Table of contents

This paper aims to describe the disruptive potential that polymeric thin films have in the field of biohybrid devices and to review the recent efforts in this area. Thin (thickness  <  1 mm) and ultra-thin (thickness  <  1 µm) matrices possess a series of intriguing features, such as large surface area/volume ratio, high flexibility, chemical and physical surface tailorability, etc. This enables the fabrication of advanced bio/non-bio interfaces able to efficiently drive cell-material interactions, which are the key for optimizing biohybrid device performances. Thin films can thus represent suitable platforms on which living and artificial elements are coupled, with the aim of exploiting the unique features of living cells/tissues. This may allow to carry out certain tasks, not achievable with fully artificial technologies. In the paper, after a description of the desirable chemical/physical cues to be targeted and of the fabrication, functionalization and characterization procedures to be used for thin and ultra-thin films, the state-of-the-art of biohybrid microrobots based on micro/nano-membranes are described and discussed. The research efforts in this field are rather recent and they focus on: (1) self-beating cells (such as cardiomyocytes) able to induce a relatively large deformation of the underlying substrates, but affected by a limited controllability by external users; (2) skeletal muscle cells, more difficult to engineer in mature and functional contractile tissues, but featured by a higher controllability. In this context, the different materials used and the performances achieved are analyzed. Despite recent interesting advancements and signs of maturity of this research field, important scientific and technological steps are still needed. In the paper some possible future perspectives are described, mainly concerning thin film manipulation and assembly in multilayer 3D systems, new advanced materials to be used for the fabrication of thin films, cell engineering opportunities and modelling/computational efforts.

Marvelous vision based dynamic behaviors of insects and birds such as perching, landing, and obstacle avoidance have inspired scientists to propose the idea of time-to-contact, which is defined as the time for a moving observer to contact an object or surface if the current velocity is maintained. Since with only a vision sensor, time-to-contact can be directly estimated from consecutive images, it is widely used for a variety of robots to fulfill various tasks such as obstacle avoidance, docking, chasing, perching and landing. However, most of existing methods to estimate the time-to-contact need to extract and track features during the control process, which is time-consuming and cannot be applied to robots with limited computation power. In this paper, we adopt a featureless estimation method, extend this method to more general settings with angular velocities, and improve the estimation results using Kalman filtering. Further, we design an error based controller with gain scheduling strategy to control the motion of mobile robots. Experiments for both estimation and control are conducted using a customized mobile robot platform with low-cost embedded systems. Onboard experimental results demonstrate the effectiveness of the proposed approach, with the robot being controlled to successfully dock in front of a vertical wall. The estimation and control methods presented in this paper can be applied to computation-constrained miniature robots for agile locomotion such as landing, docking, or navigation.

Understanding active electrolocation in weakly electric fish remains a challenging issue. In this article we propose a mathematical formulation of this problem, in terms of partial differential equations. This allows us to detail two algorithms: one for localizing a target using the multi-frequency aspect of the signal, and another one for identifying the shape of this target. Shape recognition is designed in a machine learning point of view, and takes advantage of both the multi-frequency setup and the movement of the fish around its prey. Numerical simulations are shown for the computation of the electric field emitted and sensed by the fish; they are then used as an input for the two algorithms.

Biologically inspired robots with inherent softness and body compliance increasingly attract attention in the field of robotics. Aimed at solving existing problems with soft robots, regarding actuation technology and biological principles, this paper presents a soft bio-inspired annelid robot driven by dielectric elastomer actuators (DEAs) that can advance on flat rigid surfaces. The DEA, a kind of soft functional actuator, is designed and fabricated to mimic the axial elongation and differential friction of a single annelid body segment. Several (at least three) DEAs are connected together into a movable multi-segment robot. Bristles are attached at the bottom of some DEAs to achieve differential friction for imitating the setae of annelids. The annelid robot is controlled by periodic square waves, propagating from the posterior to the anterior, which imitate the peristaltic waves of annelids. Controlled by these waves, each DEA, one-by-one from tail to head, anchors to the ground by circumferential distention and pushes the front DEAs forward by axial elongation, enabling the robot to advance. Preliminary tests demonstrate that a 3-segment robot can reach an average speed of 5.3 mm s⁻¹ (1.871 body lengths min⁻¹) on flat rigid surfaces and can functionally mimic the locomotion of annelids. Compared to the existing robots that imitate terrestrial annelids our annelid robot shows advantages in terms of speed and bionics.

