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A glove-based system for studying hand-object manipulation via joint pose and force sensing

机译:一种基于手套的系统,用于通过关节姿态和力传感研究手对象操纵

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We present a design of an easy-to-replicate glove-based system that can reliably perform simultaneous hand pose and force sensing in real time, for the purpose of collecting human hand data during fine manipulative actions. The design consists of a sensory glove that is capable of jointly collecting data of finger poses, hand poses, as well as forces on palm and each phalanx. Specifically, the sensory glove employs a network of 15 IMUs to measure the rotations between individual phalanxes. Hand pose is then reconstructed using forward kinematics. Contact forces on the palm and each phalanx are measured by 6 customized force sensors made from Velostat, a piezoresistive material whose force-voltage relation is investigated. We further develop an open-source software pipeline consisting of drivers and processing code and a system for visualizing hand actions that is compatible with the popular Raspberry Pi architecture. In our experiment, we conduct a series of evaluations that quantitatively characterize both individual sensors and the overall system, proving the effectiveness of the proposed design.
机译:我们介绍了一种简单复制的基于手套的系统,可以在精细操纵行动期间收集人类的手数据来可靠地执行同时姿势和力传感。该设计包括一个能够联合收集手指姿势的数据,手部和手掌和每种蝴蝶人的力量的感觉手套。具体地,感官手套采用15个IMU的网络来测量单个兰那烷之间的旋转。然后使用向前运动学重建手姿势。手掌上的接触力和每种点击力由由Velostat制成的6个定制的力传感器测量,该压阻材料研究其力 - 电压关系。我们进一步开发了一个开源软件管道,包括驱动程序和处理代码以及用于可视化与流行的Raspberry PI架构兼容的手动操作的系统。在我们的实验中,我们进行了一系列评估,这些评估是单独表征个别传感器和整体系统,证明了所提出的设计的有效性。

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