A Perspective on Cephalopods Mimicry and Bioinspired Technologies toward Proprioceptive Autonomous Soft Robots

Octopus skin is an amazing source of inspiration for bioinspired sensors, actuators and control solutions in soft robotics. Soft organic materials, biomacromolecules and protein ingredients in octopus skin combined with a distributed intelligence, result in adaptive displays that can control emerging optical behavior, and 3D surface textures with rough geometries, with a remarkably high control speed (≈ms). To be able to replicate deformable and compliant materials capable of translating mechanical perturbations in molecular and structural chromogenic outputs, could be a glorious achievement in materials science and in the technological field. Soft robots are suitable platforms for soft multi-responsive materials, which can provide them with improved mechanical proprioception and related smarter behaviors. Indeed, a system provided with a “learning and recognition” functions, and a constitutive “mechanical” and “material intelligence” can result in an improved morphological adaptation in multi-variate environments responding to external and internal stimuli. This review aims to explore challenges and opportunities related to smart and chromogenic responsive materials for adaptive displays, reconfigurable and programmable soft skin, proprioceptive sensing system, and synthetic nervous control units for data processing, toward autonomous soft robots able to communicate and interact with users in open-world scenarios

Multimodal Supervised Exercise Training Is Effective in Improving Long Term Walking Performance in Patients with Symptomatic Lower Extremity Peripheral Artery Disease.

This study aimed to evaluate the effect of a multimodal supervised exercise training (SET) program on walking performance for 12 months in patients with symptomatic lower extremity peripheral artery disease (PAD). Consecutive patients with Fontaine stage II PAD participating in the SET program of our hospital were retrospectively investigated. Walking performance, assessed using a treadmill with measures of the pain-free and maximal walking distance (PFWD, MWD, respectively), and 6 min walking distance (6MWD), were tested before and following SET, as well as at 6 and 12 months after SET completion. Ninety-three symptomatic patients with PAD (65.0 ± 1.1 y) were included in the study. Following SET, the walking performance significantly improved (PFWD: +145%, p ≤ 0.001; MWD: +97%, p ≤ 0.001; 6MWD: +15%, p ≤ 0.001). At 6 months, PFWD (+257%, p ≤ 0.001), MWD (+132%, p ≤ 0.001), and 6MWD (+11%, p ≤ 0.001) remained significantly improved compared with the pre-SET condition. At 12 months, PFWD (+272%, p ≤ 0.001), MWD (+130%, p ≤ 0.001), and 6MWD (+11%, p ≤ 0.001) remained significantly improved compared with the pre-training condition. The walking performance remained significantly improved in both women and men for up to 12 months (p ≤ 0.001). Multimodal SET is effective at improving walking performance in symptomatic patients with PAD, with improvements lasting up to 12 months

Octopus-Inspired Suction Cups with Embedded Strain Sensors for Object Recognition

The octopus has unique capacities are sources of inspiration in developing soft robotic-enabling technologies. Herein, soft, sensorized, suction cups inspired by the suckers of Octopus vulgaris are presented. The suction cups using direct casting are fabricated, so that materials with different mechanical properties can be combined to optimize sensing and grasping capabilities. The artificial suckers integrate four embedded strain sensors, individually characterized and placed in a 90 degrees configuration along the rim of the suction cup. Based on this arrangement, how well the sensory suction cup can detect 1) the direction and 2) the angle (from 30 degrees to 90 degrees) of a touched inclined surface and 3) the stiffness of a touched flat object (shore hardness between 0010 and D50) both in air and underwater is evaluated. Data processing on neural networks is based using a multilayer perceptron to perform regression on individual properties. The results show a mean absolute error of 0.98 for angles, 0.02 for directions, and 97.9% and 93.5% of accuracy for the material classification in air and underwater, respectively. In view of the results and scalability in manufacturing, the proposed artificial suckers would seem to be highly effective solutions for soft robotics, including blind exploration and object recognition

Pulsatile Viscous Flows in Elliptical Vessels and Annuli: Solution to the Inverse Problem, with Application to Blood and Cerebrospinal Fluid Flow

We consider the fully-developed flow of an incompressible Newtonian fluid in a cylindrical vessel with elliptical cross-section and in an annulus between two confocal ellipses. Since flow rate is the main physical quantity which can be actually be derived from measurements, we address the extit {inverse problem} to compute the velocity field associated with a given, time-periodic flow rate. We propose a novel numerical strategy, which is nonetheless grounded on several analytical relations and which leads to the solution of systems of ordinary differential equations. Our method holds romise to be more amenable to implementation than previous ones based on challenging computation of Mathieu functions. We report numerical results based on measured data for human blood flow in the internal carotid artery, and cerebrospinal fluid flow in the upper cervical region of the human spine. Computational efficiency is shown, but the main goal of the present study is to provide an improved source of initial/boundary data, as well as a benchmark solution for pulsatile flows in elliptical sections and the proposed method has potential applications to bio-fluid dynamics investigations (e.g. to address aspects of relevant diseases), to biomedical applications (e.g. targeted drug delivery and energy harvesting for implantable devices), up to longer-term medical microrobotics applications

