Hybrid metaheuristic algorithms play a prominent role in improving algorithms' searchability by combining each algorithm's advantages and minimizing any substantial shortcomings. The Quantum-based Avian Navigation Optimizer Algorithm (QANA) is a recent metaheuristic algorithm inspired by the navigation behavior of migratory birds. Different experimental results show that QANA is a competitive and applicable algorithm in different optimization fields. However, it suffers from shortcomings such as low solution quality and premature convergence when tackling some complex problems. Therefore, instead of proposing a new algorithm to solve these weaknesses, we use the advantages of the bonobo optimizer to improve global search capability and mitigate premature convergence of the original QANA. The effectiveness of the proposed Hybrid Quantum-based Avian Navigation Optimizer Algorithm (HQANA) is assessed on 29 test functions of the CEC 2018 benchmark test suite with different dimensions, 30, 50, and 100. The results are then statistically investigated by the Friedman test and compared with the results of eight well-known optimization algorithms, including PSO, KH, GWO, WOA, CSA, HOA, BO, and QANA. Ultimately, five constrained engineering optimization problems from the latest test suite, CEC 2020 are used to assess the applicability of HQANA to solve complex real-world engineering optimization problems. The experimental and statistical findings prove that the proposed HQANA algorithm is superior to the comparative algorithms.

Pacinian corpuscle is a tactile receptor that responds to high-frequency (20–1000 Hz) vibration and has high-pass filtering and mechanical signal amplification functions. It is the main receptor of vibration tactility closely related to fine touch sensation, which is the ability to perceive and localize objects’ shape, texture, and size. Currently, it is still difficult to measure and calculate the friction generated by robots grasping objects. The resolution of touch and vibration sensors cannot satisfy the demand for understanding tribological behavior. The simulation of Pacinian corpuscles’ structure and replication of its key functions will bring richer touch information to robots. In this review article, the structure and functions of Pacinian corpuscles are summarized from the internal structure of a single Pacinian corpuscle and the spatial distribution of multiple Pacinian corpuscles. Then, theoretical models and research on the bionics design of Pacinian corpuscles are introduced based on the three reception processes of Pacinian corpuscles: mechanical transmission, electromechanical transduction, and neural excitation. Finally, the bottlenecks of current research on the simulation of Pacinian corpuscles are summarized, followed by the proposal of research ideas on the simulation of Pacinian corpuscles.

Excessive vibration in civil and mechanical systems can lead to structural damage or harmful noise. Structural vibration can be mitigated by reducing the energy of the vibration source or by isolating the external disturbance from the target structure. Depending on the tunability and power consumption of the system, existing vibration control strategies are divided into active, passive and semi-active types, providing a more stable and efficient solution for vibration control. However, conventional damping structures have difficulty in meeting the requirements of wide frequency range and high precision damping under complex operating conditions. Therefore, the design of efficient damping structures is one of the key challenges in the development of vibration control technology. Organisms have evolved over millions of years to effectively damp vibrations through special structures and composite materials to ensure their survival. Opening up damping vibration isolation technology from a bionic perspective can meet the frequency requirements of vibration damping and guarantee higher output accuracy of machinery. This review summarizes the basic principles of vibration control and analyses the vibration control strategies for different damping materials and damping structures. Meanwhile, various models of bio-damped structures are outlined. Moreover, the current status and recent progress of research on bionic damped structures based on bio-vibration control strategies are discussed. Finally, new perspectives on future developments in the field of bionic damped vibration control techniques are also presented. A comprehensive understanding of existing vibration damping mechanisms and new methods of bionic damping design will certainly trigger important applications of precision vibration control in the fields of aerospace, rail transportation and mechanical systems.

The increasing demand for energy absorbent structures, paired with the need for more efficient use of materials in a wide range of engineering fields, has led to an extensive range of designs in the porous forms of sandwiches, honeycomb, and foams. To achieve an even better performance, an ingenious solution is to learn how biological structures adjust their configurations to absorb energy without catastrophic failure. In this study, we have attempted to blend the shape freedom, offered by additive manufacturing techniques, with the biomimetic approach, to propose new lattice structures for energy absorbent applications. To this aim we have combined multiple bio-inspirational sources for the design of optimized configurations under compressive loads. Periodic lattice structures are fabricated based on the designed unit cell geometries and studied using experimental and computational strategies. The individual effect of each bio-inspired feature has been evaluated on the energy absorbance performance of the designed structure. Based on the design parameters of the lattices, a tuning between the strength and energy absorption could be obtained, paving the way for transition within a wide range of real-life applicative scenarios.

Bird feathers sustain bending and vibrations during flight. Such unwanted vibrations could potentially cause noise and flight instabilities. Damping could alter the system response, resulting in improving quiet flight, stability, and controllability. Vanes of feathers are known to be indispensable for supporting the aerodynamic function of the wings. The relationship between the hierarchical structures of vanes and the mechanical properties of the feather has been previously studied. However, still little is known about their relationship with feathers’ damping properties. Here, the role of vanes in feathers’ damping properties was quantified. The vibrations of the feathers with vanes and the bare shaft without vanes after step deflections in the plane of the vanes and perpendicular to it were measured using high-speed video recording. The presence of several main natural vibration modes was observed in the feathers with vanes. After trimming vanes, more vibration modes were observed, the fundamental frequencies increased by 51–70%, and the damping ratio decreased by 38–60%. Therefore, we suggest that vanes largely increase feather damping properties. Damping mechanisms based on the morphology of feather vanes are discussed. The aerodynamic damping is connected with the planar vane surface, the structural damping is related to the interlocking between barbules and barbs, and the material damping is caused by the foamy medulla inside barbs.

