Carvajal, Christian
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Carvajal, Christian
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Ambato

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Digital Twin Integration for Active Learning in Robotic Manipulator Control Within Engineering 4.0

2025 , Fernando J. Pantusin , Jessica S. Ortiz , Carvajal, Christian , Víctor H. Andaluz , Lenin G. Yar , Flavio Roberti , Daniel Gandolfo

Robotic systems play an increasingly significant role in both education and industry; however, access to physical robots remains a challenge due to high costs and operational risks. This work presents a training platform based on Digital Twins, aimed at active learning in the control of robotic manipulators, with a focus on the UFACTORY 850 arm. The proposed approach integrates mathematical modeling, interactive simulation, and experimental validation, enabling the implementation and testing of control strategies in three virtual scenarios that replicate real-world conditions: a laboratory, a service environment, and an industrial production line. The system relies on kinematic and dynamic models of the manipulator, using maneuverability velocities as input signals, and employs ROS as middleware to link the Unity 2022.2.14 graphics engine with the control algorithms developed in MATLAB R2022a. Experimental results demonstrate the accuracy of the implemented models and the effectiveness of the control algorithms, validating the usefulness of Digital Twins as a pedagogical tool to support safe, accessible, and innovative learning in robotic engineering.

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Virtual Teleoperation System for Mobile Manipulator Robots Focused on Object Transport and Manipulation

2024 , Fernando J. Pantusin , Carvajal, Christian , Jessica S. Ortiz , Víctor H. Andaluz

This work describes the development of a tool for the teleoperation of robots. The tool is developed in a virtual environment using the Unity graphics engine. For the development of the application, a kinematic model and a dynamic model of a mobile manipulator are used. The mobile manipulator robot consists of an omnidirectional platform and an anthropomorphic robotic arm with 4 degrees of freedom (4DOF). The model is essential to emulate the movements of the robot and to facilitate the immersion in the virtual environment. In addition, the control algorithms are established and developed in MATLAB 2020 software, which improves the acquisition of knowledge to teleoperate robots and execute tasks of manipulation and transport of objects. This methodology offers a cheaper and safer alternative to real physical systems, as it reduces both the costs and risks associated with using a real robot for training.

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