AUTOMAÇÃO ROBÓTICA: SOLUÇÕES SUSTENTÁVEIS E INCLUSIVAS: UNIFEOB
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Date
2025-02-12
Journal Title
Journal ISSN
Volume Title
Publisher
Centro Universitário de Ensino Octávio Bastos
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
Description
Keywords
Machine Learning, Robótica, Álgebra Linear, Cálculo Diferencial, Inteligencia Artificial, ESP32