In this work, we propose a real proportional-integral-derivative plus second-order derivative (PIDD2) controller as an efficient controller for vehicle cruise control systems to address the challenging issues related to efficient operation. In this regard, this paper is the first report in the literature demonstrating the implementation of a real PIDD2 controller for controlling the respective system. We construct a novel and efficient metaheuristic algorithm by improving the performance of the Aquila Optimizer via chaotic local search and modified opposition-based learning strategies and use it as an excellently performing tuning mechanism. We also propose a simple yet effective objective function to increase the performance of the proposed algorithm (CmOBL-AO) to adjust the real PIDD2 controller's parameters effectively. We show the CmOBL-AO algorithm to perform better than the differential evolution algorithm, gravitational search algorithm, African vultures optimization, and the Aquila Optimizer using well-known unimodal, multimodal benchmark functions. CEC2019 test suite is also used to perform ablation experiments to reveal the separate contributions of chaotic local search and modified opposition-based learning strategies to the CmOBL-AO algorithm. For the vehicle cruise control system, we confirm the more excellent performance of the proposed method against particle swarm, gray wolf, salp swarm, and original Aquila optimizers using statistical, Wilcoxon signed-rank, time response, robustness, and disturbance rejection analyses. We also use fourteen reported methods in the literature for the vehicle cruise control system to further verify the more promising performance of the CmOBL-AO-based real PIDD2 controller from a wider perspective. The excellent performance of the proposed method is also illustrated through different quality indicators and different operating speeds. Lastly, we also demonstrate the good performing capability of the CmOBL-AO algorithm for real traffic cases. We show the CmOBL-AO-based real PIDD2 controller as the most efficient method to control a vehicle cruise control system.

Electrospun nanofibers combined with a wide range of functional additives can be used for a various tissue engineering applications due to their desired biomimetic and physicochemical properties. Therefore, the present study was conducted to obtain a highly efficient nanocomposite electrospun scaffold with appropriate physicochemical performance and biological properties based on Polycaprolactone/Polyurethane (PCL/PU) mixed with gold nanoparticles (GNPs) and soybean oil (SO). In the present study, the desired nanofibers were fabricated by electrospinning PCL/PU mixed solution with GNPs and SO. The nanocomposite electrospun PU/PCL/SO/GNP nanofibers were characterized in terms of chemical composition by attenuated total reflectance–Fourier transform infrared spectroscopy (ATR-FTIR), morphological structure by field-emission scanning electron microscopy (FE-SEM), and mechanical and biological properties. The surface topography and wettability were determined by atomic force microscopy (AFM) and water contact angle measurements, respectively. It was found that the presence of GNPs along with SO in the structure of PCL/PU nanofiber created a smoother surface in terms of surface roughness and also a more homogeneous fibrous structure. In addition, it was observed that both SO and GNPs caused an increase in the electrical conductivity of the fibrous mats. In the biocompatibility evaluations by measuring cell viability and cell adherence to the scaffold’s surfaces, it was found that adding of SO and GNPs supports fibroblasts. Taken together, the fabricated nanocomposite fibrous scaffolds can be a potential candidate for various tissue engineering purposes.

This article introduces a cable-driven lower limb rehabilitation robot with movable distal anchor points (M-CDLR). The traditional cable-driven parallel robots (CDPRs) control the moving platform by changing the length of cables, M-CDLR can also adjust the position of the distal anchor point when the moving platform moves. The M-CDLR this article proposed has gait and single-leg training modes, which correspond to the plane and space motion of the moving platform, respectively. After introducing the system structure configuration, the generalized kinematics and dynamics of M-CDLR are established. The fully constrained CDPRs can provide more stable rehabilitation training than the under-constrained one but requires more cables. Therefore, a motion planning method for the movable distal anchor point of M-CDLR is proposed to realize the theoretically fully constrained with fewer cables. Then the expected trajectory of the moving platform is obtained from the motion capture experiment, and the motion planning of M-CDLR under two training modes is simulated. The simulation results verify the effectiveness of the proposed motion planning method. This study serves as a basic theoretical study of the structure optimization and control strategy of M-CDLR.

This study proposes a novel nature-inspired meta-heuristic optimizer based on the Reptile Search Algorithm combed with Salp Swarm Algorithm for image segmentation using gray-scale multi-level thresholding, called RSA-SSA. The proposed method introduces a better search space to find the optimal solution at each iteration. However, we proposed RSA-SSA to avoid the searching problem in the same area and determine the optimal multi-level thresholds. The obtained solutions by the proposed method are represented using the image histogram. The proposed RSA-SSA employed Otsu’s variance class function to get the best threshold values at each level. The performance measure for the proposed method is valid by detecting fitness function, structural similarity index, peak signal-to-noise ratio, and Friedman ranking test. Several benchmark images of COVID-19 validate the performance of the proposed RSA-SSA. The results showed that the proposed RSA-SSA outperformed other metaheuristics optimization algorithms published in the literature.

