Generalizing Movement Primitives to New Situations
Generalizing Movement Primitives to New Situations
复制标题
将运动原语推广到新情况
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
V. Kyrki
中科院分区：
文献类型：
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作者：
Jens Lundell;Murtaza Hazara;V. Kyrki
尽管运动基元(MPS)已被广泛研究，但对其在新情况下的泛化研究却少之又少。为了应对不同的条件，MP的策略编码必须支持对任务参数的泛化，以避免为每个条件学习单独的原语。已经提出了局部和线性参数化模型来对任务参数进行内插，以提供有限的泛化。
Although motor primitives (MPs) have been studied extensively, much less attention has been devoted to studying their generalization to new situations. To cope with varying conditions, a MP’s policy encoding must support generalization over task parameters to avoid learning separate primitives for each condition. Local and linear parameterized models have been proposed to interpolate over task parameters to provide limited generalization.