Multifunctional adaptive structures for soft robotic applications

• Main Author: Yang, Xudong
• Other Authors: Yifan Wang
• Format: Thesis-Doctor of Philosophy
• Language: English
• Published: Nanyang Technological University 2025
• Subjects: Engineering
• Online Access: https://hdl.handle.net/10356/182071
• Institution: Nanyang Technological University

The remarkable adaptability of natural organisms in altering body shapes and adjusting muscle stiffness in response to environmental cues has spurred the development of adaptive robotic structures. These structures possess the capability to transform their geometrical configurations and tune mechanical properties in response to specific stimuli, finding applications in soft robotics and wearable assistive devices. However, achieving the morphing of intricate three-dimensional (3D) shapes from a two-dimensional (2D) flat state presents challenges, necessitating controlled manipulation of surface curvature. Consequently, traditional morphing materials primarily rely on material elasticity and structural instability, resulting in limited mechanical stiffness. To address this trade-off, smart materials such as shape memory polymers and electro/magnetorheological materials have been explored. Nevertheless, these materials often suffer from slow response rates and complex actuation setups. In this thesis, we aim to overcome these challenges by proposing adaptive structures based on particle assemblies. Firstly, we introduce adaptive structures with shape morphing and stiffness tuning abilities from particle assemblies. Through vacuum actuation, we achieve particle assemblies and tune their stiffness by varying the vacuum pressure. Additionally, by incorporating conductive particles, we enable self-sensing capabilities, demonstrated in applications such as robotic grippers for detecting object weight and shape. Secondly, regarding the morphing limitations in previous chapter, we introduce an improved computational method to tessellate arbitrary 3D surfaces into particle assemblies. In this part, to achieve more general shapes from particle assemblies, we present a computational method named Hierarchical tessellation. Assembling these particles with tendon-drive allows for variable stiffness by adjusting the boundary stress generated by tendon tension. We demonstrate their applications with morphing lamp and protective channels. Thirdly, to better understand the tunable mechanics of our adaptive structures based on particle assemblies, in this part, we characterize the effects of the particle geometry and boundary stress on the tunable mechanical responses under threepoint bending test and uniaxial compression test through analytical modeling, finite element simulations, and experimental methods. Lastly, we develop robotic assistive devices based on the adaptive structures derived from particle assemblies. In this part, we present active fabrics consisting of tessellated particles connected with actuating fibers. These active fabrics can rapidly (within seconds) transition between soft compliant configurations and rigid states conformable to the body (> 350 times stiffness change, loading capacity to weight ratio > 50) while minimizing the device volume after actuation. We demonstrate the versatility of our active fabrics as exosuits for tremor suppression and lifting assistance.