The pneumatic gripper in industrial applications has the advantages of structure simplicity and great adaptability, but its gripping power is usually limited due to the low modulus of soft materials. To address this problem, a novel bionic pneumatic gripper inspired by spider legs is proposed. The design has two pairs of symmetrical fingers, each finger consists of two pneumatic actuated joints, two rigid links and one pneumatic soft pad. The rigid link connects the pneumatic chamber which is enclosed in a retractable shell to increase the actuation pressure and the gripping force. The compressibility and elasticity of the soft joint and pad enable the gripper to grasp fragile objects without damage. The modeling of the bionic gripper is developed, and the parameters of the joint actuators are optimized accordingly. The prototype is manufactured and tested with the developed experimental platform, where the gripping force, flexibility and adaptability are evaluated. The results indicate that the designed gripper can grasp irregular and fragile items in sizes from 40 to 140 mm without damage, and the lifting weight is up to 15 N.

The acoustic performance for the nanoporous frustule of the diatom is studied based on the computational fluid dynamics theory and acoustic theory involved. Representative Coscinodiscus sp. frustule is observed through the scanning electron microscope and modeled by the commercial software Solidworks. Further, the acoustic performance for the Coscinodiscus sp. frustule is studied at the varied depth, diameter or interval of the pore, as well as the film thickness of the fluid surrounding the Coscinodiscus sp. frustule. The numerical results show that, when the upper and lower pore diameters are separately 200 and 300 nm, the upper and lower pore depths are separately 200 and 250 nm, and both the pore interval and fluid film thickness are 500 nm, the elaborate nanoporous structure of Coscinodiscus sp. frustule can lower its acoustic power level by 17.49%, compared with that without porous structure. Meanwhile, the double-layer pore of Coscinodiscus sp. frustule can decrease its acoustic power level by 12.69%, compared with its single-layer pore structures.

Ankle injury is one of the most common joint diseases that people experience during exercise. Most people have suffered ankle injuries at least once in their lives. The studies have shown that the ankle joint provides the most power and torques during the act of walking, compared to the knee and hip joints. This paper presents an ankle joint exoskeleton device, which is mainly used to provide assistance and protection to the human ankle joint with a pneumatic assist drive during walking. The pneumatic pressure smart shoes for this ankle exoskeleton were designed for detecting the human gaits to control the exoskeleton with certain supporting forces to the ankle joints at the appropriate timing. Each smart shoe has two sensors placed in between the wearable layer and the sole. The changes of the foot pressures were measured by the sensors for a microcontroller to control the exoskeleton. Two sets of experimental tests which were 2-month trials and gait selection were used to test the shoes. The experiments of 2-month trials were made to evaluate the stability of the shoes. The results showed that the shoes had no damages, no air leakage, and no malfunctions after the trials. The trials of gait selection were made to test the recognition rate which reached at 99.9% for the shoe system. The results showed that the design of the pneumatic smart shoes for the ankle-assisted exoskeleton met the requirements.

Micro-robots have the characteristics of small size, light weight and flexible movement. To design a micro three-legged crawling robot with multiple motion directions, a novel driving scheme based on the inverse piezoelectric effect of piezoelectric ceramics was proposed. The three legs of the robot were equipped with piezoelectric bimorphs as drivers, respectively. The motion principles were analyzed and the overall force analysis was carried out with the theoretical mechanics method. The natural frequency, mode shape and amplitude were analyzed with simulation software COMSOL Multiphysics, the optimal size was determined through parametric analysis, and then the micro three-legged crawling robot was manufactured. The effects of different driving voltages, different driving frequencies, different motion bases and different loads on the motion speed of the robot were tested. It is shown that the maximum speed of single-leg driving was 35.41 cm/s, the switching ability between different motion directions was measured, and the movements in six different directions were achieved. It is demonstrated the feasibility of multi-directional motion of the structure. The research may provide a reference for the design and development of miniature piezoelectric three-legged crawling robots.

This work presents a novel highly adaptable flexible soft glove composed of multimode deformable three-jointed soft fingers. The soft fingers are assembled by soft actuators and plastic materials that can be driven and controlled with single Degree of Freedom (DOF). A variety of different soft actuators are used as joint drive components to meet the motion requirements of fingers under different working conditions. We established a theoretical model to describe the deflection of the soft actuators based on reciprocal theorems. In addition, the finite-element method (FEM) was used to simulate the curvature change of the soft actuator and the soft finger, the soft actuators theoretical and simulation results were verified by experiments, and the multimode deformable soft fingers were simulated by FEM. Finally, a five-finger soft rehabilitation glove was prototyped and presented experimentally where the flexibility and functionality endowed by the soft fingers were demonstrated and highlighted. The versatility was also showcased in the applications.

A new process for the fabrication of sharkskin bionic structures on metal surfaces is proposed. The sharkskin bionic surface was successfully machined on the surface of IN718 by laser sequencing of the abrasive belt surface, laser processing of the layered scale-like structure, and ribbed texture grinding. The flexible contact properties of belt grinding allow ribbed structures to be machined uniformly on a hierarchical, scale-like microstructure. Sharkskin bionic microstructures with radii greater than 75 μm were prepared after parameter optimisation. The influence of processing parameters on the geometrical accuracy of the microstructure was investigated, the microstructure microform and elemental distribution were analyzed, and the relationship between the ribbed microstructure and chemical properties of the surface of the bionic sharkskin on wettability was revealed. The results indicate that reducing the laser power and increasing the laser scan rate can reduce the laser thermal effect and improve the microstructure processing accuracy. The laser ablation process is accompanied by a violent chemical reaction that introduces a large amount of oxygen and carbon elements and infiltrates them at a certain depth. The wettability of the surface undergoes a transition from hydrophilic (contact angle 69.72°) to hydrophobic (contact angle 131.56°) due to the adsorption of C–C/C–H and the reduction of C=O/O=C–O during the placement process. The ribbed microstructure changes the solid–liquid contact on the surface into a solid–liquid–gas contact, which has an enhanced effect on hydrophobicity. This study is a valuable guide to the processing of hydrophobic layered bionic microstructures.

