Positioning error compensation method for industrial robots based on stacked ensemble learning
Qizhi Chen,
Chengrui Zhang,
Wei Ma
et al.
Abstract:Due to the advantages of low cost, high flexibility and large workspace, industrial robot has been considered to be the most promising plan to replace traditional CNC machine tool. However, the low absolute positioning accuracy of robot is a key factor that restricts further application in high-precision metal cutting scenarios. In order to improve the absolute positioning accuracy of robot, a positioning error compensation method based on the stacked ensemble learning is proposed. Firstly, the sources of posi… Show more
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