Classification System Design using Redundant Robot and Artificial Vision (Diseño de Sistema de Clasificación usando Robot Redundante y Visión Artificial)
The following Project was presented as part of my university thesis to graduate as a Mechatronics Engineer from UNITEC-Tegucigalpa, Honduras (2021).
The focus of this project is to use the tools available today to develop much more complex robotic systems that allow it to further facilitate meeting the needs of humans. The main objective of this project is to program and control a Redundant Robot with 7 degrees of freedom and simulate it in an industrial context with conveyor belts, proximity sensors and an RGB camera that allows the robot to detect products with errors, by means of algorithms. implemented in Artificial Vision systems.
The main objective of the project was to develop the design of a classification system by means of a redundant robot with 7 degrees of freedom and artificial vision for the detection of products with errors or unwanted characteristics.
To achieve the control and programming of the redundant robot, a robotics simulator known as CoppeliaSim (V-REP) from the company Coppelia Robotics has been used, a simulator that allows creating, composing and simulating almost any type of robot with very precise physics engines.
The same simulator provides the facility to program the robot with a programming language known as Python, Python is a very complete and flexible language that has allowed to implement very useful functions for the control of the robotic system, and also the inclusion of libraries such as OpenCV that they facilitate the intervention to the classification system by means of a vision sensor and artificial vision.