport. The designed robot is on a reduced scale of what would be used to actually perform this task, thus being a prototype for academic purposes.The project will use diverse knowledge from the study units covered in module. They are: Robotics, under the responsibility of Prof. Marcelo Ciacco de Almeida, introducing us to robotics knowledge for assembling the robot, identifying movements, classification and possible calculations; Machine Learning, under the responsibility of Prof. Rodrigo Marudi de Oliveira, introducing us to the development of learning machine that controls the robot, and bridging the Differential and Integral Calculus unit, of responsibility of the Prof. Carlos Alberto Collozzo de Souza; and Linear Algebra and Geometry Analytics, also the responsibility of Prof. Carlos Alberto Collozzo de Souza, who introduces algebraic notions related to the general movement of the robot, such as drivability and the movement of the robotic arm. Through this project, we developed an autonomous machine prototype, equipped with computer vision and robotic arms, capable of identifying, locating and collecting different types of raw materials in complex industrial environments. This innovative solution promises significantly increase the efficiency of production processes, reduce operating costs and ensure greater safety for workers by automating repetitive and potentially dangerous

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Machine Learning, Robótica, Álgebra Linear, Cálculo Diferencial, Inteligencia Artificial, ESP32

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