Legged robots relying on dry adhesives for vertical climbing are required to preload their feet against the wall to increase contact surface area and consequently maximize adhesion force. Preloading a foot causes a redistribution of forces in the entire robot, including contact forces between the other feet and the wall. An inappropriate redistribution of these forces can cause irreparable detachment of the robot from the vertical surface. This paper investigates an optimal preloading and detaching strategy that minimizes energy consumption, while retaining safety, during locomotion on vertical surfaces. The gait of a six-legged robot is planned using a quasi-static model that takes into account both the structure of the robot and the characteristics of the adhesive material. The latter was modelled from experimental data collected for this paper. A constrained optimization routine is used, and its output is a sequence of optimal posture and motor torque set-points.

A versatile locomotion mechanism is introduced and experimentally verified. This mechanism comprises four rectangular wheels (legs) with rotational phase difference which enables the application of pressure to each contacting surface for securing it to the surface using bio-inspired or pressure-sensitive adhesives. In this mechanism, the adhesives are applied to two rigid plates attached to each wheel via hinges incorporating torsional springs. The springs force the plates back to their original position after the contact with the surface is lost in the course of locomotion. The wheels are made of low-modulus elastomers, and the pressure applied during contact is controlled by the elastic modulus, geometry and phase difference of wheels. This reliable adhesion system does not rely upon gravity for adhering to surfaces, and provides the locomotion mechanism with the ability to climb walls and transition from horizontal to vertical surfaces.

The aerodynamic interactions between the body and the wings of a model insect in forward flight and maneuvers are studied using the method of numerically solving the Navier-Stokes equations over moving overset grids. Three cases are con-sidered, including a complete insect, wing pair only and body only. By comparing the results of these cases, the interaction effect between the body and the wing pair can be identified. The changes in the force and moment coefficients of the wing pair due to the presence of the body are less than 4.5% of the mean vertical force coefficient of the model insect; the changes in the aero-dynamic force coefficients of the body due to the presence of the wings are less than 5.0% of the mean vertical force coefficient of the model insect. The results of this paper indicate that in studying the aerodynamics and flight dynamics of a flapping insect in forward flight or maneuver, separately computing (or measuring) the aerodynamic forces and moments on the wing pair and on the body could be a good approximation.

The configurations of dragonfly wings, including the corrugations of the chordwise cross-section, the microstructure of the longitudinal veins and membrane, were comprehensively investigated using the Environmental Scanning Electron Microscopy (ESEM). Based on the experimental results reported previously, the multi-scale and multi-dimensional models with different structural features of dragonfly wing were created, and the biological dynamic behaviors of wing models were discussed through the Finite Element Method (FEM). The results demonstrate that the effects of different structural features on dynamic behaviors of dragonfly wing such as natural frequency/modal, bending/torsional deformation, reaction force/torque are very significant. The corrugations of dragonfly wing along the chordwise can observably improve the flapping frequency because of the greater structural stiffness of wings. In updated model, the novel sandwich microstructure of the longitudinal veins re-markably improves the torsional deformation of dragonfly wing while it has a little effect on the flapping frequency and bending deformation. These integrated structural features can adjust the deformation of wing oneself, therefore the flow field around the wings can be controlled adaptively. The fact is that the flights of dragonfly wing with sandwich microstructure of longitudinal veins are more efficient and intelligent.

This paper presents the dynamic modeling of a flexible tail for a robotic fish. For this purpose firstly, the flexible tail was simplified as a slewing beam actuated by a driving moment. The governing equation of the flexible tail was derived by using the Euler-Bernoulli theory. In this equation, the resistive forces were estimated as a term analogous to viscous damping. Then, the modal analysis method was applied in order to derive an analytical solution of the governing equation, by which the relationship between the driving moment and the lateral movement of the flexible tail was described. Finally, simulations and experiments were carried out and the results were compared to verify the accuracy of the dynamic model. It was proved that the dynamic model of a fish robot with a flexible tail fin well explains the real behavior of robotic fish in underwater environment.

