Identifying Dynamic Parameters With a Novel Software Design for the M-DOF Collaborative Robot
[ 1 ] Instytut Automatyki i Robotyki, Wydział Automatyki, Robotyki i Elektrotechniki, Politechnika Poznańska | [ D ] phd student | [ P ] employee
[2.2] Automation, electronics, electrical engineering and space technologies
2022
scientific article
english
- collaborative robot
- dynamic modeling
- identification model
- rigid body
EN The primary goal of this project was to develop a general identification method via software that can be applied to collaborative robots. To achieve this, the collaborative ultralight robots Kinova Gen2 and Kuka LWR4C with seven degrees of freedom (M-DOF) were used. Specifically, the "recursive Newton-Euler'' formulation was used to provide a set of parameters that could describe the body structure and to create a general symbolic representation for collaborative robots. For parameter estimation, the least squares method was used. In addition, trajectories generated with random numbers typically do not produce consistent results; thus, verified trajectories were used. To verify trajectories, real robots were simulated with V-Rep before being executed. When untested trajectories are first tested on robots, undesirable results may occur. This method was convenient for parameter estimation and robot health; saves time; and increases the consistency of results. Algorithms were coded in MATLAB and ROS packages via Python. MATLAB, ROS, and V-Rep worked together in the Ubuntu operating system. The identification methods were modeled, implemented, tested, and validated successfully, and the results for both robots are reported in this article.
11.02.2022
24627 - 24637
CC BY-NC-ND (attribution - noncommercial - no derivatives)
open journal
final published version
at the time of publication
public
100
3,9