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Texture Discrimination using a Flexible Tactile Sensor Array on a Soft Biomimetic Finger

机译:使用柔性触觉传感器阵列在软仿生手指上的纹理辨别

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Soft robotic fingers provide enhanced flexibility and dexterity when interacting with the environment. The capability of soft fingers can be further improved by integrating them with tactile sensors to discriminate various textured surfaces. In this work, a flexible 3×3 fabric-based tactile sensor array was integrated with a soft, biomimetic finger for a texture discrimination task. The finger palpated seven different textured plates and the corresponding tactile response was converted into neuromorphic spiking patterns, mimicking the firing pattern of mechanoreceptors in the skin. Spike-based feature metrics were used to classify different textures using the support vector machine (SVM) classifier. The sensor was able to achieve an accuracy of 99.21% when two features, mean spike rate and average inter-spike interval, from each taxel were used as inputs into the classifier. The experiment showed that an inexpensive, soft, biomimetic finger combined with the flexible tactile sensor array can potentially help users perceive their environment better.
机译:软机械手指在与环境互动时提供增强的柔韧性和灵巧性。通过将它们与触觉传感器集成以区分各种纹理表面来进一步改善软手指的能力。在这项工作中,柔性3×3基础织物的触觉传感器阵列与柔软的仿生手指集成在纹理歧视任务中。手指触摸七种不同的纹理板,并将相应的触觉反应转化为神经形态尖峰图案,模仿皮肤中机械运动员的烧制模式。基于Spike的特征度量用于使用支持向量机(SVM)分类器对不同的纹理进行分类。当从每个TaxEL中使用两个特征,平均尖峰速率和平均速度间隔时,传感器能够实现99.21%的精度。该实验表明,廉价,柔软,仿生的手指与柔性触觉传感器阵列相结合,可能有助于用户更好地感知其环境。

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