Research on Feedforward Control Based on Robot Dynamics Parameters Identification

Shao, Xingmao; Wang, Shoujun; Yang, Liusong; Liu, Nan

doi:10.1109/icma49215.2020.9233788

Cited by 6 publications

(1 citation statement)

References 12 publications

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“…On the other hand, the remaining 54 (9 × 6), which include links and motors inertia and Coulomb and viscous friction, remain unknown, thus preventing the definition of accurate dynamic models. According to [2,3], this is of primary importance for control algorithms currently adopted for industrial manipulators which often rely on control strategies far more complex than simple Proportional-Integral-Differential (PID) ones [4]. On the other hand, a different approach could be derived from [5], where deterministic artificial intelligence has been effectively used to learn the dynamic properties of an unmanned underwater vehicle for autonomous trajectory generation and control.…”

Section: Introductionmentioning

confidence: 99%

Effects of Temperature and Mounting Configuration on the Dynamic Parameters Identification of Industrial Robots

et al. 2021

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Dynamic parameters are crucial for the definition of high-fidelity models of industrial manipulators. However, since they are often partially unknown, a mathematical model able to identify them is discussed and validated with the UR3 and the UR5 collaborative robots from Universal Robots. According to the acquired experimental data, this procedure allows for reducing the error on the estimated joint torques of about 90% with respect to the one obtained using only the information provided by the manufacturer. The present research also highlights how changes in the robot operating conditions affect its dynamic behavior. In particular, the identification process has been applied to a data set obtained commanding the same trajectory multiple times to both robots under rising joints temperatures. Average reductions of the viscous friction coefficients of about 20% and 17% for the UR3 and the UR5 robots, respectively, have been observed. Moreover, it is shown how the manipulator mounting configuration affects the number of the base dynamic parameters necessary to properly estimate the robots’ joints torques. The ability of the proposed model to take into account different mounting configurations is then verified by performing the identification procedure on a data set generated through a digital twin of a UR5 robot mounted on the ceiling.

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