Accuracy Improvement of Robot-Based Milling Using an Enhanced Manipulator Model

Alexandr Klimchik (1, 2) , Yier Wu (1, 2) , Stéphane Caro (2) , Benoît Furet (3) , Anatol Pashkevich (1, 2)

1 Mines Nantes - Mines Nantes
2 IRCCyN - Institut de Recherche en Communications et en Cybernétique de Nantes
3 Modélisation et Optimisation de Process de Production (MO2P)

The paper is devoted to the accuracy improvement of robot-based milling by using an enhanced manipulator model that takes into account both geometric and elastostatic factors. Particular attention is paid to the model parameters identification accuracy. In contrast to other works, the proposed approach takes into account impact of the gravity compensator and link weights on the manipulator elastostatic properties. In order to improve the identification accuracy, the industry oriented performance measure is used to define optimal measurement configurations and an enhanced partial pose measurement method is applied for the identification of the model parameters. The advantages of the developed approach are confirmed by experimental results that deal with the elastostatic calibration of a heavy industrial robot used for milling. The achieved accuracy improvement factor is about 2.4.

Mots clés: Robot-based milling; elastostatic calibration; gravity compensator

Domaines: Robotique [cs.RO]

Alexandr Klimchik, Yier Wu, Stéphane Caro, Benoît Furet, Anatol Pashkevich. Accuracy Improvement of Robot-Based Milling Using an Enhanced Manipulator Model. Advances on Theory and Practice of Robots and Manipulators, Springer, pp.73-81, 2014, ⟨10.1007/978-3-319-07058-2_9⟩. ⟨hal-01066965⟩