A bio-robot system refers to an animal equipped with Brain-Computer Interface (BCI), through which the outer stimulation is delivered directly into the animal’s brain to control its behaviors. The development of bio-robots suffers from the dependency on real-time guidance by human operators. Because of its inherent difficulties, there is no feasible method for automatic con-trolling of bio-robots yet. In this paper, we propose a new method to realize the automatic navigation for bio-robots. A General Regression Neural Network (GRNN) is adopted to analyze and model the controlling procedure of human operations. Com-paring to the traditional approaches with explicit controlling rules, our algorithm learns the controlling process and imitates the decision-making of human-beings to steer the rat-robot automatically. In real-time navigation experiments, our method suc-cessfully controls bio-robots to follow given paths automatically and precisely. This work would be significant for future ap-plications of bio-robots and provide a new way to realize hybrid intelligent systems with artificial intelligence and natural biological intelligence combined together.

Biomaterial scaffolds play an important role in maintaining the viability and biological functions of highly metabolic hepatocytes in liver tissue engineering. One of the major challenges involves building a complex microchannel network inside three-dimensional (3D) scaffolds for efficient mass transportation. Here we presented a biomimetic strategy to generate a mi-crochannel network within porous biomaterial scaffolds by mimicking the vascular tree of rat liver. The typical parameters of the blood vessels were incorporated into the biomimetic design of the microchannel network such as branching angle and diameter. Silk fibroin-gelatin scaffolds with biomimetic vascular tree were fabricated by combining micromolding, freeze drying and 3D rolling techniques. The relationship between the micro-channeled design and flow pattern was revealed by a flow experiment, which indicated that the scaffolds with biomimetic vascular tree exhibited unique capability in improving mass transportation inside the 3D scaffold. The 3D scaffolds, preseeded with primary hepatocytes, were dynamically cultured in a bioreactor system. The results confirmed that the pre-designed biomimetic microchannel network facilitated the generation and expansion of hepatocytes.

The electrode resolution of current retinal prostheses is still far from matching the densities of retinal neurons. Decreasing electrode diameter increases impedance levels thus deterring effective stimulation of neurons. One solution is to increase the surface roughness of electrodes, which can be done via nanoparticle coatings. This paper explores a Lattice Gas Model of the drying-mediated self-assembly of nanoparticle mixtures. The model includes representations for different types of nanoparti-cles, solvent, vapour, substrate and the energetic relationships between these elements. The dynamical aspect of the model is determined by energy minimization, stochastic fluctuations and physical constraints. The model attempts to unravel the rela-tionships between different experimental conditions (e.g. evaporation rate, substrate characteristics and solvent viscosity) and the surface roughness of resulting assemblies. Some of the main results include the facts that the assemblies formed by nanoparticles of different sizes can boost roughness in specific circumstances and that the optimized assemblies can exhibit walled or stalagmite structures. This study provides a set of simulation modelling experiments that if confirmed in the laboratory may result in new and useful materials.

The mechanical and frictional properties of different parts of the elytra of five species of beetle were measured using a nano-indenter and a micro-tribometer. The surface microstructures of the elytra were observed by optical microscopy and scanning white light interferometry. The surface microstructures of the elytra of all five species are characterized as non-smooth concavo-convex although specific morphological differences demonstrate the diversity of beetle elytra. Young’s modulus and the hardness of the elytral materials vary with the species of beetle and the sampling locations, ranging from 1.80 GPa to 12.44 GPa, and from 0.24 GPa to 0.75 GPa, respectively. In general, both the Young’s modulus and the hardness are lower in samples taken from the center of the elytra than those taken from other regions, which reflects the functional heterogeneity of biological material in the process of biological evolution. The elytra have very low friction coefficient, ranging from 0.037 to 0.079, which is related to their composition and morphology. Our measurements indicate that the surface texture and its mi-crostructural size of beetle elytra contribute to anti-friction effects.

Titanium alloy is one of the best materials for biomedical applications due to its superior biocompatibility, outstanding corrosion resistance, and low elastic modulus. However, the friction and wear behaviors of titanium alloys were sensitive to the environment including lubrication. In order to clarify the wear mechanism of titanium alloy under different lubrications including deionized water, physiological saline and bovine serum, the friction and wear tests were performed between Ti6Al4V plates and Si3N4 ball on a universal multi-functional tester. The friction and the wear rate of titanium alloy were measured under dry friction and three different lubrication conditions. The worn surfaces were examined by scanning electron microscopy. The results revealed that under the dry friction, the wear resistance of titanium alloy was the worst since the wear mechanism was mainly the combination of abrasive wear and oxidation wear. It was also found that Ti6Al4V alloy had low friction coefficient and wear rate under three lubrication conditions, and its wear mechanism was adhesive wear.

