Table of contents

This paper presents a review of biological mechanical linkage mechanisms. One purpose is to identify the range of kinematic functions that they are able to perform. A second purpose is to review progress in bioinspired designs. Ten different linkage mechanisms are presented. They are chosen because they cover a wide range of functionality and because they have potential for bioinspired design. Linkage mechanisms enable animal joints to perform highly sophisticated and optimised motions. A key function of animal linkage mechanisms is the optimisation of actuator location and mechanical advantage. This is crucially important for animals where space is highly constrained. Many of the design features used by engineers in linkage mechanisms are seen in nature, such as short coupler links, extended bars, elastic energy storage and latch mechanisms. However, animal joints contain some features rarely seen in engineering such as integrated cam and linkage mechanisms, nonplanar four-bar mechanisms, resonant hinges and highly redundant actuators. The extreme performance of animal joints together with the unusual design features makes them an important area of investigation for bioinspired designs. Whilst there has been significant progress in bioinspiration, there is the potential for more, especially in robotics where compactness is a key design driver.

An optical zoom imaging system that can vary the magnification factor without displacing the object and the image plane has been widely used. Nonetheless, conventional optical zoom imaging systems suffer from slow response, complicated configuration, vulnerability to misalignment during zoom operation, and are incompatible with miniaturized applications. This review article focuses on state-of-the-art research on novel optical zoom imaging systems that use adaptive liquid lenses. From the aspect of the configuration, according to the number of adaptive liquid lenses, we broadly divide the current optical zoom imaging systems using adaptive liquid lenses into two configurations: multiple adaptive liquid lenses, and a single adaptive liquid lens. The principles and configurations of these optical zoom imaging systems are introduced and represented. Three different working principles of the adaptive liquid lens (liquid crystal, polymer elastic membrane, and electrowetting effect) adopted in the optical zoom imaging systems are reviewed. Some representative applications of optical zoom imaging systems using adaptive liquid lenses are introduced. The opportunities and challenges of the optical zoom imaging systems using adaptive liquid lenses are also discussed. This review aims to provide a snapshot of the current state of this research field with the aim to attract more attention to put forward the development of the next-generation optical zoom imaging systems.

Biofouling refers to the adverse attachment and colonization of fouling organisms, including macromolecules, bacteria, and sessile invertebrates, on the surfaces of materials submerged in aquatic environments. Almost all structures working in watery surroundings, from marine infrastructures to healthcare facilities, are affected by this sticky problem, resulting in massive direct and indirect economic loss and enormous cost every year in protective maintenance and remedial cleaning. Traditional approaches to preventing marine biofouling primarily rely on the application of biocide-contained paints, which certainly impose adverse effects on the ocean environment and marine ecology. Biomimicry offers an efficient shortcut to developing environmentally friendly antifouling techniques and has yielded encouraging and promising results. The antifouling strategies learned from nature can be broadly classified into two categories according to the nature of the cues applied for biofouling control. One is the chemical antifouling techniques, which are dedicated to extracting the effective antifoulant compounds from marine organisms and synthesizing chemicals mimicking natural antifoulants. In contrast, the physical biomimetic (BM) antifouling practices focus on the emulation and optimization of the physical cues such as micro and nanoscale surface topographies learned from naturally occurring surfaces for better antifouling efficacy. In this review, a synopsis of the techniques for manufacturing the BM and bioinspired (BI) antifouling surface topographies is introduced, followed by the bioassay to assess the antifouling performance of the structured surfaces. Then, the BM and BI surface topographies that were reported to possess enhanced antifouling competence are introduced, followed by a summary of theoretical modeling. The whole paper is concluded by summarizing the studies' deficiencies so far and outlooking the research directions in the future.

Evaporative interfaces help process heat and substances in a variety of technical realms, from electronic to architectural applications. Because geometry affects the hydraulics, thermal properties and aerodynamics of evaporative devices, their performance can be tuned through design. While non-smooth interfaces are widely exploited to enhance transfer passively, surface area extension in packed volumes is a predominant line of research. This leaves aerodynamic structure-transfer relations and the impact of geometry itself unclear. Meanwhile, protrusions in leaves such as lobes and toothed margins have been associated with enhanced vapor dissipation. This experimental study explores the design space of leaf-inspired structures with evaporating protrusions. Three sets of water-absorbing models with fixed evaporating surface area and unlimited hydraulic supply were tested: (1) paper strips with dimension-equivalent protrusions of varied shape and degree of elongation; (2) cellulose sponges with the same designs as their cross-sectional profile, extruded three-dimensionally; (3) ceramic tiles with grooves of varied cross-section, conceived as building elements for evaporative cooling. Overall, results demonstrate that protrusions affect mass transfer rate and surface temperatures and can be integrated in the design of evaporative exchangers with non-smooth geometries. For the paper models, evaporation rate correlated with protrusion aspect ratio, supporting a functional interpretation of leaf design and its utilization in low-wind plate-fin exchangers. However, the same transfer enhancement was not regained from simply extruding an effective design into three-dimensions. For the ceramic tiles, geometry-driven differences in evaporation depended on the aerodynamic roughness and size of the grooved pattern, and on ventilation. Their outdoor thermal behavior was complex due to a multifaceted interaction with the environment and geometry-related factors such as self-shading and thermal mass. Ultimately, this design effort illustrates the potential of structured interfaces for evaporative exchange and thermoregulating the built environment.