Natural fibers are displacing synthetic fibers as reinforcement in polymer composites due to their ease of processing, low cost, wide availability, biodegradability and sustainability. In this study, industrially discarded agro-waste areca fruit husk and tamarind fruit fibers were processed and used as reinforcement with unsaturated polyester resin to create a hybrid composite containing SiC nano filler particles. The SiC nano filler particles were varied from 1 to 4 wt.% in incremental steps of 1 wt.% with a constant 40 wt.% fiber reinforcement to determine its impact on the thermo-mechanical, morphological, wear and hygro-aging properties of the developed hybrid composite. However, the composite made of 3 wt.% SiC nano filler particles exposed overall better properties with better tensile (9.137 MPa), flexural (104.056 MPa), impact (7.983 J/cm2), hardness (91.577 HRRW), wear (2.2?×?10–6 μm), crystallite size (7.9 nm) and thermal stability (360 °C). Further advancement in weight percent of filler material, has worsened the properties due to poor dispersion and agglomeration factors by reducing the tensile, flexural, impact and hardness characteristics by 4.6%, 6.4%, 4.5% and 2.18% respectively. Also, the microstructural investigation revealed the failure pattern, information on interfacial adhesion between the reinforcement, filler and matrix of the hybrid composites. In addition, the crystalline characteristics and availability of functional groups in hybrid polymer composite with 3 wt.% SiC nano filler particles were disclosed by X-ray diffraction (XRD) and Fourier Transform Infrared (FTIR) spectrum analysis, respectively. The above findings reflects that the produced hybrid polymer composites suits well for interiors of automobiles and maritime interior applications to support loads with in the specified range.

Following the natural structure of the nacre, the material studied consists of a multitude of hexagonal tiles that are glued together in an offset manner with a ductile adhesive. This so-called “wood nacre” consists of macroscopic tiles of birch wood veneer with a thickness of 0.8 mm and a size of 20 or 10 mm in diameter in order to mimic the aragonite tiles and the ductile PUR-adhesive corresponds to the layers of collagen in between. E-modulus (MOE), bending strength (MOR) and impact bending strength of the samples were determined and compared with reference samples of birch laminated wood. The hierarchical layered structure of the tiles does not cause any relevant loss in stiffness. Like nacre, “wood nacre” also shows tough fracture behaviour and a high homogenization effect. However, strain hardening and high fracture toughness of the natural model could not be fully achieved. The reason for this is the insufficient ratio between the strength and stiffness of the veneer layers and the adhesive. By adjusting the size of the tiles, increasing the strength and surface roughness of the veneers, e.g. by densification, and using more ductile adhesives that can be applied in smaller layer thicknesses, it should be possible to better reproduce the natural ratios of nacre and thus achieve a significant improvement in the material properties of “wood nacre”. In addition to the mechanical properties, the high potential of the new material lies in the possibility of producing 3D shell-shaped elements for lightweight wood hybrid construction.

Till now, several novel metaheuristic algorithms are proposed for global search. But only specific algorithms have become popular or attracted researchers, who are efficient in solving global optimization problems as well as real-world application problems. The Social Group Optimization (SGO) algorithm is a new metaheuristic bioinspired algorithm inspired by human social behavior that attracted researchers due to its simplicity and problem-solving capability. In this study, to deal with the problems of low accuracy and local convergence in SGO, the chaos theory is introduced into the evolutionary process of SGO. Since chaotic mapping has certainty, ergodicity, and stochastic property, by replacing the constant value of the self-introspection parameter with chaotic maps, the proposed chaotic social group optimization algorithm increases its convergence rate and resulting precision. The proposal chaotic SGO is validated through 13 benchmark functions and after that 9 structural engineering design problems have been solved. The simulated results have been noticed as competent with that of state-of-art algorithms regarding convergence quality and accuracy, which certifies that improved SGO with chaos is valid and feasible.

Coiled polymer artificial muscles with both large tensile stroke and giant force generation are needed for practical applications in robotics, soft exosuits, and prosthesis. However, most polymer yarn artificial muscles cannot generate a large force or stress. Here, we report an inexpensive Twisted and Coiled Polymer artificial muscle (TCP) that performs both large isobaric and isometric contractions. This TCP can generate a tensile stroke of 20.1% and a specific work capacity of up to 1.3 kJ kg?1 during temperature changes from 20 to 180 °C. Moreover, the nylon yarn artificial muscle produced a reversible output stress of 28.4 MPa, which is 100 times larger than human skeletal muscle. A robot arm and a simple gripper were made to demonstrate the isobaric actuation and isometric actuation of our TCP muscle, repectivley. Thus, the polymer artificial muscles with dual-mode actuation show potential applications in the field of robotics, grippers, and exoskeletons and so on.

