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Dynamic parameters identification of a UR5 robot manipulator

Gabriele Porcelli

Dynamic parameters identification of a UR5 robot manipulator.

Rel. Massimo Sorli, Andrea Raviola, Stefano Paolo Pastorelli, Stefano Mauro. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Meccanica (Mechanical Engineering), 2020

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Due to the importance to model-based control, an exact dynamic model of the manipulator is required. While the geometry structure of robot manipulators is well known, the involved dynamic parameters are not always available, since exact values are rarely provided by the robot manufacturers and often not directly measurable. Therefore, dynamic parameter identification of robot manipulators has aroused increasing interest from researchers. In this thesis project a UR5 robot manipulator from Universal Robots is used as case study for the identification scheme developing. The purpose is to provide Polytechnic University of Turin with a resource which can be used to determine dynamic parameters of robots in future works. Moreover, the complete identification of a robot is of particular interest in Prognostic and Health Management (PHM) applications. Starting from Euler-Lagrangian equations, the dynamic model of the UR5 is determined and and rewritten in linear form with respect to the dynamic parameters of the robot. However, each parameter can not be separately identified but only linear combinations of them. The procedure for determination of base parameters is explained and the base set of parameter is obtained. In order to obtain an accurate approximate solution for the parameter identification problem a specially chosen trajectory must be adopted. This trajectory must persistently excite the system. An optimality criteria is introduced to find this persistent trajectory. Then, the base set of dynamic parameter is identified using the Least Mean Square method. Another persistent trajectory is generated for validation of the obtained parameter vector. In order to check the quality of the calculated set of base parameters, predicted torques are compared with the measured ones.

Relators: Massimo Sorli, Andrea Raviola, Stefano Paolo Pastorelli, Stefano Mauro
Academic year: 2019/20
Publication type: Electronic
Number of Pages: 82
Corso di laurea: Corso di laurea magistrale in Ingegneria Meccanica (Mechanical Engineering)
Classe di laurea: New organization > Master science > LM-33 - MECHANICAL ENGINEERING
Ente in cotutela: Hochschule Regensburg (GERMANIA)
Aziende collaboratrici: UNSPECIFIED
URI: http://webthesis.biblio.polito.it/id/eprint/15519
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