Natural flexural armors combine hard, discrete scales attached to soft tissues, providing unique combinations of surface hardness (for protection) and flexibility (for unimpeded motion). Scaled skins are now inspiring synthetic protective materials which offer attractive properties, but which still suffer from limited trade-offs between flexibility and protection. In particular, bending a scaled skin with the scales on the intrados side jams the scales and stiffen the system significantly, which is not desirable in systems like gloves where scales must cover the palm side. Nature appears to have solved this problem by creating scaled skins that can form wrinkles and folds, a very effective mechanism to accommodate large bending deformations and to maintain flexural compliance. This study is inspired from these observations: we explored how rigid scales on a soft membrane can buckle and fold in a controlled way. We examined the energetics of buckling and stability of different buckling modes using a combination of discrete element modeling and experiments. In particular, we demonstrate how scales can induce a stable mode II buckling, which is required for the formation of wrinkles and which could increase the overall flexural compliance and agility of bioinspired protective elements.

Artificial muscles have unique advantages for driving bionic robots because their driving mode is similar to biological muscles. However, there is still a big gap between the existing artificial muscle and biological muscle in performance. The twisted artificial muscles (TAMs) from nylon 6,6 provides a low-cost, high integration, low hysteresis driving method. But as a soft actuator, the control of the TAM is so complex that the advantage of excellent embeddedness has not been brought into play. This work presents a self-sensing control method for the TAM by monitoring the real-time resistance of the heating wire which realizes the accurate controlling of the TAM temperature. The simultaneous control of 18 TAMs is realized by using the self-sensing control method. By using a new step walking method based on the principle of insect bionics, a bionic soft hexapod robot with both multi-motion and load capacity is realized. Besides, due to the excellent environmental adaptability of the TAM, the bionic robot can realize amphibious motion both on land and underwater conditions, and the corresponding maximum load capacities are 300 g and 1 kg, respectively. This work not only provides a reliable self-sensing control method of the TAMs but also promotes the development of bionic soft robots.

This work investigates the possible integration of an energy harvester in a bioinspired fish-like aquatic unmanned vehicle. The defined fish-like system utilizes a reduced complexity prescribed motion as the representation for energy harvester to be subjected to. Nonlinear electromechanical modeling is performed by considering the geometric and piezoelectric nonlinearities. A convergence analysis is carried out in order to determine the required modes in the Galerkin discretization due to the presence of nonlinear interactions between the prescribed and relative motions. The utilization of higher-order modeling for the strain and material leads to the identification of impactful prescribed motions terms that can activate the nonlinearities in the system, results in more harmonics to consider, and leads to the presence parametric excitation terms. Considering a reduced-complex model by decreasing the value of the quadratic constraint envelope that the fish-like system would be forced with, the soft-robotic system behaves more with a base excitation characteristic. Small damping would allow this prescribed motion with reduced quadratic envelope forcing still induces a hardening behavior, but the other harmonics and parametric resonance seen are greatly reduced. Considering this reduced complexity system, the interaction between the prescribed and base excitations is also investigated to demonstrate that when the two excitations are of similar nature constructive and destructive build of the response waveform can occur when looking at near the first natural resonance. It is shown that the quenching phenomenon can take place which may result in a destructive response of the piezoelectric energy harvester. The results show that the robustness of the fish-like robot is directly dependent on the design parameters including the damping of the structure, importance of the undulatory motion, and activation of the resonances.

Fish benefit energetically when swimming in groups, which is reflected in lower tail-beat frequencies for maintaining a given speed. Recent studies further show that fish save the most energy when swimming behind their neighbor such that both the leader and the follower benefit. However, the mechanisms underlying such hydrodynamic advantages have thus far not been established conclusively. The long-standing drafting hypothesis—reduction of drag forces by judicious positioning in regions of reduced oncoming flow–fails to explain advantages of in-line schooling described in this work. We present an alternate hypothesis for the hydrodynamic benefits of in-line swimming based on enhancement of propulsive thrust. Specifically, we show that an idealized school consisting of in-line pitching foils gains hydrodynamic benefits via two mechanisms that are rooted in the undulatory jet leaving the leading foil and impinging on the trailing foil: (i) leading-edge suction on the trailer foil, and (ii) added-mass push on the leader foil. Our results demonstrate that the savings in power can reach as high as 70% for a school swimming in a compact arrangement. Informed by these findings, we designed a modification of the tail propulsor that yielded power savings of up to 56% in a self-propelled autonomous swimming robot. Our findings provide insights into hydrodynamic advantages of fish schooling, and also enable bioinspired designs for significantly more efficient propulsion systems that can harvest some of their energy left in the flow.