Electric fish are privileged animals for bio-inspiring man-built autonomous systems since they have a multimodal sense that allows underwater navigation, object classification and intraspecific communication. Although there are taxon dependent variations adapted to different environments, this multimodal system can be schematically described as having four main components: active electroreception, passive electroreception, lateral line sense and, proprioception. Amongst these sensory modalities, proprioception and electroreception show 'active' systems that extrct information carried by self generated forms of energy. This ensemble of four sensory modalities is present in African mormyriformes and American gymnotiformes. The convergent evolution of similar imaging, peripheral encoding, and central processing mechanisms suggests that these mechanisms may be the most suitable for dealing with electric images in the context of the other and self generated actions. This review deals with the way in which biological organisms address three of the problems that are faced when designing a bioinspired electroreceptive agent: (a) body shape, material and mobility, (b) peripheral encoding of electric images, and (c) early processing of electrosensory signals. Taking into account biological solutions I propose that the new generation of underwater agents should have electroreceptive arms, use complex peripheral sensors for encoding the images and cerebellum like architecture for image feature extraction and implementing sensory-motor transformations.

Flapping-wing micro air vehicles (FWMAVs) are a class of unmanned aircraft that imitate flight characteristics of natural organisms such as birds, bats, and insects, in order to achieve maximum flight efficiency and manoeuvrability. Designing proper mechanisms for flapping transmission is an extremely important aspect for FWMAVs. Compliant transmission mechanisms have been considered as an alternative to rigid transmission systems due to their lower the number of parts, thereby reducing the total weight, lower energy loss thanks to little or practically no friction among parts, and at the same time, being able to store and release mechanical power during the flapping cycle. In this paper, the state-of-the-art research in this field is dealt upon, highlighting open challenges and research topics. An optimization method for designing compliant transmission mechanisms inspired by the thoraxes of insects is also introduced.

Robust and efficient target-tracking algorithms embedded on moving platforms, are a requirement for many computer vision and robotic applications. However, deployment of a real-time system is challenging, even with the computational power of modern hardware. As inspiration, we look to biological lightweight solutions–lightweight and low-powered flying insects. For example, dragonflies pursue prey and mates within cluttered, natural environments, deftly selecting their target amidst swarms. In our laboratory, we study the physiology and morphology of dragonfly 'small target motion detector' neurons likely to underlie this pursuit behaviour. Here we describe our insect-inspired tracking model derived from these data and compare its efficacy and efficiency with state-of-the-art engineering models. For model inputs, we use both publicly available video sequences, as well as our own task-specific dataset (small targets embedded within natural scenes). In the context of the tracking problem, we describe differences in object statistics within the video sequences. For the general dataset, our model often locks on to small components of larger objects, tracking these moving features. When input imagery includes small moving targets, for which our highly nonlinear filtering is matched, the robustness outperforms state-of-the-art trackers. In all scenarios, our insect-inspired tracker runs at least twice the speed of the comparison algorithms.

We introduce an octopus-inspired, underwater, soft-bodied robot capable of performing waterborne pulsed-jet propulsion and benthic legged-locomotion. This vehicle consists for as much as 80% of its volume of rubber-like materials so that structural flexibility is exploited as a key element during both modes of locomotion. The high bodily softness, the unconventional morphology and the non-stationary nature of its propulsion mechanisms require dynamic characterization of this robot to be dealt with by ad hoc techniques. We perform parameter identification by resorting to a hybrid optimization approach where the characterization of the dual ambulatory strategies of the robot is performed in a segregated fashion. A least squares-based method coupled with a genetic algorithm-based method is employed for the swimming and the crawling phases, respectively. The outcomes bring evidence that compartmentalized parameter identification represents a viable protocol for multi-modal vehicles characterization. However, the use of static thrust recordings as the input signal in the dynamic determination of shape-changing self-propelled vehicles is responsible for the critical underestimation of the quadratic drag coefficient.

