Enhancing Gecko-Inspired Adhesion through Multi-scale and Multi-modal Strategies for Soft Robotic Grippers

Abstract

Gecko-inspired adhesion owing to its advantages of high adhesion strength, zero power consumption, tunable adhesion through microstructure design, residue-free detachment and relatively good surface conformity it has been applied in various fields such as robotic grippers, climbing robots, and functional adhesive patches.

Although gecko-inspired adhesion has been shown to be highly adhesive, the performance of current synthetic gecko-inspired skins (GSs) has been poor on rough surfaces. In this study, the author investigates how to increase the adhesion of gecko-inspired skins on different surfaces from smooth to rough by generating a controllable preload and by improving the compliance of gecko-inspired skins. Furthermore, demonstrations show that the different gecko-inspired skins developed in this study perform effectively when applied to robotic grippers.

The advances in this thesis demonstrate gecko-inspired adhesive systems with enhanced adhesion for robotic manipulation, enabling reliable handling of different objects ranging from rigid to soft, including flexible and delicate materials, with surface roughness varying from smooth to rough.

Date of Award	20 Jan 2026
Original language	English
Awarding Institution	University of Bristol
Supervisor	Andrew T Conn (Supervisor) & Jonathan M Rossiter (Supervisor)