The flight of monarch butterflies is characterized by a relatively large wing, flapping at a relatively low frequency coupled with abdomen undulation. This paper presents the dynamics of a flapping wing flyer that can be applied to the coupled motion of the wing, body, and abdomen at the monarch butterfly scale, which is formulated directly on the configuration manifold. The resulting thorax and abdomen motion as well as the resultant forces are consistent with the flight of a live monarch butterfly. Based on these, beneficial effects of the abdomen undulation in the flight of monarch butterflies are illustrated. For both hover and forward-climbing trajectories, the abdomen undulation results in a reduction of the energy and power consumption. Furthermore, the Floquet stability analysis shows that the periodic orbits associated with both flight modes are stable. In particular, the abdomen undulation improves the stability. Compared to the dynamics of hawkmoth, bumblebee, and fruitfly models, the monarch possesses superior stability properties.

This paper presents a tendon-driven robotic finger with its inspiration derived from the human extensor mechanism. The analytical model presented relates the contractions of the intrinsic muscles of the human hand to abduction–adduction and coordinated motion of proximal and distal interphalangeal joints. The design presented is simplified from the complex webs of fibers appearing in prior works, but preserves the dual role the interossei have of abducting/adducting the finger and flexing it at the metacarpal-phalangeal joint with the finger outstretched. The anatomical feature in our design is that the proximal interphalangeal joint passes through a set of lateral bands as the finger flexes. We discovered that by including a mechanical stop that causes the lateral bands to 'fold' at large enough flexion aids coordinated movements of the two interphalangeal joints as the finger flexes. Because it involves engineering running and sliding fits, this finger admits a concise kinematic model, which accurately predicts the tendon excursions from a known pose. In this work, however, we evaluate what happens when the model is used to search for a sequence of tendon excursions corresponding to a desired movement. We perform several such sequences of tendon excursions experimentally and present the poses that result using motion capture. We also demonstrate executing several types of grasps on an underactuated robotic hand that incorporates this finger design.

While fish use continuous and flexible bodies to propel themselves, fish robots are often made from interconnected segments. How many segments do robots need to represent fish movements accurately? We propose a new method to automatically determine parsimonious robot models from actual fish data. We first identify key bending points (i.e., joint positions) along the body and then study the concerted movement of the segments so that the difference between actual fish and modelled bending kinematics is minimized. To demonstrate the utility of our method, we analyse the steady swimming kinematics of 10 morphologically distinct fish species. Broadly classified as sub-carangiform (e.g., rainbow trout) and carangiform (e.g., crevalle jack) swimmers, these species exhibit variations in the way they undulate when traditional parameters (including head and tail beat amplitudes, body wavelength and maximum curvature along the body) are considered. We show that five segments are sufficient to describe the kinematics with at least 99% accuracy. For optimal performance, segments should progressively get shorter towards the tail. We also show that locations where bending moments are applied vary among species, possibly because of differences in morphology. More specifically, we find that wider fish have shorter head segments. We discover that once bending points are factored in, the kinematics differences observed in these species collapse into a single undulatory pattern. The amplitude and timing of how body segments move entirely depend on their respective joint positions along the body. Head and body segments are also coupled in a timely manner, which depends on the position of the most anterior joint. Our findings provide a mechanistic understanding of how morphology relates to kinematics and highlight the importance of head control, which is often overlooked in current robot designs.

Certain animal species use the Earth's magnetic field (i.e. magnetoreception) in conjunction with other sensory modalities to navigate long distances. It is hypothesized that several animals use combinations of magnetic inclination and intensity as unique signatures for localization, enabling migration without a pre-surveyed map. However, it is unknown how animals use magnetic signatures to generate guidance commands, and the extent to which species-specific capabilities and environmental factors affect a given strategy's efficacy or deterioration. Understanding animal magnetoreception can aid in developing better engineered navigation systems that are less reliant on satellites, which are expensive and can become unreliable or unavailable under a variety of circumstances. Building on previous studies, we implement an agent-based computer simulation that uses two variants of a magnetic signature-based navigation strategy. The strategy can successfully migrate to eight specified goal points in an environment that resembles the northern Atlantic ocean. In particular, one variant reaches all goal points with faster ocean current velocities, while the other variant reaches all goal points with slower ocean current velocities. We also employ dynamic systems tools to examine the stability of the strategy as a proxy for whether it is guaranteed to succeed. The findings demonstrate the efficacy of the strategy and can help in the development of new navigation technologies that are less reliant on satellites and pre-surveyed maps.