This study integrates high-speed photogrammetry, 3D surface reconstruction, and computational fluid dynamics to explore a dragonfly (Erythemis Simplicicollis) in free flight. Asymmetric wing kinematics and the associated aerodynamic characteristics of a turning dragonfly are analyzed in detail. Quantitative measurements of wing kinematics show that compared to the outer wings, the inner wings sweep more slowly with a higher angle of attack during the downstroke, whereas they flap faster with a lower angle of attack during the upstroke. The inner–outer asymmetries of wing deviations result in an oval wingtip trajectory for the inner wings and a figure-eight wingtip trajectory for the outer wings. Unsteady aerodynamics calculations indicate significantly asymmetrical force production between the inner and outer wings, especially for the forewings. Specifically, the magnitude of the drag force on the inner forewing is approximately 2.8 times greater than that on the outer forewing during the downstroke. In the upstroke, the outer forewing generates approximately 1.9 times greater peak thrust than the inner forewing. To keep the body aloft, the forewings contribute approximately 64% of the total lift, whereas the hindwings provide 36%. The effect of forewing-hindwing interaction on the aerodynamic performance is also examined. It is found that the hindwings can benefit from this interaction by decreasing power consumption by 13% without sacrificing force generation.

There are disadvantages to existing damping knee prostheses which cause an asymmetric gait and higher metabolic cost during level walking compared to non-amputees. Most existing active knee prostheses which could benefit the amputees use a significant amount of energy and require a considerable motor. In this work, a novel semi-active actuator with a lockable parallel spring for a prosthetic knee joint has been developed and tested. This actuator is able to provide an approximation of the behavior of a healthy knee during most of the gait cycle of level walking. This actuator is expanded with a series-elastic actuator to mimic the full gait cycle and enable its use in other functional tasks like stair climbing and sit-to-stance. The proposed novel actuator reduces the energy consumption for the same trajectory with respect to a compliant or directly-driven prosthetic active knee joint and improves the approximation of healthy knee behavior during level walking compared to passive or variable damping knee prostheses.

In this work, we address human-like motor planning in redundant manipulators. Specifically, we want to capture postural synergies such as Donders' law, experimentally observed in humans during kinematically redundant tasks, and infer a minimal set of parameters to implement similar postural synergies in a kinematic model. For the model itself, although the focus of this paper is to solve redundancy by implementing postural strategies derived from experimental data, we also want to ensure that such postural control strategies do not interfere with other possible forms of motion control (in the task-space), i.e. solving the posture/movement problem.

The redundancy problem is framed as a constrained optimization problem, traditionally solved via the method of Lagrange multipliers. The posture/movement problem can be tackled via the separation principle which, derived from experimental evidence, posits that the brain processes static torques (i.e. posture-dependent, such as gravitational torques) separately from dynamic torques (i.e. velocity-dependent). The separation principle has traditionally been applied at a joint torque level. Our main contribution is to apply the separation principle to Lagrange multipliers, which act as task-space force fields, leading to a task-space separation principle. In this way, we can separate postural control (implementing Donders' law) from various types of tasks-space movement planners.

As an example, the proposed framework is applied to the (redundant) task of pointing with the human wrist. Nonlinear inverse optimization (NIO) is used to fit the model parameters and to capture motor strategies displayed by six human subjects during pointing tasks. The novelty of our NIO approach is that (i) the fitted motor strategy, rather than raw data, is used to filter and down-sample human behaviours; (ii) our framework is used to efficiently simulate model behaviour iteratively, until it converges towards the experimental human strategies.

This paper focuses on design, fabrication and characterization of a biomimetic, compact, low-cost and lightweight 3D printed humanoid hand (TCP Hand) that is actuated by twisted and coiled polymeric (TCP) artificial muscles. The TCP muscles were recently introduced and provided unprecedented strain, mechanical work, and lifecycle (Haines et al 2014 Science343 868–72). The five-fingered humanoid hand is under-actuated and has 16 degrees of freedom (DOF) in total (15 for fingers and 1 at the palm). In the under-actuated hand designs, a single actuator provides coupled motions at the phalanges of each finger. Two different designs are presented along with the essential elements consisting of actuators, springs, tendons and guide systems. Experiments were conducted to investigate the performance of the TCP muscles in response to the power input (power magnitude, type of wave form such as pulsed or square wave, and pulse duration) and the resulting actuation stroke and force generation. A kinematic model of the flexor tendons was developed to simulate the flexion motion and compare with experimental results. For fast finger movements, short high-power pulses were employed. Finally, we demonstrated the grasping of various objects using the humanoid TCP hand showing an array of functions similar to a natural hand.

