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Jingnan Yan1, Yue Wu1, Kexin Ji1

  • 1School of Technology, State Key Laboratory of Efficient Production of Forest Resources, Key Laboratory of National Forestry and Grassland Administration on Forestry Equipment and Automation, Beijing Forestry University, Beijing, China.

PloS one
|February 14, 2025
PubMed
概括

这项研究引入了使用高斯混合模型进行机器人手臂轨迹学习的新方法. 它准确地选择最佳的核数量,大大提高了轨迹精度超过15%.

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