In order to increase the compatibility between underwater robots and the underwater environment and inspired by the coconut octopus's underwater bipedal walking, a method was proposed for bipedal walking for an underwater soft robot based on a spring-loaded inverted pendulum (SLIP) model. Using the characteristics of octopus tentacles rolling on the ground, a wrist arm was designed using the cable-driven method, and an underwater SLIP bipedal walking model was established, which makes an underwater soft robot more suitable for moving on uneven ground. An underwater bipedal walking soft robot based on coconut octopus was then designed, and a machine vision algorithm was used to extract the motion information for analysis. Experimental analysis shows that the underwater bipedal walking robot can achieve an average speed of 6.48 cm s⁻¹, and the maximum instantaneous speed can reach 8.14 cm s⁻¹.

We investigate the influence of smooth and ribletted shark skin on a turbulent boundary layer flow. Through laser Doppler anemometry (LDA) the role of riblets in combination with the shark skin denticle is established for the first time. Our results show that smooth denticles behave like a typical rough surface when exposed to an attached boundary layer. Drag is increased for the full range of tested dimensionless denticle widths, w⁺ ≈ 25–80, where w⁺ is the denticle width, w, scaled by the friction velocity, u_τ, and the kinematic viscosity, ν. However, when riblets are added to the denticle crown we demonstrate there is a significant reduction in drag, relative to the smooth denticles. We obtain a modest maximum drag reduction of 2% for the ribletted denticles when compared to the flat plate, but when compared to the smooth denticles the difference in drag is in excess of 20% for w⁺ ≈ 80. This study enables a new conclusion that riblets have evolved as a mechanism to reduce or eliminate the skin friction increase due to the presence of scales (denticles). The combination of scales and riblets is hydrodynamically efficient in terms of skin-friction drag, while also acting to maintain flow attachment, and providing the other advantages associated with scales, e.g. anti-fouling, abrasion resistance, and defence against parasites.

Stomatopods are creatures that have a unique ability to manipulate their environment by detecting polarized light for finding prey, choosing habitat, and navigation. In this study, based on the concept of polarization distance proposed by Martin J et al 2014 [Proc. R. Soc. B281, 20131632], we have analyzed several multi-channel polarization distance models. The simulation and experimental results revealed that compared to other models, a four-channel polarization distance model can significantly enhance the contrast between the target and the background, and it exhibits excellent performance in terms of scene discrimination capability and robustness to noise. The structure and signal processing method of this model are inspired by biological polarization vision such as that of mantis shrimps. According to this method, a polarization-vision neural network is simulated with four-orientation receptor information as the input, and the network connections are realized in a cascaded order. The target–background contrast enhancement method based on this model has wide application prospects in the field of camouflage removal and target detection.

The numerical investigation of 2D insect wing kinematics in an inclined stroke plane is carried out using an immersed boundary solver. The effect of vortex shedding and dipole jet on the vertical force generation by the flapping wing due to change in the stroke plane angle is investigated in the vicinity of the ground. The results of instantaneous force and vorticity contours reveal the underlying lift enhancement mechanisms for the inclined stroke plane flapping wing. Moreover, they aid in the understanding of the wake-ground interaction and the associated shear layers. The calculated average vertical force delineates different force trends for the inclined stroke plane flapping near the ground. Furthermore, the dipole jet patterns are analyzed for different heights. These patterns are found to be a better tool to assess the kinematics for the vertical force enhancement and reduction, especially at intermediate heights. Vertical force enhancement is the critical parameter in the design of the micro aerial vehicle (MAV). Through this study, it is certain that the dipole jet has the potential to be used as a lift modification mechanism in MAVs. In summary, the study gives a holistic view of the physics of the inclined plane kinematics near the ground and serves as the basis for the design of MAVs.

Bird flight involves complicated wing kinematics, especially during hovering flight. The detailed aerodynamic effects of wings with higher degrees of freedom (DOFs) remain to be further investigated. Therefore, we designed a novel multiarticulate flapping-wing robot with five DOFs on each wing. Using this robot we aimed to investigate the more complicated wing kinematics of birds, which are usually difficult to test and analyze. In this study the robot was programmed to mimic the previously observed hovering motion of passerines, and force measurements and particle image velocimetry experiments. We experimented with two different wing-folding amplitudes: one with a larger folding amplitude, similar to that of real passerines, and one with only half the amplitude. The robot kinematics were verified utilizing direct linear transformation, which confirmed that the wing trajectories had an acceptable correlation with the desired motion. According to the lift force measurements, four phases of the wingbeat cycle were characterized and elaborated through camera images and flow visualization. We found that the reduction in folding amplitude caused a higher negative force during upstrokes and also induced a greater positive force at the initial downstroke through 'wake capture'. This could increase the vertical oscillation while hovering despite a minor increase in average force production. This phenomenon was not observed during forward flight in previous studies. Our results provide a critical understanding of the effect of wing folding which is required for designing the wing kinematics of future advanced flapping-wing micro aerial vehicles.

