Design and Validation of a Dynamic Parameter Identification Model for Industrial Manipulator Robots - Urrea-Onate, E; Pascal-Mamani, J (Springer Science and Business Media Deutschland GmbH, 2021)
This article presents the design and validation of a regression model for the identification of dynamic parameters in manipulator robots. The model exhibits implementation advantages as it is based on the acquisition of position, speed and voltage data from the actuator in each joint rather than on the calculation of acceleration and torque. Actuators can be direct current and/or servomotor type. The regression model developed is simulated using MATLAB/Simulink software to identify the parameters of 2-DoF (Degrees of Freedom) and 5-DoF manipulator robots. Additionally, the model is experimentally validated on a real 5-DoF redundant manipulator robot. The identification model has great advantages in terms of implementation. © 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature.