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运动分割的切换隐式力模型
Switched Latent Force Models for Movement Segmentation |
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| 课程网址: |
http://videolectures.net/nips2010_alvarez_slf/
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| 主讲教师: |
Mauricio Alvarez
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| 开课单位: |
曼彻斯特大学
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| 开课时间: |
2011-03-25
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| 课程语种: |
英语
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| 中文简介: |
潜力模型以核函数或协方差函数的形式对多个相关动力系统之间的相互作用进行编码。将要建模的每个变量表示为一个微分方程的输出，每个微分方程由一个潜在函数的加权和驱动，不确定性由高斯过程先验给出。本文针对机器人电机基本体的确定问题，考虑采用隐力模型框架。为了处理动力系统中的不连续性或潜在驱动力，我们引入了基本潜在力模型的扩展，该模型在不同的潜在功能和潜在的不同动力系统之间切换。这为机器人运动创建了一个通用的表示，可以捕捉离散的变化和动力学中的非线性。我们给出了合成数据和用barrett-wam机器人作为触觉输入装置记录的撞击运动的例子。我们的灵感来源于机器人运动原语，但我们希望我们的模型在包括人类运动捕捉数据模型和系统生物学在内的动态系统中有广泛的应用。
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| 课程简介: |
Latent force models encode the interaction between multiple related dynamical systems in the form of a kernel or covariance function. Each variable to be modeled is represented as the output of a differential equation and each differential equation is driven by a weighted sum of latent functions with uncertainty given by a Gaussian process prior. In this paper we consider employing the latent force model framework for the problem of determining robot motor primitives. To deal with discontinuities in the dynamical systems or the latent driving force we introduce an extension of the basic latent force model, that switches between different latent functions and potentially different dynamical systems. This creates a versatile representation for robot movements that can capture discrete changes and non-linearities in the dynamics. We give illustrative examples on both synthetic data and for striking movements recorded using a Barrett WAM robot as haptic input device. Our inspiration is robot motor primitives, but we expect our model to have wide application for dynamical systems including models for human motion capture data and systems biology.
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| 关 键 词: |
高斯过程; 计算机科学; 机器学习; 核方法
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| 课程来源: |
视频讲座网
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| 最后编审: |
2020-06-02：张荧(课程编辑志愿者)
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| 阅读次数: |
48
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