Diseño y Fabricacion de un brazo robotico de 3 ejes.
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Date
2025-04
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Universidad Nacional de Trujillo
Abstract
El presente trabajo aborda el diseño y fabricación de un brazo robótico, centrándose en el análisis cinemático y la optimización de su rendimiento. Se implementan modelos matemáticos de cinemática directa e inversa utilizando la notación Denavit-Hartenberg (DH) y métodos numéricos basados en la matriz Jacobiana. Para validar la precisión y repetitividad del sistema, se realizan simulaciones en MATLAB, permitiendo la optimización de trayectorias y el control del movimiento.
Se seleccionan materiales avanzados y se integran actuadores eléctricos (BUS servomotores) y sensores para mejorar la estabilidad y adaptabilidad del robot. Se utilizan estrategias de microcontrolador ESP32 y aprendizaje automático para optimizar el consumo energético y la eficiencia operativa.
Los resultados muestran una mejora significativa en la precisión, estabilidad y eficiencia energética, validando la viabilidad del diseño propuesto. Se concluye que la combinación de modelado cinemático, simulaciones avanzadas y control inteligente es fundamental para el desarrollo de brazos robóticos en aplicaciones industriales y médicas.
Palabras clave: Brazo robótico, cinemática directa, cinemática inversa, Denavit-Hartenberg, control PID, aprendizaje automático, ROS, MATLAB, simulación, eficiencia energética.
This work addresses the design and manufacturing of a robotic arm, focusing on kinematic analysis and optimization of its performance. Mathematical models of forward and inverse kinematics are implemented using the Denavit-Hartenberg (DH) notation and numerical methods based on the Jacobian matrix. To validate the accuracy and repeatability of the system, simulations are performed in MATLAB, allowing trajectory optimization and motion control. Advanced materials are selected and electric actuators (BUS SERVOMOTORS) and sensors are integrated to improve the stability and adaptability of the robot. ESP32 microcontroller and machine learning strategies are used to optimize energy consumption and operational efficiency. The results show a significant improvement in accuracy, stability and energy efficiency, validating the feasibility of the proposed design. It is concluded that the combination of kinematic modeling, advanced simulations and intelligent control is essential for the development of robotic arms in industrial and medical applications.
This work addresses the design and manufacturing of a robotic arm, focusing on kinematic analysis and optimization of its performance. Mathematical models of forward and inverse kinematics are implemented using the Denavit-Hartenberg (DH) notation and numerical methods based on the Jacobian matrix. To validate the accuracy and repeatability of the system, simulations are performed in MATLAB, allowing trajectory optimization and motion control. Advanced materials are selected and electric actuators (BUS SERVOMOTORS) and sensors are integrated to improve the stability and adaptability of the robot. ESP32 microcontroller and machine learning strategies are used to optimize energy consumption and operational efficiency. The results show a significant improvement in accuracy, stability and energy efficiency, validating the feasibility of the proposed design. It is concluded that the combination of kinematic modeling, advanced simulations and intelligent control is essential for the development of robotic arms in industrial and medical applications.
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TECHNOLOGY::Engineering mechanics