Over many decades the biological surfaces of aquatic swimmers have been studied for their potential as drag reducing surfaces. The hydrodynamic benefit of riblets, or grooves embedded parallel to the flow which appear on surfaces such as shark skin, have been well documented. However the skin of dolphins is embedded with sinusoidal grooves that run perpendicular or transverse to the flow over their bodies. It is theorized that the transverse grooves present on dolphin skin trap vortices between them, creating a partial slip condition over the surface and inducing turbulence augmentation in the boundary layer, thus acting as a potential mechanism to reduce flow separation and thus pressure drag. In an attempt to test this hypothesis and study these effects, an adverse pressure gradient was induced above a flat plate resulting in a controlled region of flow separation occurring within a tripped, turbulent boundary layer. Small transverse grooves of both rectangular and sinusoidal shape were 3D printed and mounted to the plate to measure their effect on the boundary layer flow. The results were compared to a flat plate without grooves using digital particle image velocimetry (DPIV). The strength of the adverse pressure gradient was varied, and the observed control in flow separation and other effects upon the boundary layer are discussed.

Inspired by the relationship between leg compliance and jumping performance in the false stick insect, this paper describes how variations in leg compliance and jumping direction affect the performance of a flea-inspired jumping mechanism. The amount of energy lost during jumping was determined by examining the ratio of kinetic energy to input energy (also called conversion efficiency). Leg compliance is modeled based on the compliant mechanics to determine energy transfer during jumping and determined the optimum degree of leg compliance for maximizing performance. Jumping experiments are then performed using six different legs with progressively greater degrees of stiffness and three different jumping directions. The experiments show that conversion efficiency decreases by approximately 3–5% as leg stiffness increases, compared to the optimal case. In the most compliant legs (i.e. stiffness of 0.0338 Nm rad⁻¹ or less), conversion efficiency rapidly drops to near 0% because the leg bends so much that it cannot support the thrusting force. The optimal conversion efficiency tends to increase when the mechanism jumps vertically owing to reduced slippage and increased ground reaction force. These investigations show that optimizing leg compliance can improve the performance of a jumping robot by up to 5% by enabling more of the initially stored energy in the leg to be used. This finding will likely prove helpful for choosing the leg stiffness for a small-scale jumping robot.

Modern cars are equipped with both active and passive sensor systems that can detect potential collisions. In contrast, locusts avoid collisions solely by responding to certain visual cues that are associated with object looming. In neurophysiological experiments, I investigated the possibility that the 'collision-detector neurons' of locusts respond to impending collisions in films recorded with dashboard cameras of fast driving cars. In a complementary modelling approach, I developed a simple algorithm to reproduce the neuronal response that was recorded during object approach.

Instead of applying elaborate algorithms that factored in object recognition and optic flow discrimination, I tested the hypothesis that motion detection restricted to a 'danger zone', in which frontal collisions on the motorways are most likely, is sufficient to estimate the risk of a collision. Furthermore, I investigated whether local motion vectors, obtained from the differential excitation of simulated direction-selective networks, could be used to predict evasive steering maneuvers and prevent undesired responses to motion artifacts.

The results of the study demonstrate that the risk of impending collisions in real traffic scenes is mirrored in the excitation of the collision-detecting neuron (DCMD) of locusts. The modelling approach was able to reproduce this neuronal response even when the vehicle was driving at high speeds and image resolution was low (about 200  ×  100 pixels). Furthermore, evasive maneuvers that involved changing the steering direction and steering force could be planned by comparing the differences in the overall excitation levels of the simulated right and left direction-selective networks. Additionally, it was possible to suppress undesired responses of the algorithm to translatory movements, camera shake and ground shadows by evaluating local motion vectors. These estimated collision risk values and evasive steering vectors could be used as input for a driving assistant, converting the first into braking force and the latter into steering responses to avoid collisions. Since many processing steps were computed on the level of pixels and involved elements of direction-selective networks, this algorithm can be implemented in hardware so that parallel computations enhance the processing speed significantly.