Soil penetration is an energy-intensive process that is common in both nature and civil infrastructure applications. Many human construction activities involve soil penetration that is typically accomplished through impact-driving, pushing against a reaction mass, excavating, or vibrating using large equipment. This paper presents a numerical investigation into the self-penetration process of a probe that uses an 'anchor–tip' burrowing strategy with the goal of extending the mechanics-based understanding of burrower–soil interactions at the physical dimensions and stress levels relevant for civil infrastructure applications. Self-penetration is defined here as the ability of a probe to generate enough anchorage forces to overcome the soil penetration resistance and advance the probe tip to greater depths. 3D Discrete element modeling simulations are employed to understand the self-penetration process of an idealized probe in noncohesive soil along with the interactions between the probe's anchor and tip. The results indicate that self-penetration conditions improve with simulated soil depth, and favorable probe configurations for self-penetration include shorter anchor–tip distances, anchors with greater length and expansion magnitudes, and anchors with a greater friction coefficient. The results shed light on the scaling of burrowing forces across a range of soil depths relevant to civil infrastructure applications and provide design guidance for future self-penetrating probes.

While the collective movements of fish schools evading predators in nature are complex, they can be fundamentally represented by simplified mathematical models. Here we develop a numerical model, which considers self-propelled particles subject to phenomenological behavioural rules and the hydrodynamic interactions between individuals. We introduce a predator in this model, to study the spontaneous response of a group of simulated fish to the threat. A self-organized fish school with a milling pattern is considered, which was expected to be efficient to evade the threat of predators. Four different attack tactics are adopted by the predator. We find that the simulated fish form transiently smaller structures as some prey individuals split from the main group, but eventually they will re-organize, sometimes into sub groups when the simulated predator approaches the fish school unidirectionally or take a reciprocating action. As the predator is programmed to target the centroid, the school ends in a gradually enlarging circle. For the fourth tactic, as the predator chases its nearest prey, the fish school's response varies with the predator's delay factor. Moreover, the average speed of the group and the distance between individuals have also been studied, both demonstrating that the fish school is able to respond spontaneously to the predator's invasion. We demonstrate that the currently adopted model can predict prey–predator interactions.

Lessons about artificial sensor design may be taken from evolutionarily perfected physiological systems. Mechanosensory cells in human skin are exquisitely sensitive to gentle touch and enable us to distinguish objects of different stiffnesses and textures. These cells are embedded in soft epidermal layers of gel-like consistency. Reproducing these mechanosensing capabilities in new soft materials may lead to the development of adaptive mechanosensors which will further enhance the abilities of engineered membrane-based structures with bioinspired sensing strategies. This strategy is explored here using droplet interface bilayers embedded within a thermoreversible organogel. The interface between two lipid-coated aqueous inclusions contained within a soft polymeric matrix forms a lipid bilayer resembling the lipid matrix of cell membranes. These interfaces are functionalized with bacterial mechanosensitive channels (V23T MscL) which convert membrane tension into changes in membrane conductance, mimicking mechanosensitive channel activation in mammalian mechanosensory cells. The distortion of encapsulated adhered droplets by cyclical external forces are first explored using a finite element composite model illustrating the directional propagation of mechanical disturbances imposed by a piston. The model predicts that the orientation of the droplet pair forming the membrane relative to the direction of the compression plays a role in the membrane response. The directional dependence of mechanosensitive channel activation in response to gel compression is confirmed experimentally and shows that purely compressive perturbations normal to the interface invoke different channel activities as compared to shearing displacement along a plane of the membrane. The developed system containing specially positioned pairs of droplets functionalized with bacterial mechanosensitive channels and embedded in a gel creates a skin-inspired soft material with a directional response to mechanical perturbation.

An unsupervised machine learning strategy is developed to automatically cluster the vortex wakes of bio-inspired propulsors into groups of similar propulsive thrust and efficiency metrics. A pitching and heaving foil is simulated via computational fluid dynamics with 121 unique kinematics by varying the frequency, heaving amplitude, and pitching amplitude. A Reynolds averaged Navier–Stokes model is employed to simulate the flow over the oscillating foils at Re = 10⁶, computing the propulsive efficiency, thrust coefficient and the unsteady vorticity wake signature. Using a pairwise Pearson correlation it is found that the Strouhal number most strongly influences the thrust coefficient, whereas the relative angle of attack, defined by both the mid-stroke and maximum have the most significant impact on propulsive efficiency. Next, the various kinematics are automatically clustered into distinct groups exclusively using the vorticity footprint in the wake. A convolutional autoencoder is developed to reduce vortex wake images to their most significant features, and a k-means++ algorithm performs the clustering. The results are assessed by comparing clusters to a thrust versus propulsive efficiency map, which confirms that wakes of similar performance metrics are successfully clustered together. This automated clustering has the potential to identify complex vorticity patterns in the wake and modes of propulsion not easily discerned from traditional classification methods.

