Empowering Particle Jamming Soft Gripper with Tactility via Stretchable Optoelectronic Sensing Skin

IF 6.1 Q1 AUTOMATION & CONTROL SYSTEMS Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) Pub Date : 2024-08-11 DOI:10.1002/aisy.202400285
Liyan Mo, Wenhao Xie, Jingting Qu, Jiutian Xia, Yunquan Li, Yuanfang Zhang, Tao Ren, Yang Yang, Juan Yi, Changchun Wu, Yonghua Chen
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Abstract

Particle-jamming soft grippers demonstrate notable shape adaptability and adjustable stiffness, which improve their grasping efficiency. However, integrating tactile sensing into these grippers presents challenges due to the specific properties of the particle jamming mechanism. This study introduces a parallel particle jamming soft gripper equipped with tactile sensing capabilities. The gripper consists of two tactile sensing particle jamming pads (TSPJPs) that are integrated with flexible optoelectronic skins. These skins are made of silicone rubber membranes and are embedded with a 3 × 3 array of stretchable optical waveguide arrays (SOWAs). Testing indicates that incorporating these sensors enhances the gripper's tactile sensing capabilities, with minimal impact on its particle jamming-based grasping function. A single TSPJP can accurately detect various contact points and estimate the contract forces. The proposed soft gripper can reliably grasp a wide range of objects, varying in shape, hardness, and weight, and it provides detailed tactile feedback on contact locations and the intensity of the grasping through the SOWA sensor. It can precisely distinguish between different grasping postures using a light gradient boosting machine (LightGBM) learning model. Furthermore, it can effectively detect the slippage of grasped objects, facilitating accurate closed-loop control for secure manipulation.

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通过可拉伸光电传感皮肤增强粒子干扰软爪的触感
颗粒干扰软夹持器具有良好的形状适应性和刚度可调性,提高了夹持效率。然而,由于粒子干扰机制的特定特性,将触觉传感集成到这些夹具中提出了挑战。本文介绍了一种具有触觉感知能力的平行粒子干扰软爪。该夹具由两个触觉传感粒子干扰垫(tspjp)组成,并与柔性光电皮肤集成。这些皮肤由硅橡胶膜制成,并嵌入3x3可拉伸光波导阵列(sowa)。测试表明,结合这些传感器增强了抓手的触觉感知能力,对其基于粒子干扰的抓取功能的影响最小。单个TSPJP可以准确地检测各种接触点并估计收缩力。所提出的软爪可以可靠地抓取各种形状、硬度和重量不同的物体,并通过SOWA传感器提供有关接触位置和抓取强度的详细触觉反馈。利用光梯度增强机(light gradient boosting machine, LightGBM)学习模型,可以精确区分不同的抓取姿势。此外,它可以有效地检测抓取物体的滑移,为安全操作提供精确的闭环控制。
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CiteScore
1.30
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0
审稿时长
4 weeks
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