Integrated Identification of Collaborative Robots for Robot Assisted 3D Printing Processes
Alessandro Dimauro, Davide Tebaldi, Fabio Pini, Luigi Biagiotti, Francesco Leali

TL;DR
This paper presents a comprehensive model-based identification method for collaborative robots to improve precision and control in robot-assisted 3D printing, validated through a real-world case study.
Contribution
It introduces an integrated five-step parameter identification procedure that ensures physical consistency and enhances dynamic modeling of collaborative robots in additive manufacturing.
Findings
The identified model closely matches experimental data.
The approach improves robot control and error prediction.
Validation on a real collaborative robot demonstrates effectiveness.
Abstract
In recent years, the integration of additive manufacturing (AM) and industrial robotics has opened new perspectives for the production of complex components, particularly in the automotive sector. Robot-assisted additive manufacturing processes overcome the dimensional and kinematic limitations of traditional Cartesian systems, enabling non-planar deposition and greater geometric flexibility. However, the increasing dynamic complexity of robotic manipulators introduces challenges related to precision, control, and error prediction. This work proposes a model-based approach equipped with an integrated identification procedure of the system's parameters, including the robot, the actuators and the controllers. We show that the integrated modeling procedure allows to obtain a reliable dynamic model even in the presence of sensory and programming limitations typical of collaborative robots.…
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