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State Space Estimation Method for the Identification of an Industrial Robot Arm

Mathieu Brunot, Alexandre Janot, Francisco Javier Carrillo

发表年份
2017
引用次数
8

摘要

In this paper, we study the identification of industrial robot dynamic models. Since the models are linear with respect to the parameters, the usual identification technique is based on the Least-Squares method. That requires a careful preprocessing of the data to obtain consistent estimates of the dynamic parameters. The preprocessing mainly consists in estimating the joint velocities and accelerations from the measured joint positions. In this paper, we carefully detail this process and propose a new procedure based on Kalman filtering and fixed interval smoothing. This new technique is compared to usual one with experimental data considering an industrial robot arm. The obtained results show that the proposed technique is a credible alternative, especially if the system bandwidth is unknown.

关键词

SmoothingKalman filterIdentification (biology)PreprocessorIndustrial robotComputer scienceRobotProcess (computing)Control theory (sociology)Robotic arm

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