Data-driven Robust High-speed Grasping for A Variable Stiffness Soft-hand-eye System

数据驱动的鲁棒高速抓取可变刚度软手眼系统

• 批准号: 19K14950
• 负责人: Zhu Mingzhu
• 金额: $ 2.16万
• 依托单位: Ritsumeikan University
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Early-Career Scientists
• 财政年份: 2019
• 资助国家: 日本
• 起止时间: 2019-04-01 至 2020-03-31
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-19K14950/
• 关键词: Soft robotics; 3D Printing; Triboelectric; Self-powered; Soft gripper; Robust grasping; Data-driven

Significant advances in the area of additive manufacturing have provided a novel fabrication method to develop soft robots with its self-powered sensors. In this paper, multi-material 3D printing is used to directly print out a soft robotic finger with its triboelectric bending sensor. The reinforced soft finger with single-electrode triboelectric curvature sensor (RSF-S-TECS) combines the advantages of multi-material 3D printing and stretchable electrodes to achieve fast prototyping and easy system integration. The triboelectric curvature sensor is located on the top of the finger. One of the active layers of the S-TECS is directly printed on the top surface of the reinforced finger body by multi-material 3D printing, and another active layer is made of PDMS attached to a stretchable electrode. The S-TECS behavior is evaluated for different active surface profiles, applied forces and operational frequency using an automated setup. The integrated S-TECS can measure a finger curvature up to 8.2 m-1 under an extremely low working frequency of 0.06 Hz, proving the effectiveness of the proposed S-TECS as a self-powered curvature sensor. This work presents a novel design and fabrication method of S-TECS for its potential applications in multi-material 3D printed soft robotics.

增材制造领域的重大进展为开发具有自供电传感器的软机器人提供了一种新的制造方法。本文采用多材料3D打印技术直接打印出带有摩擦电弯曲传感器的柔性机器人手指。带有单电极摩擦电曲率传感器（RSF-S-TECS）的增强型软手指结合了多材料3D打印和可拉伸电极的优势，可实现快速原型设计和轻松的系统集成。摩擦电曲率传感器位于手指的顶部。S-TECS的其中一个活性层通过多材料3D打印直接打印在增强手指主体的顶面上，另一个活性层由附着在可拉伸电极上的PDMS制成。S-TECS的行为进行了评估，不同的活性表面轮廓，施加的力量和操作频率使用自动设置。集成的S-TECS可以在0.06 Hz的极低工作频率下测量高达8.2 m-1的手指曲率，证明了所提出的S-TECS作为自供电曲率传感器的有效性。这项工作提出了一种新的设计和制造方法的S-TECS在多材料3D打印软机器人的潜在应用。