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    • 基于PCA-RVM模型的机器人铣削加工末端变形误差预测

    HU Huazhou,JIN Yongqiao,TANG Xiaowei

    Equipment Manufacturing Technology（2021）

    Cited 1|Views6
    Abstract
    机器人铣削加工是大型结构件的重要加工手段,具有工作空间大、成本低的优势,然而由于工业机器人相对弱刚性特征,其末端在铣削力的作用下会发生变形误差,制约其应用工况.传统的末端变形误差获取方法通常是根据末端刚度模型以及刀具铣削力模型来利用胡克定律预测,难以考虑机器人加工系统中的不确定性因素,具有一定的误差.针对机器人铣削加工变形误差预测中的不确定性因素,开展基于数据驱动的误差预测研究.首先利用主成分分析和相关向量机构建铣削力、关节角等多参数与变形误差的映射关系;其次在机器人铣削加工平台中开展铣削实验并采集样本,基于PCA-RVM模型训练变形误差预测模型,并采用均方根误差和平均绝对误差指标验证了基于数据驱动的变形误差预测模型的精确度及可靠性.
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    • Pretraining has recently greatly promoted the development of natural language processing (NLP)
    • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
    • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
    • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
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