Hybrid-driven Underwater Glider (HUG) is a new type of underwater vehicle which integrates the functions of an Autonomous Underwater Glider (AUG) and an Autonomous Unmanned Vehicle (AUV). Although HUG has the characteristics of long endurance distance, its maneuverability still has room to be improved. This work introduces a new movement form of the neck of the underwater creature into HUG and proposes a parallel mechanism to adjust the attitude angle and displacement of the HUG’s bow, which can improve the steering maneuverability. Firstly, the influence of bow movement and rotation on the hydrodynamic force and flow field of the whole machine is analyzed by using the Computational Fluid Dynamics (CFD) method. The degree of freedom, attitude control range and movement amount of the Movable Bow Mechanism (MBM) are obtained, and then the design of MBM is completed based on these constraints. Secondly, the kinematic and dynamic models of MBM are established based on the closed vector method and the Lagrange equation, respectively, which are fully verified by comparing the results of simulation in Matlab and Adams software, then a Radial Basis Function (RBF) neural network adaptive sliding mode controller is designed to improve the dynamic response effect of the output parameters of MBM. Finally, a prototype of MBM is manufactured and assembled. The kinematic, dynamics model and controller are verified by experiments, which provides a basis for applying MBM in HUGs.

Legged locomotion poses significant challenges due to its nonlinear, underactuated and hybrid dynamic properties. These challenges are exacerbated by the high-speed motion and presence of aerial phases in dynamic legged locomotion, which highlights the requirement for online planning based on current states to cope with uncertainty and disturbances. This article proposes a real-time planning and control framework integrating motion planning and whole-body control. In the framework, the designed motion planner allows a wider body rotation range and fast reactive behaviors based on the 3-D single rigid body model. In addition, the combination of a Bézier curve based trajectory interpolator and a heuristic-based foothold planner helps generate continuous and smooth foot trajectories. The developed whole-body controller uses hierarchical quadratic optimization coupled with the full system dynamics, which ensures tasks are prioritized based on importance and joint commands are physically feasible. The performance of the framework is successfully validated in experiments with a torque-controlled quadrupedal robot for generating dynamic motions.

Increasing the power density and overload capability of the energy-supply units (ESUs) is always one of the most challenging tasks in developing and deploying legged vehicles, especially for heavy-duty legged vehicles, in which significant power fluctuations in energy supply exist with peak power several times surpassing the average value. Applying ESUs with high power density and high overload can compactly ensure fluctuating power source supply on demand. It can avoid the ultra-high configuration issue, which usually exists in the conventional lithium-ion battery-based or engine-generator-based ESUs. Moreover, it dramatically reduces weight and significantly increases the loading and endurance capabilities of the legged vehicles. In this paper, we present a hybrid energy-supply unit for a heavy-duty legged vehicle combining the discharge characteristics of lithium-ion batteries and peak energy release/absorption characteristics of supercapacitors to adapt the ESU to high overload power fluctuations. The parameters of the lithium-ion battery pack and supercapacitor pack inside the ESU are optimally matched using the genetic algorithm based on the energy consumption model of the heavy-duty legged vehicle. The experiment results exhibit that the legged vehicle with a weight of 4.2 tons can walk at the speed of 5 km/h in a tripod gait under a reduction of 35.39% in weight of the ESU compared to the conventional lithium-ion battery-based solution.

With the aid of different types of mechanoreceptors, human is capable of perceiving stimuli from surrounding environments and manipulating various objects dexterously. In this paper, a bio-inspired tactile fingertip is designed mimicking human fingertip in both structures and functionalities. Two pairs of strain gages and (Polyvinylidene Fluoride) PVDF films are perpendicularly arranged to simulate the Fast-Adapting (FA) and Slowly Adapting (SA) type mechanoreceptors in human hands, while silicones, Polymethyl Methacrylate (PMMA), and electronic wires are applied to mimic the skin, bone and nerve fibers. Both static and dynamic forces can be perceived sensitively. A preprocessing electric circuit is further designed to transform the resistor changes into voltages, and then filter and amplify the four-channel signals. In addition to strong robustness due to the embedded structure, the developed fingertip is found sensitive to deformations via a force test experiment. Finally, two robotic experiments explore its recognition ability of contact status and object surface. Excellent performance is found with high accuracy of 99.72% achieved in discriminating six surfaces that are ubiquitous in daily life, which demonstrates the effectiveness of our designed tactile sensor.

Recent advances in bionics have made it possible to create various tissue and organs. Using this cell culture technology, engineers have developed a robot driven by three-dimensional cultured muscle cells (bioactuator)—a muscle cell robot. For more applications, researchers have been developed various tissues and organs with bio3D printer. However, three-dimensional cultured muscle cells printed by bio3D printer have been not used for muscle cell robot yet. The aim of our study is to develop easy fabrication method of bioactuator having high design flexibility like as bio3D printer. We fabricated three-dimensional cultured muscle cells using mold and dish having pin which can contribute to shape and cell alignment. In this study, we observed that our method maintained the shape of three-dimensional cultured muscle cells and caused cell alignment which is important for bioactuator development. We named three-dimensional cultured muscle cells developed in this study “bio-cultured artificial muscle (BiCAM)”. Finally, we observed that BiCAM contracted in response to electrical stimulus. From these data, we concluded our proposed method is easy fabrication method of bioactuator having high design flexibility.