The lattice Boltzmann method was employed to simulate electroosmotic driven flow and Debye layer screening in con-ducting electrolyte around a porous structure with average size of 40 nm. The charge screening around the nanopores was investigated by solving the vector-superpositioned potential equilibrium distribution function and adding electro-kinetic force term to the evolution equation. In this intermediate case of moderate Debye length, the electrophoresis problem becomes complicated. The motion of the particles distorts the screening cloud, which becomes asymmetric, resulting in very complex interactions between the electrolyte, the screening cloud and the particle; but the Electroosmotic Flow (EOF) behaviour was still considered based on the Helmoholtz-Smoluchowski model with adaptation to fit nanoporous flow in the porous structure. In the present approach, the flow in the nanopores is directly modelled; the detailed flow information can be obtained by simplifying the repeated macrostructure. Due to the symmetry of the domain, the size of computational domain can be largely reduced by less repeated spherical nanoparticles. Each pore of the medium contains several lattice nodes on the simplified curved edges and potential gradients are produced by adjusting the zeta potential value. The velocity results for pressure-driven and EOF flows agree well with the analytical solutions and recent experimental results. In particular, the interface between solid particles and fluids, the influences of porosity, solid particle diameter, yield stress and electric parameters in EOF were investigated. The anti-adhesion effect of electroosmotic pumping effect was evaluated, and the pulsed DC was applied in order to enhance the performance of the electroosmotic pumping. The results demonstrate that the present lattice Boltzmann model is capable of modelling flow through nanoporous media at certain restrictions while some results deviate from the predictions based on the macroscopic theories.

Maximum Likelihood (ML) method has an excellent performance for Direction-Of-Arrival (DOA) estimation, but a mul-tidimensional nonlinear solution search is required which complicates the computation and prevents the method from practical use. To reduce the high computational burden of ML method and make it more suitable to engineering applications, we apply the Artificial Bee Colony (ABC) algorithm to maximize the likelihood function for DOA estimation. As a recently proposed bio-inspired computing algorithm, ABC algorithm is originally used to optimize multivariable functions by imitating the be-havior of bee colony finding excellent nectar sources in the nature environment. It offers an excellent alternative to the con-ventional methods in ML-DOA estimation. The performance of ABC-based ML and other popular meta-heuristic-based ML methods for DOA estimation are compared for various scenarios of convergence, Signal-to-Noise Ratio (SNR), and number of iterations. The computation loads of ABC-based ML and the conventional ML methods for DOA estimation are also investi-gated. Simulation results demonstrate that the proposed ABC based method is more efficient in computation and statistical performance than other ML-based DOA estimation methods.

This research aims to develop Wood Plastic Composites (WPCs) from rice hull and poly(vinyl chloride) (PVC). The in-fluences of the rice hull particle size and content on the mechanical properties and the visual appearance of the WPC decking board were investigated. The experimental results revealed that the impact strength tended to decrease with increasing rice hull content. The composites with larger particle sizes exhibited higher impact strength. Under tensile and flexure load, higher rice hull content induced greater modulus and ultimate strength when the rice hull was applied at less than 60 phr. Beyond this concentration, the modulus and the strength dropped due to the formation of rice hull agglomerates. The smaller particles of the milled rice hull, the greater tendency there was for them to act as a pigment to form a darker shade close that of the rice hull on the composite decking board. The larger particle sizes were 106 μm and beyond simply embedded in the white PVC matrix.

Mole rat (Scaptochirus moschatus), a soil-burrowing mammal, can efficiently dig soil using its fore claws. The profile curves of its claw toe provide excellent structure for digging. In this paper, a biomimetic stubble-cutting disc was designed by learning from the geometrical characteristics of the mole rat claw toes. To compare the structural strength and working effi-ciency of the biomimetic disc and the conventional stubble-cutting disc, three-dimensional (3D) models of the discs were built and numerical analyzed in ABAQUS. In the dynamic soil cutting model, soil was modeled as an elastic-plastic material with elastic parameters, including Young’s modulus, Poisson’s ratio and Drucker-Prager criterion, which were obtained from triaxial tests. A general contact algorithm was used to simulate the interaction between rotary disc and soil. In FEA models, for the combined action of normal and friction stresses, the stress on the biomimetic disc is 34.33 % lower than that of the conventional disc. For only the normal stress, the stress on the biomimetic disc is 22.64% lower than that on the conventional one. The magnitude of soil stress in biomimetic disc cutting model is 6.87% higher than that in conventional disc. The FEA results indicate that the biomimetic disc performs better in structural strength and cutting efficiency.