Soft Structures and their integrity: Inspiration from nature

Designing soft robots with increased toughness, an improved resistance to damage
propagation, and having more robust sensors, all while retaining their compliant prop-
erties, is crucial for applications in soft robotics.
The first contribution of this study is the proposal of a framework for nonlinear
multi-material architectural design of soft structures to enhance their toughness and
delay damage propagation. Regarding biological evolution, creatures like the Pangolin,
Seashell, and Arapaima have evolved strategies for deflecting cracks and maintaining
strength in their bodies. What are the synergies and limitations of combining different
materials in a single structure to delay crack propagation while significantly maintaining
post-damage toughness? This study reveals a dynamic interplay when significantly
different materials are combined in one structure, which can either weaken or strengthen
the multi-material structure’s toughness.
Our research explores how multi-material structures, inspired by nature, affect the
crack propagation. We have found that the multi-material toughness largely depend on
parameters such as the components’ relative morphology, architecture, spatial distribu-
tion, surface areas, and Young’s modulus. In multi-material design, linear geometry in
morphology and/or architecture significantly reduces overall toughness and fails to de-
lay crack propagation. In contrast, incorporating geometric nonlinearities in morphol-
ogy and architecture significantly maintains higher total toughness even after damage
and significantly delays crack propagation. This study can open the door to further
research and promising applications in soft robotics.
Also for sensing, Nature provides various solutions to overcome sensing difficulties.
Spider orb webs are an intriguing source of inspiration for creating strain sensors. The
unique structural properties of spider orb webs, capable of detecting even subtle changes
in strain, offer valuable insights for developing susceptible strain sensors. Most sensors
today are based on linear structures or matrices, whereas nature exhibits fascinating
characteristics of geometric nonlinearities. Radial and spiral threads that compose spi-
der webs are designed to disperse kinetic energy and trap prey, which is one reason
spiders build these specific structures. In this work, we explore the incorporation of
geometric nonlinearities in the design of spider web inspired strain sensors.
Practical limitations and failures encountered in this study, require attention for fur-
ther progress. While the spider web structure, including radials and spirals, appears
promising for providing redundant elements in a more robust sensor design, enhance-
ments in 3D printing of conductive materials are necessary to improve its behavior. A
comparison between 3D printing and casting highlights the importance of 3D print-
ing for complex sensor structures, such as those involving multiple stages of a spider
web. Spirals notably emerge as elements that increase the robustness of the sensors, as
demonstrated through SOFA simulations of damaged spiderweb sensors and resistance
measurements of purposefully damaged spider web sensors. Future work will explore
bi-axial strain simulation and tests for further development.
Soft robotics transitioning from laboratory innovation to commercialization entails
several critical factors gleaned from interviews and discussions featured on the author’s
Soft Robotics podcast and articles in Robotics Reports. Drawing on insights and per-
spectives gained,the final contribution explores what constitutes a good soft robot de-
sign for real-world applications. Ultimately, prioritizing commercialization should be
guided by a nuanced understanding of the potential societal impact and ethical con-
siderations. While commercialization can accelerate the translation of research into
practical solutions, it is equally crucial to preserve space for exploratory research that
may not have immediate commercial applications but could yield profound insights or
unexpected breakthroughs in the future.