The traditionally articulated manipulator had a single control method, and the limited motion trajectory space was unsuitable for working in an unstructured environment. This paper introduces a control method and optimization for a multijoint manipulator Inspired by snakes' curling and stretching motions. First, we analyze the manipulator’s connection mode and motion planning and propose a new motion method. In addition, we calculated the relevant positions and angles and subdivided the motion of some joints based on the principle of the meta-heuristic algorithm. Ultimately, the manipulator in this mode has a larger workspace and more flexible motion trajectories. The experimental results are consistent with the theoretical analysis, which further proves the feasibility and scalability of the scheme.

Active exoskeletons have been widely investigated to supplement and restore human hand movements, but a significant limitation is that they have a complicated design requiring multi actuators. Single Degree-Of-Freedom (DOF) planar linkage mechanisms could be used with simple control. This research represents the design and optimization of a mechanism proposed for a finger exoskeleton bionic device. One DOF six-bar linkage Stephenson-II is selected, and a motion-generation mechanism synthesis problem is defined. The design is based on the data obtained from the flexion/extension motion of the index finger through 16 precision points and 16 angles for each phalange associated with the fingertip position. After explaining the kinematic analysis of the Stephenson-II, an evaluation of swarm intelligence techniques, including PSO, GWO, and ARO algorithms for solving optimization problems, is presented. ARO algorithm demonstrates the best performance among them. Moreover, the optimized mechanism in this study has a 50% error reduction compared to the one previously designed (Bataller et al. in Mech Mach Theory 105: 31–43, 2016).

Bilateral rehabilitation systems with bilateral or unilateral assistive robots have been developed for hemiplegia patients to recover their one-side paralysis. However, the compliant robotic assistance to promote bilateral inter-limb coordination remains a challenge that should be addressed. In this paper, a biomimetic variable stiffness modulation strategy for the Variable Stiffness Actuator (VSA) integrated robotic is proposed to improve bilateral limb coordination and promote bilateral motor skills relearning. An Electromyography (EMG)-driven synergy reference stiffness estimation model of the upper limb elbow joint is developed to reproduce the muscle synergy effect on the affected side limb by independent real-time stiffness control. Additionally, the bilateral impedance control is incorporated for realizing compliant patient–robot interaction. Preliminary experiments were carried out to evaluate the tracking performance and investigate the multiple task intensities’ influence on bilateral motor skills relearning. Experimental results evidence the proposed method could enable bilateral motor task skills relearning with wide-range task intensities and further promote bilateral inter-limb coordination.

Nowadays, meta-heuristic algorithms are attracting widespread interest in solving high-dimensional nonlinear optimization problems. In this paper, a COVID-19 prevention-inspired bionic optimization algorithm, named Coronavirus Mask Protection Algorithm (CMPA), is proposed based on the virus transmission of COVID-19. The main inspiration for the CMPA originated from human self-protection behavior against COVID-19. In CMPA, the process of infection and immunity consists of three phases, including the infection stage, diffusion stage, and immune stage. Notably, wearing masks correctly and safe social distancing are two essential factors for humans to protect themselves, which are similar to the exploration and exploitation in optimization algorithms. This study simulates the self-protection behavior mathematically and offers an optimization algorithm. The performance of the proposed CMPA is evaluated and compared to other state-of-the-art metaheuristic optimizers using benchmark functions, CEC2020 suite problems, and three truss design problems. The statistical results demonstrate that the CMPA is more competitive among these state-of-the-art algorithms. Further, the CMPA is performed to identify the parameters of the main girder of a gantry crane. Results show that the mass and deflection of the main girder can be improved by 16.44% and 7.49%, respectively.

In recent years, designing a soft robot that can jump continuously and quickly explore in a narrow space has been a hot research topic. With the continuous efforts of researchers, many types of actuators have been developed and successfully employed to actuate the rapid locomotion of soft robots. Although these mechanisms have enabled soft robots with excellent movement capabilities, they largely rely on external energy supply cables, which greatly limits their applications. Therefore, it is still a big challenge to realize the unconstrained movement of the soft robot and the flexible adjustment of the movement direction in a narrow space. Here, a wireless magnetically controlled soft jumping robot with single-leg is proposed, which can achieve continuous and rapid jumping motion. What's more interesting is that by changing the frequency and waveform of the control signal, this soft robot can easily switch between forward and backward motions. This motion direction switching function enables the magnetically controlled soft robot to return to the initial position without adjusting the direction when it completes the operation in a narrow pipe or takes the wrong path, which greatly improves the motion efficiency of the soft jumping robot and broadens its application field.

This paper presents an efficient enhanced snake optimizer termed BEESO for global optimization and engineering applications. As a newly mooted meta-heuristic algorithm, snake optimizer (SO) mathematically models the mating characteristics of snakes to find the optimal solution. SO has a simple structure and offers a delicate balance between exploitation and exploration. However, it also has some shortcomings to be improved. The proposed BEESO consequently aims to lighten the issues of lack of population diversity, convergence slowness, and the tendency to be stuck in local optima in SO. The presentation of Bi-Directional Search (BDS) is to approach the global optimal value along the direction guided by the best and the worst individuals, which makes the convergence speed faster. The increase in population diversity in BEESO benefits from Modified Evolutionary Population Dynamics (MEPD), and the replacement of poorer quality individuals improves population quality. The Elite Opposition-Based Learning (EOBL) provides improved local exploitation ability of BEESO by utilizing solid solutions with good performance. The performance of BEESO is illustrated by comparing its experimental results with several algorithms on benchmark functions and engineering designs. Additionally, the results of the experiment are analyzed again from a statistical point of view using the Friedman and Wilcoxon rank sum tests. The findings show that these introduced strategies provide some improvements in the performance of SO, and the accuracy and stability of the optimization results provided by the proposed BEESO are competitive among all algorithms. To conclude, the proposed BEESO offers a good alternative to solving optimization issues.