An autonomous biodegradable hygroscopic seed-inspired soft robot for visual humidity sensing

Visual sensors for relative humidity (RH) are of interest for distributed and autonomous environmental monitoring. Most of the visual humidity sensors are based on colorimetric sensing through the employment of hygroscopic inorganic pigments or photonic crystals (PCs). However, the toxicity of some inorganic pigments poses a risk to the environment especially if dispersed during in-situ measurements. On the other hand, the angle-dependent structural colours reading of the PCs, make these devices non suitable for autonomous and in-situ environmental monitoring. Here, we report the first visual humidity sensor using an artificial and hygroscopic seed-like robot (I-SeedPel) recently (2023) developed by our group for hygro-driven environmental exploration (https://doi.org/10.1002/advs.202205146). The I-SeedPel design is bioinspired to the hygroscopic and layered tissues of the Pelargonium appendiculatum seed and fabricated through additive manufacturing techniques using biodegradable polymers. The hygro-mechanical response of the I-SeedPel generates a reversible change of the geometrical features in the artificial seed structure (i.e., awn's angular displacement and diameter variation) related to the RH. The variation of the geometric properties can be quantified and correlated to RH in a wide range (30–90 %), with an accuracy of 97–98 %, with a resolution of 0.17–0.52 % of RH and a good reproducibility (average RSD = 14.7 %)

The role of hairs in the adhesion of octopus suckers: a hierarchical peeling approach.

Organisms like the octopus or the clingfish are a precious source of inspiration for the design of innovative adhesive systems based on suction cups, but a complete mechanical description of their attachment process is still lacking. In this paper, we exploit the recent discovery of the presence of hairs in the acetabulum roof of octopus suction cups to revise the current model for its adhesion to the acetabulum wall. We show how this additional feature, which can be considered an example of a hierarchical structure, can lead to an increase of adhesive strength, based on the analysis of the cases of a simple tape and an axisymmetrical membrane adhering to a substrate. Using peeling theory, we discuss in both cases the influence of hierarchical structure and the resulting variation of geometry on the adhesive energy, highlighting how an increase in number of hierarchical levels contributes to its increment, with a corresponding improvement in functionality for the octopus suckers

Air Trapping Mechanism in Artificial Salvinia-Like Micro-Hairs Fabricated via Direct Laser Lithography

Salvinia leaves represent an extraordinary example of how nature found a strategy for the long term retainment of air, and thus oxygen, on a surface, the so-called ‘Salvinia effect’, thanks to the peculiar three-dimensional and hierarchical shape of the hairs covering the leaves. Here, starting from the natural model, we have microfabricated hairs inspired by those present on the Salvinia molesta leaves, by means of direct laser lithography. Artificial hairs, like their natural counterpart, are composed of a stalk and a crown-like head, and have been reproduced in the microscale since this ensures, if using a proper design, an air-retaining behavior even if the bulk structural material is hydrophilic. We have investigated the capability of air retainment inside the heads of the hairs that can last up to 100 h, demonstrating the stability of the phenomenon. For a given dimension of the head, the greater the number of filaments, the greater the amount of air that can be trapped inside the heads since the increase in the number of solid–air interfaces able to pin the liquid phase. For this reason, such type of pattern could be used for the fabrication of surfaces for controlled gas retainment and gas release in liquid phases. The range of applications would be quite large, including industrial, medical, and biological fields

4D Printing of Humidity-Driven Seed Inspired Soft Robots

Geraniaceae seeds represent a role model in soft robotics thanks to their ability to move autonomously across and into the soil driven by humidity changes. The secret behind their mobility and adaptivity is embodied in the hierarchical structures and anatomical features of the biological hygroscopic tissues, geometrically designed to be selectively responsive to environmental humidity. Following a bioinspired approach, the internal structure and biomechanics of Pelargonium appendiculatum (L.f.) Willd seeds are investigated to develop a model for the design of a soft robot. The authors exploit the re-shaping ability of 4D printed materials to fabricate a seed-like soft robot, according to the natural specifications and model, and using biodegradable and hygroscopic polymers. The robot mimics the movement and performances of the natural seed, reaching a torque value of ≈30 µN m, an extensional force of ≈2.5 mN and it is capable to lift ≈100 times its own weight. Driven by environmental humidity changes, the artificial seed is able to explore a sample soil, adapting its morphology to interact with soil roughness and cracks