Objective. The use of diffusion magnetic resonance imaging (dMRI) opens the door to characterizing brain microstructure because water diffusion is anisotropic in axonal fibres in brain white matter and is sensitive to tissue microstructural changes. As dMRI becomes more sophisticated and microstructurally informative, it has become increasingly important to use a reference object (usually called an imaging phantom) for validation of dMRI. This study aims to develop axon-mimicking physical phantoms from biocopolymers and assess their feasibility for validating dMRI measurements. Approach. We employed a simple and one-step method—coaxial electrospinning—to prepare axon-mimicking hollow microfibres from polycaprolactone-b-polyethylene glycol (PCL-b-PEG) and poly(D, L-lactide-co-glycolic) acid (PLGA), and used them as building elements to create axon-mimicking phantoms. Electrospinning was firstly conducted using two types of PCL-b-PEG and two types of PLGA with different molecular weights in various solvents, with different polymer concentrations, for determining their spinnability. Polymer/solvent concentration combinations with good fibre spinnability were used as the shell material in the following co-electrospinning process in which the polyethylene oxide polymer was used as the core material. Following the microstructural characterization of both electrospun and co-electrospun fibres using optical and electron microscopy, two prototype phantoms were constructed from co-electrospun anisotropic hollow microfibres after inserting them into water-filled test tubes. Main results. Hollow microfibres that mimic the axon microstructure were successfully prepared from the appropriate core and shell material combinations. dMRI measurements of two phantoms on a 7 tesla (T) pre-clinical scanner revealed that diffusivity and anisotropy measurements are in the range of brain white matter. Significance. This feasibility study showed that co-electrospun PCL-b-PEG and PLGA microfibre-based axon-mimicking phantoms could be used in the validation of dMRI methods which seek to characterize white matter microstructure.

The unique morphological bases of human hands, which are distinct from other primates, endow them with excellent grasping and manipulative abilities. However, the lack of understanding of human hand morphology and its parametric features is a major obstacle in the scientific design of prosthetic hands. Existing designs of prosthetic hand morphologies mostly adopt engineering-based methods, which depend on human experience, direct measurements of human hands, or numerical simulation/optimization. This paper explores for the first time a science-driven design method for prosthetic hand morphology, aiming to facilitate the development of prosthetic hands with human-level dexterity. We first use human morphological, movement, and postural data to quantitatively cognize general morphological characteristics of human hands in static, dynamic, functional, and non-functional perspectives. Taking these cognitions as bases, we develop a method able to quickly transfer human morphological parameters to prosthetic hands and endow the prosthetic hands with great grasping/manipulative potential at the same time. We apply this method to the design of an advanced prosthetic hand (called X-hand II) embedded with compact actuating systems. The human-size prosthetic hand can reach wide grasping/manipulative ranges close to those of human hands, replicate various daily grasping types and even execute dexterous in-hand manipulation. This science-driven method may also inspire other artificial limb and bionic robot designs.

Stimuli-responsive actuating materials offer a promising way to power insect-scale robots, but a vast majority of these material systems are too soft for load bearing in different applications. While strategies for active stiffness control have been developed for humanoid-scale robots, for insect-scale counterparts for which compactness and functional complexity are essential requirements, these strategies are too bulky to be applicable. Here, we introduce a method whereby the same actuating material serves not only as the artificial muscles to power an insect-scale robot for load bearing, but also to increase the robot stiffness on-demand, by bending it to increase the second moment of area. This concept is biomimetically inspired by how insect wings stiffen themselves, and is realized here with manganese dioxide as a high-performing electrochemical actuating material printed on metallized polycarbonate films as the robot bodies. Using an open-electrodeposition printing method, the robots can be rapidly fabricated in one single step in ∼15 minutes, and they can be electrochemically actuated by a potential of ∼1 V to produce large bending of ∼500° in less than 5 s. With the stiffness enhancement method, fast (∼5 s) and reversible stiffness tuning with a theoretical increment by ∼4000 times is achieved in a micro-robotic arm at ultra-low potential input of ∼1 V, resulting in an improvement in load-bearing capability by about 4 times from ∼10 μN to ∼41 μN.

Crepuscular mosquitoes, which swarm in low light conditions, exhibit a range of adaptations including large aspect-ratio wings, high flapping frequencies and small stroke amplitudes that taken together, facilitate the generation of wing-tones that are well-suited for acoustic communication. In the current study, we employ computational aeroacoustic modeling to conduct a comparative study of wing-tone and flight efficiency in a mosquito (male Culex) and a similar sized flying insect: a fruit fly (Drosophila). Based on this analysis, we show that pound-for-pound, a mosquito generates wing-tones that are a factor of about 3.4 times more intense than a fruit fly, and the mosquito is more efficient by a factor of about 3.7 in converting mechanical power into acoustic power. The wing-tones for the mosquito are also more tilted in the forward direction, a characteristic that would be more conducive for acoustic signaling during a mate chase. The simulation data also shows that the specific power (mechanical power over mean lift) of the mosquito is nearly equal to that of the fruit fly, indicating that the adaptations that facilitate wing-tone based communication in mosquitoes, do not seem to compromise their flight efficiency.

