Enhancing Parameter Identification in Robot Manipulators: Experimental Validation

Abstract

Dynamic modeling of manipulators carrying payloads with unspecified physical parameters is crucial for optimal path planning, mitigating fatigue in robots, and ensuring collision avoidance in real-world industrial applications. This important issue is addressed in the present study by introducing a novel form of mathematical equations that are linear in terms of system parameters, leading to more accurate and robust parameter identification. The proposed method is applied to identify the UR5e manipulator based on experimental tests, while the moments of inertia of the motors are taken into account in mathematical modeling. The presented results demonstrate excellent agreement between the model and experimental outputs. This method has the potential to be applied to any manipulator, as well as many other nonlinear systems, with significant implications for various industrial applications.