Shape‐Adaptive Mechanical Metastructure Enables Robust Adhesion and Dynamic Capturing of 3D Objects
Rui Xu, Changhong Linghu, Wentao Mao, Haozhe Zhang, Jiang-Hao Yu, Yulong He, Yangchengyi Liu, Yan Li, Huajian Gao, Yan‐Feng Chen, Minghui Lu, Xin Li, K. Jimmy Hsia
- 发表年份
- 2025
- 引用次数
- 4
摘要
Abstract Grasping irregularly shaped and fast‐moving objects remains a key challenge in robotics. Although planar grippers that utilize surface van der Waals interactions are valued for their energy efficiency, sustainability, reusability, and versatility, they struggle to adapt to three‐dimensional and dynamic objects. In this study, we introduce a shape‐adaptive mechanical metastructure (SAMMS) based on the concept of physical intelligence for robust and dynamic grasping of 3D objects. SAMMS integrates multistable snap fit structures with rotational ball joint tips and adhesive films. The snap fit structures enable shape adaptation and energy absorption, while the ball joint tips provide flexible alignment, together maximizing adhesion on irregular 3D surfaces. Furthermore, SAMMS achieves on‐demand detachment by selectively pushing out snap fit components. Experimental results show that SAMMS increases adhesion force by approximately 6.66‐fold and nearly doubles the capturable velocity compared to conventional designs. This innovation significantly broadens the capabilities of intelligent adhesion technologies, offering a robust solution for applications such as multifunctional assembly and space debris capture.
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