Evaluating Morphological Computation in Muscle and DC-Motor Driven Models of Hopping Movements
Evaluating Morphological Computation in Muscle and DC-Motor Driven Models of Hopping Movements
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DOI：
10.3389/frobt.2016.00042
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发表时间：
2016-07-25
影响因子：
3.4
通讯作者：
Ay, Nihat
中科院分区：
文献类型：
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作者：
Ghazi-Zahedi, Keyan;Haeufle, Daniel F. B.;Ay, Nihat
在具体人工智能的背景下，形态计算是指由身体（和环境）进行的过程，否则必须由大脑执行。利用环境和形态特性是体现系统的一个重要特征。主要原因是它可以显着降低控制器的复杂性。形态计算的一个重要方面是它本身不能分配给具体系统，但正如我们所展示的，它是行为和状态依赖的。在这项工作中，我们评估了两种不同的形态计算方法，这些方法可应用于机器人系统和生物运动的计算机模拟。例如，这些措施是在肌肉和直流电机驱动的跳跃模型上进行评估的。我们表明，对跳跃行为的状态相关分析提供了仅从平均测量中无法获得的额外见解。这项工作包括用于措施的算法和计算机代码。
In the context of embodied artificial intelligence, morphological computation refers to processes, which are conducted by the body (and environment) that otherwise would have to be performed by the brain. Exploiting environmental and morphological properties are an important feature of embodied systems. The main reason is that it allows to significantly reduce the controller complexity. An important aspect of morphological computation is that it cannot be assigned to an embodied system per se, but that it is, as we show, behavior and state dependent. In this work, we evaluate two different measures of morphological computation that can be applied in robotic systems and in computer simulations of biological movement. As an example, these measures were evaluated on muscle and DC-motor driven hopping models. We show that a state-dependent analysis of the hopping behaviors provides additional insights that cannot be gained from the averaged measures alone. This work includes algorithms and computer code for the measures.