Even though unmanned aerial vehicles (UAVs) are taking on more expansive roles in military and commercial applications, their adaptability and agility are still inferior to that of their biological counterparts like birds, especially at low and moderate Reynolds numbers. A system of aeroelastic devices used by birds, known as the covert feathers, has been considered as a natural flow-control device for mitigating flow separation, enhancing lift, and delaying stall. This study presents the effects of a covert-inspired flap on two airfoils with different stall characteristics at Reynolds numbers in the order of 10⁵, where small scale UAVs operate. Detailed experiments and simulations are used to investigate how the covert-inspired flap affects lift and drag on an airfoil that exhibits sharp or sudden stall (i.e. the NACA 2414 airfoil) and one that exhibits soft or gradual stall (i.e. an E387(A) airfoil). The effects of the flap chord-wise locations and deflection angles on lift and drag is investigated, through wind tunnel experiments, for two types of flaps namely, a freely-moving flap and a static flap. Results show that the static covert-inspired flap can delay stall by up to 5° and improve post-stall lift by up to 23%. However, the post-stall lift improvement characteristics and sensitivities are highly affected by the airfoil choice. For the soft stall airfoil (i.e. E387(A)), the stall onset delay is insensitive to changing the flap deflection angle, and the flap becomes ineffective when the flap location is changed. In contrast, for the sharp stall airfoil (i.e. NACA 2414), the post-stall lift improvements can be tuned using the flap deflection angle, and the flap remains effective over a wide range of chord-wise locations. Numerical studies reveal that the lift improvements are attributed to a step in the pressure distribution over the airfoil, which allows for lower pressures on the suction side upstream of the flap. The distinctions between the flap-induced lift enhancements on the soft and sharp stall airfoils suggest that the flap can be used as a tunable flow control device for the sharp stall airfoil, while for the soft stall airfoil, it can solely be used as a stall mitigation device that is either on or off.

This paper comprehensively investigates elastic and viscoelastic flexural wave propagation in structures that are inspired by the unique suture configurations present in a woodpecker's beak, in order to understand their ability to attenuate velocity amplitudes and wave speeds. Waveguides characterized by sinusoidal depth variations, both plain and variously graded along the length, mimicking the suture geometry, are considered in this work. Elastic and viscoelastic wave propagation analyses, along with prior static and free vibration studies, are carried out using a novel superconvergent finite element formulation. In elastic wave propagation analysis, firstly the attenuation characteristics are appraised in relation to the high amplitude and frequency waves of three different plain waveguides with differing depth profile orientations. This prompted us to next consider waveguides of hybrid configurations derived from them. Further, waveguides with lengthwise graded sinusoidal segments, as observed in nature, are studied for better wave attenuation properties compared to plain waveguides. This is followed by viscoelastic wave propagation analysis. Regarding the important role of the suture geometry, which is the focus of this work, the results from the elastic analyses revealed the nature of the reduction in wave speeds and amplitudes, both qualitatively and quantitatively, in such waveguides, and their dependence on the orientation and magnitude of the sinusoidal depth variation. Some waveguide configurations with remarkable wave attenuation characteristics, in terms of both wave speeds and amplitudes, are presented, along with their implications regarding impact mitigation applications.

With increasing ocular motility disorders affecting human eye movement, the need to understand the biomechanics of the human eye rises constantly. A robotic eye system that physically mimics the human eye can serve as a useful tool for biomedical researchers to obtain an intuitive understanding of the functions and defects of the extraocular muscles and the eye. This paper presents the design, modeling, and control of a two degree-of-freedom (2-DOF) robotic eye, driven by artificial muscles, in particular, made of super-coiled polymers (SCPs). Considering the highly nonlinear dynamics of the robotic eye system, this paper applies deep deterministic policy gradient (DDPG), a machine learning algorithm to solve the control design problem in foveation and smooth pursuit of the robotic eye. To the best of our knowledge, this paper presents the first modeling effort to establish the dynamics of a robotic eye driven by SCP actuators, as well as the first control design effort for robotic eyes using a DDPG-based control strategy. A linear quadratic regulator-type reward function is proposed to achieve a balance between system performances (convergence speed and tracking accuracy) and control efforts. Simulation results are presented to demonstrate the effectiveness of the proposed control strategy for the 2-DOF robotic eye.

