A Sensorized Mechanically Self-Guided Suction Cup for Improved Adhesion in Complex Environments
Octopuses can effectively interact with environments using their agile suction cups, in which abundant neuroreceptors are embodied inside. Inspired by this, we proposed an electronics-integrated self-guided adhesive suction cup (E-SGAS) capable of environmental sensing and adaptively adhesion on diverse surfaces. E-SGAS features an inflatable adhesive membrane and an under-actuated design, enabling it to adapt to various angles and surface roughness under low preloads. A theoretical model is presented to predict self-guided adhesion outcomes. The integrated multilayer stretchable liquid metal sensory circuit (with a maximum deformation rate of 186%) in the adhesive membrane allows for detecting expansion, contact, suction, leakage, and surface roughness. E-SGAS can also process the sensory information to guide intelligent gripping in various complex environments. Experimental results demonstrate the ability of E-SGAS to autonomously grip under a preload force of 0.11 N, a maximum adhesion force of 57.9N, and a detachment force of only 0.34 N. It can adhere to surfaces up to 60-grit roughness and accommodate a surface with a relative angle of 90°. We also show that E-SGAS can capture flying objects or work in a confined space. The proposed adhesion and sensing strategies aim to enhance the performance and expand the application range of suction cup-like grippers. E-SGAS's results can provide design insights into creating stretchable electronics-integrated bioinspired adhesive systems that can interact with unconstructed environments.
Authors
- Li Wen (ORCID: https://orcid.org/0000-0002-1498-3103)
- Haoyuan Xu (ORCID: https://orcid.org/0000-0003-2862-0888)
- Zhexin Xie (ORCID: https://orcid.org/0000-0001-6994-6863)
- Bo Yuan (ORCID: https://orcid.org/0000-0001-9899-8961)
- Feiyang Yuan (ORCID: https://orcid.org/0000-0003-1597-1531)
- Wenjie Wu (ORCID: https://orcid.org/0000-0002-5382-5394)
- Lufeng Tian (ORCID: https://orcid.org/0009-0001-5730-0376)
- Zhongqiang Fu (ORCID: https://orcid.org/0009-0009-7840-5204)
- Ding Xilun
- Tianmiao Wang
Institutions
- National University of Singapore (SG)
- Beihang University (CN)
Publication Details
- Journal
- Soft Robotics
- Published
- 2025-04-09
- DOI
- https://doi.org/10.1089/soro.2024.0152
- Primary Topic
- Adhesion, Friction, and Surface Interactions
- Type
- article
- Field-Weighted Citation Impact
- 0.00