This work proposes an improved multi-objective slime mould algorithm, called IBMSMA, for solving the multi-objective truss optimization problem. In IBMSMA, the chaotic grouping mechanism and dynamic regrouping strategy are employed to improve population diversity; the shift density estimation is used to assess the superiority of search agents and to provide selection pressure for population evolution; and the Pareto external archive is utilized to maintain the convergence and distribution of the non-dominated solution set. To evaluate the performance of IBMSMA, it is applied to eight multi-objective truss optimization problems. The results obtained by IBMSMA are compared with other 14 well-known optimization algorithms on hypervolume, inverted generational distance and spacing-to-extent indicators. The Wilcoxon statistical test and Friedman ranking are used for statistical analysis. The results of this study reveal that IBMSMA can fnd the Pareto front with better convergence and diversity in less time than state-of-the-art algorithms, demonstrating its capability in tackling large-scale engineering design problems.

This paper proposes a modified version of the Dwarf Mongoose Optimization Algorithm (IDMO) for constrained engineering design problems. This optimization technique modifies the base algorithm (DMO) in three simple but effective ways. First, the alpha selection in IDMO differs from the DMO, where evaluating the probability value of each fitness is just a computational overhead and contributes nothing to the quality of the alpha or other group members. The fittest dwarf mongoose is selected as the alpha, and a new operator ω is introduced, which controls the alpha movement, thereby enhancing the exploration ability and exploitability of the IDMO. Second, the scout group movements are modified by randomization to introduce diversity in the search process and explore unvisited areas. Finally, the babysitter's exchange criterium is modified such that once the criterium is met, the babysitters that are exchanged interact with the dwarf mongoose exchanging them to gain information about food sources and sleeping mounds, which could result in better-fitted mongooses instead of initializing them afresh as done in DMO, then the counter is reset to zero. The proposed IDMO was used to solve the classical and CEC 2020 benchmark functions and 12 continuous/discrete engineering optimization problems. The performance of the IDMO, using different performance metrics and statistical analysis, is compared with the DMO and eight other existing algorithms. In most cases, the results show that solutions achieved by the IDMO are better than those obtained by the existing algorithms

Bioinspired active camber morphing is an innovative solution for the aerodynamic performance enhancement of flight vehicles such as Micro Aerial Vehicles (MAVs) and Unmanned Aerial Vehicles (UAVs). In the present article, a bio-inspired Fish Bone Active Camber (FishBAC) corrugated rib design concept with and without a spine for an Unmanned Aerial Vehicle (UAV) is proposed. The wing model is composed of multiple corrugated ribs and a splitted spar for connecting each rib. The rib geometry is subjected to static structural analysis using ANSYS Finite Element Analysis (FEA) module under the unit load conditions. The deformation modes are first extracted from the solution of the wind tunnel test and the elastically deformed NACA 4412 profile will be used to perform Fluid-Structure Interaction (FSI) studies as a partly coupled analysis. FishBAC corrugated rib with spine design is a stable structure as inspired from nature species that can withstand elastic and inertial loads. Computational fluid dynamics (CFD) simulation is performed to compute the coefficient of lift (Cl), coefficient of drag (Cd) at different Angle of Attack (AoA) for a modified NACA 4412 airfoil and the pressure loads acting on the deformed shape is extracted. The Cl obtained for the modified airfoil at lower AoA is about 60–80% higher and the maximum Cl (Clmax) is 62% higher than the baseline airfoil. The Cd of modified airfoil is reduced about 20% at the AoA α?=?3° as compared with the baseline model. The proposed corrugated rib structure has been successfully 3D printed with Polylactic Acid plus (PLA+) material and the wind tunnel testing is done to validate the Cl, Cd values obtained through CFD simulations and the results are presented.

Natural fibre-reinforced composites are now becoming incredibly common in various products because of their comparable qualities to conventional materials. Due to its availability, superior mechanical qualities, and low cost, banana pseudostem is extensively used in various applications requiring natural fibres. This study investigates the physical and mechanical properties of epoxy composites reinforced with banana pseudostem fibres that contain Al2O3 particulate. In order to produce composites with fibre and filler loadings, manual hand layup was used. Fibre and filler loading effects on composite properties were studied in experiments. The results of the investigations demonstrate that proportion of Al2O3 in composites significantly influences their mechanical and physical properties. Additionally, the composite with a fibre content of 30% shows improved mechanical proportions and hardness. Thermogravimetric analysis was used to study the composite's thermal behaviour. Composites are more thermally stable than raw epoxy. Fourier Transform Infrared Spectroscopy and Scanning electron microscopy analyses were used to characterize the composites.

The temperature distribution along the surface of evaporating droplets can afect signifcantly the fow feld inside the liquid and consequently the deposition pattern on the substrate. Although a “phase diagram” for the temperature distribution along the droplet surface was revealed by the numerical simulations, its experimental verifcation has still not been reported. In this paper, the surface temperature of evaporating droplets has been observed by using an infrared (IR) camera. The experimental observations show that three diferent patterns of temperature distribution along the droplet surface occur in succession with the change of the contact angle during the evaporation process, which is in good agreement with the theoretical predictions by the “phase diagram” of the surface temperature distribution. Furthermore, the efects of evaporative cooling on the “phase diagram” of sessile droplets have been explored. The numerical results indicate that the evaporative cooling efect can alter the size of the phase regions in the “phase diagram”. These results may provide a better understanding of the evaporation process of drying sessile droplets.