Fish median fins are extremely diverse, but their function is not yet fully understood. Various biological studies on fish and engineering studies on flapping foils have revealed that there are hydrodynamic interactions between fins arranged in tandem and that these interactions can lead to improved performance by the posterior fin. This performance improvement is often driven by the augmentation of a leading-edge vortex on the trailing fin. Past experimental studies have necessarily simplified fish anatomy to enable more detailed engineering analyses, but such simplifications then do not capture the complexities of an undulating fish-like body with fins attached. We present a flexible fish-like robotic model that better represents the kinematics of swimming fishes while still being simple enough to examine a range of morphologies and motion patterns. We then create statistical models that predict the individual effects of each kinematic and morphological variable. Our results demonstrate that having fins arranged in tandem on an undulating body can lead to more steady production of thrust forces determined by the distance between the fins and their relative motion. We find that these same variables also affect swimming speed. Specifically, when swimming at high frequencies, self-propelled speed decreases by 12%–26% due to out of phase fin motion. Flow visualization reveals that variation within this range is caused in part by fin–fin flow interactions that affect leading edge vortices. Our results indicate that undulatory swimmers should optimize both the positioning and relative motion of their median fins in order to reduce force oscillations and improve overall performance while swimming.

This work presents our experimental studies on a trout-inspired multifunctional robotic fish as an underwater swimmer and energy harvester. Fiber-based flexible piezoelectric composites with interdigitated electrodes, specifically macro-fiber composite (MFC) structures, strike a balance between the deformation and actuation force capabilities to generate hydrodynamic propulsion without requiring additional mechanisms for motion amplification. A pair of MFC laminates bracketing a passive fin functions like artificial muscle when driven out of phase to expand and contract on each side to create bending. The trout-like robotic fish design explored in this work was tested for both unconstrained swimming in a quiescent water tank and under imposed flow in a water tunnel to estimate the maximum swimming speed, which exceeded 0.25 m s⁻¹, i.e., 0.8 body lengths per second. Hydrodynamic thrust characterization was also performed in a quiescent water setting, revealing that the fin can easily produce tens of mN of thrust, similar to its biological counterpart for comparable swimming speeds. Overall, the prototype presented here generates thrust levels higher than other smart material-based concepts (such as soft polymeric material-based actuators which provide large deformation but low force), while offering simple design, geometric scalability, and silent operation unlike motor-based robotic fish (which often use bulky actuators and complex mechanisms). Additionally, energy harvesting experiments were performed to convert flow-induced vibrations in the wake of a cylindrical bluff body (for different diameters) in a water tunnel. The shed vortex frequency range for a set of bluff body diameters covered the first vibration mode of the tail, yielding an average electrical power of 120 μW at resonance for a flow speed around 0.3 m s⁻¹ and a bluff body diameter of 28.6 mm. Such low-power electricity can find applications to power small sensors of the robotic fish in scenarios such as ecological monitoring, among others.

One of the biggest issues of the mechanical cylindrical joints is related to premature wear appearing. Application of bioinspiration principles in an engineering context taking advantage of smart solutions offered by nature in terms of kinematic joints could be a way of solving those problems. This work is focussed on joints of one degrees of freedom in rotation (revolute or ginglymus joints in biological terms), as this is one of the most common type of mechanical joints. This type of joints can be found in the elbow of some quadrupedal mammals. The articular morphology of the elbow of these animals differs in the presence/absence of a trochlear sulcus. In this study, bio-inspired mechanical joints based on these morphologies (with/without trochlear sulcus) were designed and numerically tested. Their load bearing performance was numerically analysed. This was done through contact simulations using the finite element method under different external loading conditions (axial load, radial load and turnover moment). Results showed that the tested morphologies behave differently in transmission of external mechanical loads. It was found that bio-inspired joints without trochlea sulcus showed to be more specialized in the bearing of turnover moments. Bio-inspired joints with trochlea sulcus are more suitable for supporting combined loads (axial and radial load and turnover moments). Learning about the natural rules of mechanical design can provide new insights to improve the design of current mechanical joints.

Certain bat species (family Rhinolophidae) dynamically deform their emission baffles (noseleaves) and reception baffles (pinnae) during echolocation. Prior research using numerical models, laboratory characterizations, and experiments with simple targets have suggested that this dynamics may manifest itself in time-variant echo signatures. Since the pronounced random nature of echoes from natural targets such as foliage has not been reflected in these experiments, we have collected a large number (>55 000) of foliage echoes outdoors with a sonar head that mimics the dynamic periphery in bats. The echo data was processed with a custom auditory processing model to create spike-based echo representations. Deep-learning classifiers were able to estimate the dynamic state of the periphery, i.e., static or dynamic, based on single echoes with accuracies of up to 80%. This suggests that the effects of the peripheral dynamics are present in the bat brains and could hence be used by the animals. The best classification performances were obtained for data obtained within a spatially confined area. Hence, if the bat brains suffer from the same generalization issues, they would have to have a way to adapt their neural echo processing to such local fluctuations to exploit the dynamic effects successfully.