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

2019 Fiscal Year Annual Research Report

• Project/Area Number: 19K14950
• Research Institution: Ritsumeikan University
• Principal Investigator: Zhu Mingzhu 立命館大学, 立命館グローバル・イノベーション研究機構, 研究員 (50806180)
• Project Period (FY): 2019-04-01 – 2020-03-31
• Keywords: Soft robotics / 3D Printing / Triboelectric / Self-powered

Outline of Annual Research Achievements

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.