By imitating the behavioral characteristics of some typical animals, researchers develop bionic stepping motors to extend the working range of piezoelectric materials and utilize their high accuracy advantage as well. A comprehensive review of the bionic stepping motors driven by piezoelectric materials is presented in this work. The main parts of stepping piezoelectric motors, including the feeding module, clamping module, and other critical components, are introduced elaborately. We classify the bionic stepping piezoelectric motors into inchworm motors, seal motors, and inertia motors depending on their main structure modules, and present the mutual transformation relationships among the three types. In terms of the relative position relationships among the main structure modules, each of the inchworm motors, seal motors, and inertia motors can further be divided into walker type, pusher type, and hybrid type. The configurations and working principles of all bionic stepping piezoelectric motors are reported, followed by a discussion of the advantages and disadvantages of the performance for each type. This work provides theoretical support and thoughtful insights for the understanding, analysis, design, and application of the bionic stepping piezoelectric motors.

Small parasitic Hemipteran insects known as bedbugs (Cimicidae) feed on warm-blooded mammal’s blood. The most famous member of this family is the Cimex lectularius or common bedbug. The current paper proposes a novel swarm intelligence optimization algorithm called the Bedbug Meta-Heuristic Algorithm (BMHA). The primary inspiration for the bedbug algorithm comes from the static and dynamic swarming behaviors of bedbugs in nature. The two main stages of optimization algorithms, exploration, and exploitation, are designed by modeling bedbug social interaction to search for food. The proposed algorithm is benchmarked qualitatively and quantitatively using many test functions including CEC2019. The results of evaluating BMHA prove that this algorithm can improve the initial random population for a given optimization problem to converge towards global optimization and provide highly competitive results compared to other well-known optimization algorithms. The results also prove the new algorithm's performance in solving real optimization problems in unknown search spaces. 

It has been proved that the construction of interconnected armour on superhydrophobic surface could significantly enhance the mechanical robustness. Here, a new kind of armour with frame/protrusion hybrid structure was achieved by nanosecond laser technology. Then, this armoured superhydrophobic surface demonstrated excellent durability, which could withstand linear abrasion (~?3 N press) 800 cycles, water jet test (1.0 MPa pressure) 40 times and 100 °C treatment 18 days. Particularly, the armoured superhydrophobic sample shows outstanding anti-icing ability, which can speed up the supercooled water dropping (no adhesion within 2 h), increase the freezing delay time by?~?3 times and maintain low adhesion force (less than 35 kPa) after 30 icing/de-icing cycles. Further finite element analysis and theoretical modeling proved that the developed frame/protuberance hybrid structure could effectively enhance the durability. The relatively low surface accuracy in this study can significantly reduce processing cost, which provides a bright future for the practical application of armour superhydrophobic materials

The purpose of community detection in complex networks is to identify the structural location of nodes. Complex network methods are usually graphical, with graph nodes representing objects and edges representing connections between things. Communities are node clusters with many internal links but minimal intergroup connections. Although community detection has attracted much attention in social media research, most face functional weaknesses because the structure of society is unclear or the characteristics of nodes in society are not the same. Also, many existing algorithms have complex and costly calculations. This paper proposes different Harris Hawk Optimization (HHO) algorithm methods (such as Improved HHO Opposition-Based Learning(OBL) (IHHOOBL), Improved HHO Lévy Flight (IHHOLF), and Improved HHO Chaotic Map (IHHOCM)) were designed to balance exploitation and exploration in this algorithm for community detection in the social network. The proposed methods are evaluated on 12 different datasets based on NMI and modularity criteria. The findings reveal that the IHHOOBL method has better detection accuracy than IHHOLF and IHHOCM. Also, to offer the efficiency of the , state-of-the-art algorithms have been used as comparisons. The improvement percentage of IHHOOBL compared to the state-of-the-art algorithm is about 7.18%.

The pelvis plays a significant role in creating smooth and efficient motion during gait. In this study, an orthosis is designed to support pelvis motion of patients with the inability to walk. This assistive device is un-powered and consists of only passive elements. By focusing on the motion of the lower extremities during treadmill walking, a 3D dynamic model of the human body is simulated through a coupled optimization process. Based on two approaches of direct and inverse dynamics, the optimization problems are defined to derive optimum structural parameters of the pelvic orthosis. The optimization results of the direct dynamics problem indicate good matches between the optimized time plots of pelvis rotations with corresponding desired ones. Moreover, by solving the inverse dynamics problem, the minimum value of torque vector of the hip joint of the stance leg during a gait cycle is obtained. Furthermore, by utilizing a prototype of the orthosis, preliminary experiments are conducted on a normal user to validate the model and to investigate the feasibility of using the device for rehabilitation. For this purpose, the rotational movements of the pelvis and energy consumption of the subject in two cases with and without the device are compared during gait on a treadmill. Decreased energy consumption and the compliant motion of the pelvis while using the device verify simulation results and confirm the favorable performance of the assistive device for pelvic support during walking rehabilitation.