The growth of leading-edge vortices (LEV) on analogous flapping and rotating profiles has been investigated experimentally. Three time-varying cases were considered: a two-dimensional reference case with a spanwise-uniform angle-of-attack variation α; a case with increasing α towards the profile tip (similar to flapping flyers); and a case with increasing α towards the profile root (similar to rotor blades experiencing an axial gust). It has been shown that the time-varying spanwise angle-of-attack gradient produces a vorticity gradient, which, in combination with spanwise flow, results in a redistribution of circulation along the profile. Specifically, when replicating the angle-of-attack gradient characteristic of a rotor experiencing an axial gust, the spanwise-vorticity gradient is aligned such that circulation increases within the measurement domain. This in turn increases the local LEV growth rate, which is suggestive of force augmentation on the blade. Reversing the relative alignment of the spanwise-vorticity gradient and spanwise flow, thereby replicating that arrangement found in a flapping flyer, was found to reduce local circulation. From this, we can conclude that spanwise flow can be arranged to vary LEV growth to prolong lift augmentation and reduce the unsteadiness of cyclic loads.

Here we investigate the mechanical properties and structural design of the pericarp of the green coconut (Cocos nucifera L.). The pericarp showed excellent impact characteristics, and mechanical tests of its individual components revealed gradients in stiffness, strength and elongation at break from the outer to the inner layer of the pericarp. In order to understand more about the potential effect of such gradients on 'bulk' material properties, we designed simple, graded, cellulose fibre-reinforced polylactide (PLA) composites by stacking layers reinforced with fibres of different mechanical properties. Tensile properties of the graded composites were largely determined by the 'weakest' fibre, irrespective of the fibre distribution. However, a graded design led to pronounced asymmetric bending and impact properties. Bio-inspired, asymmetrically graded composites showed a flexural strength and modulus comparable to that of the strongest reference samples, but the elongation at maximum load was dependent on the specimen orientation. The impact strength of the graded composites showed a similar orientation-dependence, and peak values exceeded the impact strength of a non-graded reference composite containing identical fibre fractions by up to a factor of three. In combination, our results show that an asymmetric, systematic variation of fibre properties can successfully combine desirable properties of different fibre types, suggesting new routes for the development of high-performance composites, and improving our understanding of the structure-function relationship of the coconut pericarp.

Flapping wing micro air vehicles (MAVs) take inspiration from natural fliers, such as insects and hummingbirds. Existing designs manage to mimic the wing motion of natural fliers to a certain extent; nevertheless, differences will always exist due to completely different building blocks of biological and man-made systems. The same holds true for the design of the wings themselves, as biological and engineering materials differ significantly. This paper presents results of experimental optimization of wing shape of a flexible wing for a hummingbird-sized flapping wing MAV. During the experiments we varied the wing 'slackness' (defined by a camber angle), the wing shape (determined by the aspect and taper ratios) and the surface area. Apart from the generated lift, we also evaluated the overall power efficiency of the flapping wing MAV achieved with the various wing design. The results indicate that especially the camber angle and aspect ratio have a critical impact on the force production and efficiency. The best performance was obtained with a wing of trapezoidal shape with a straight leading edge and an aspect ratio of 9.3, both parameters being very similar to a typical hummingbird wing. Finally, the wing performance was demonstrated by a lift-off of a 17.2 g flapping wing robot.

Using a fluid-structure interaction model, we study the effect of ray stiffness distribution on the deformation and performance of a caudal fin. By prescribing a simple swaying motion, our results show that through passive structural deformation alone it is possible to reproduce some complicated fin movements (e.g. the cup and 'W'-shape deformations) observed in real fish. Moreover, it has been numerically shown that, compared with a fin with uniform ray stiffness, at the same (average) ray stiffness fins with nonuniform stiffness distribution may achieve further performance enhancement, e.g. increase in propulsion efficiency and decrease in lateral force generation. This is attributed to spanwise deformations caused by phase differences between different rays.

