The present paper describes an algorithm for the identification of the dynamic parameters of an industrial robot. This approach is based on the possibility to write robot dynamics in a linear form with respect to a specific set of dynamic parameters. To properly detect them, the coefficients of a 5th order Fast Fourier Series (FFS) trajectory have been optimized using a genetic algorithm. Such identification trajectory has been then commanded to a UR5 collaborative robot from Universal Robots and experimental joints torques have been recorded at a frequency of 125 Hz. Base dynamic parameters were identified using least square errors optimization reaching low standard deviations. The algorithm has been validated with a second persistent trajectory with good results. Temperature effects on friction coefficients have been analyzed by running two identification processes: one just after the first power-up of the robot and the other one after a half an hour warm-up.

Identification of a UR5 collaborative robot dynamic parameters / Raviola, A.; De Martin, A.; Guida, R.; Pastorelli, S.; Mauro, S.; Sorli, M.. - 102:(2021), pp. 69-77. ((Intervento presentato al convegno RAAD 2021: The 30th International Conference on Robotics in Alpe-Adria-Danube Region [10.1007/978-3-030-75259-0_8].

Identification of a UR5 collaborative robot dynamic parameters

Raviola A.;De Martin A.;Guida R.;Pastorelli S.;Mauro S.;Sorli M.
2021

Abstract

The present paper describes an algorithm for the identification of the dynamic parameters of an industrial robot. This approach is based on the possibility to write robot dynamics in a linear form with respect to a specific set of dynamic parameters. To properly detect them, the coefficients of a 5th order Fast Fourier Series (FFS) trajectory have been optimized using a genetic algorithm. Such identification trajectory has been then commanded to a UR5 collaborative robot from Universal Robots and experimental joints torques have been recorded at a frequency of 125 Hz. Base dynamic parameters were identified using least square errors optimization reaching low standard deviations. The algorithm has been validated with a second persistent trajectory with good results. Temperature effects on friction coefficients have been analyzed by running two identification processes: one just after the first power-up of the robot and the other one after a half an hour warm-up.
978-3-030-75258-3
978-3-030-75259-0
File in questo prodotto:
File Dimensione Formato  
Identification of a UR5 Collaborative Robot Dynamic Parameters.pdf

embargo fino al 04/05/2022

Tipologia: 2. Post-print / Author's Accepted Manuscript
Licenza: PUBBLICO - Tutti i diritti riservati
Dimensione 1.09 MB
Formato Adobe PDF
1.09 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11583/2901812