Touch modality interpretation for an EIT-based sensitive skin
Touch modality interpretation for an EIT-based sensitive skin
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基于 EIT 的敏感皮肤的触摸方式解释
DOI：
10.1109/icra.2011.5979697
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发表时间：
2011
期刊：
影响因子：
--
通讯作者：
Mari Velonaki
中科院分区：
文献类型：
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作者：
David Silvera Tawil;D. Rye;Mari Velonaki
在社会互动中，人类从触觉刺激中提取重要信息，以提高他们对互动的理解。机器人中类似能力的开发将有助于未来人与机器人直观交互的成功。提出了一种基于电阻抗断层成像(EIT)原理的触觉传感方法，可用于机器人实现大尺寸、柔性、可伸缩的人工敏感皮肤。基于LogitBoost算法的分类器被用来对基于EIT的实验皮肤上的六种不同类型的触摸的形态进行分类。实验表明，在大约80%的试验中，触摸的形式被正确分类。这可以与人类触摸接受者的实验精度相媲美。与以往应用于不同人工敏感皮肤的分类算法相比，分类精度有了显著的提高。
During social interaction, humans extract important information from tactile stimuli that improves their understanding of the interaction. The development of a similar capacity in a robot will contribute to the future success of intuitive human-robot interaction. This paper presents a method of touch sensing based on the principle of electrical impedance tomography (EIT) that can be used to implement a large, flexible and stretchable artificial sensitive skin for robots. A classifier based on the “LogitBoost” algorithm is used to classify the modality of six different types of touch on an experimental EIT-based skin. Experiments showed that the modality of touch was correctly classified in approximately 80% of the trials. This is comparable with the experimental accuracy of a human touch recipient. The classification accuracies show significant improvements from previous classification algorithms applied to different artificial sensitive skins.