The development of programmable self-shaping materials enables the onset of new and innovative functionalities in many application fields. Commonly, shape adaptation is achieved by exploiting diffusion-driven swelling or nano-scale phase transition, limiting the change of shape to slow motion predominantly determined by the environmental conditions and/or the materials specificity. To address these shortcomings, we report shape adaptable programmable shells that undergo morphing via a snap-through mechanism inspired by the Dionaea muscipula leaf, known as the Venus fly trap. The presented shells are composite materials made of epoxy reinforced by stiff anisotropic alumina micro-platelets oriented in specific directions. By tailoring the microstructure via magnetically-driven alignment of the platelets, we locally tune the pre-strain and stiffness anisotropy of the composite. This novel approach enables the fabrication of complex shapes showing non-orthotropic curvatures and stiffness gradients, radically extending the design space when compared to conventional long-fibre reinforced multi-stable composites. The rare combination of large stresses, short actuation times and complex shapes, results in hinge-free artificial shape adaptable systems with large design freedom for a variety of morphing applications.

Gliding flight—moving horizontally downward through the air without power—has evolved in a broad diversity of taxa and serves numerous ecologically relevant functions such as predator escape, expanding foraging locations, and finding mates, and has been suggested as an evolutionary pathway to powered flight. Historically, gliding has been conceptualized using the idealized conditions of equilibrium, in which the net aerodynamic force on the glider balances its weight. While this assumption is appealing for its simplicity, recent studies of glide trajectories have shown that equilibrium gliding is not the norm for most species. Furthermore, equilibrium theory neglects the aerodynamic differences between species, as well as how a glider can modify its glide path using control. To investigate non-equilibrium glide behavior, we developed a reduced-order model of gliding that accounts for self-similarity in the equations of motion, such that the lift and drag characteristics alone determine the glide trajectory. From analysis of velocity polar diagrams of horizontal and vertical velocity from several gliding species, we find that pitch angle, the angle between the horizontal and chord line, is a control parameter that can be exploited to modulate glide angle and glide speed. Varying pitch results in changing locations of equilibrium glide configurations in the velocity polar diagram that govern passive glide dynamics. Such analyses provide a new mechanism of interspecies comparison and tools to understand experimentally-measured kinematics data and theory. In addition, this analysis suggests that the lift and drag characteristics of aerial and aquatic autonomous gliders can be engineered to passively alter glide trajectories with minimal control effort.

Additive manufacturing technologies offer new ways to fabricate cellular materials with composite cell walls, mimicking the structure and mechanical properties of woods. However, materials limitations and a lack of design tools have confined the usefulness of 3D printed cellular materials. We develop new carbon fiber reinforced, epoxy inks for 3D printing which result in printed materials with longitudinal Young's modulus up to 57 GPa (exceeding the longitudinal modulus of wood cell wall material). To guide the design of hierarchical cellular materials, we developed a parameterized, multi-scale, finite element model. Computational homogenization based on finite element simulations at multiple length scales is employed to obtain the elastic properties of the material at multiple length scales. Parameters affecting the elastic response of cellular composites, such as the volume fraction, orientation distribution, and aspect ratio of fibers within the cell walls as well as the cell geometry and relative density are included in the model. To validate the model, experiments are conducted on both solid carbon fiber/epoxy composites and cellular structures made from them, showing excellent agreement with computational multi-scale model predictions, both at the cell-wall and at the cellular-structure levels. Using the model, cellular structures are designed and experimentally shown to achieve a specific stiffness nearly as high as that observed in balsa wood. The good agreement between the multi-scale model predictions and experimental data provides confidence in the practical utility of this model as a tool for designing novel 3D cellular composites with unprecedented specific elastic properties.

While insect grooming has been observed and documented for over one hundred years, we present the first quantitative analysis of this highly dynamic process. Pollinating insects, like honey bees, purposely cover themselves with millions of pollen particles that, if left ungroomed, would make sensing and controlled flight difficult. How do they get clean? We show that the hairs on insect eyes are tuned to the pollen they collect; namely, the hairs are spaced so that they suspend pollen above the body for easy removal by the forelegs. In turn, hair spacing on the foreleg dictates the leg's ability to store the pollen removed during each swipe. In tests with wax-covered honey bees, we show that hairy forelegs are necessary for pollen removal. Moreover, the viscous fluid found on the surface of pollen grains, or pollenkitt, greatly enhances adhesion. We find that bees accumulate twice as much pollen if pollenkitt is present. This study may help further understand pollination, as well as inform designs for mechanically-sensitive functional surfaces with micro- and nano-structures that are easier to keep clean.