Soft Multi-point Waveguide Sensor for Proprioception and Extereoception in Inflatable Fingers

Ahmed Hassan, Faisal Al Jaber, Hareesh Godaba, I. Vitanov, K. Althoefer
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引用次数: 2

Abstract

Disadvantages of conventional robotic systems include rigidity, multiple moving parts, and the need for elaborate safety mechanisms when used in human-machine interaction. Soft manipulators and grippers are gaining in popularity due to being able to handle large payloads whilst being lightweight, highly compliant, low-cost, and compactible or collapsible. Yet soft robots cannot make use of traditional rigid sensors to measure their pose or interaction with the environment. Perception in soft robotics needs to embrace alternative methods: sensors made from soft materials that perform robustly under compression and bending conditions; i.e, stretchable soft sensors that rely on (their) material and electrical properties to output signal measurements. However, many such sensors come with inherent drawbacks, including material incompatibility, fabrication complexity, and hysteresis. In this paper, we report on the use of multiple staggered optical waveguide sensors embedded in silicone. These stretchable optical waveguide sensors coated with a thin layer of gold were fabricated and integrated with a fabric-based, inflatable robot finger. An experimental study was performed to evaluate the sensor's responsiveness. We find that multi-curvature pose estimation (from 0.05-0.135 m-1) (from fully deflated to maximum inflation) can be acquired after integration with the inflatable robot finger. The sensor proves capable of measuring force information by way of interaction with the environment at multiple points along the gripper.
软多点波导传感器在充气式手指本体感觉和外感觉中的应用
传统机器人系统的缺点包括刚性,多个运动部件,以及在人机交互中使用时需要精心设计的安全机制。软操纵器和抓手越来越受欢迎,因为能够处理大的有效载荷,同时重量轻,高度合规,低成本,紧凑或可折叠。然而,软体机器人不能利用传统的刚性传感器来测量它们的姿势或与环境的互动。软机器人的感知需要采用替代方法:由柔软材料制成的传感器,在压缩和弯曲条件下表现稳健;即,可拉伸的软传感器,依靠(它们)的材料和电气特性来输出信号测量。然而,许多这样的传感器都有固有的缺点,包括材料不兼容、制造复杂和滞后。在本文中,我们报告了在硅树脂中嵌入多个交错光波导传感器的使用。这些可拉伸的光波导传感器涂上一层薄薄的金,并与基于织物的充气机器人手指集成在一起。对传感器的响应性进行了实验研究。我们发现,在与充气机器人手指集成后,可以获得多曲率姿态估计(从0.05-0.135 m-1)(从完全放气到最大充气)。实验证明,该传感器能够通过与夹持器沿线多个点的环境相互作用来测量力信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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