Biomimetics, Volume 9, Issue 1 (January 2024) – 62 articles

The routine use of prosthetic hands significantly enhances amputees’ daily lives, yet it often introduces cognitive load and reduces reaction speed. To address this issue, we introduce a wearable semi-autonomous hierarchical control framework tailored for amputees. Drawing inspiration from the visual processing stream in humans, a fully autonomous bionic controller is integrated into the prosthetic hand control system to offload cognitive burden, complemented by a Human-in-the-Loop (HIL) control method. In the ventral-stream phase, the controller integrates multi-modal information from the user’s hand–eye coordination and biological instincts to analyze the user’s movement intention and manipulate primitive switches in the variable domain of view. Transitioning to the dorsal-stream phase, precise force control is attained through the HIL control strategy, combining feedback from the prosthetic hand’s sensors and the user’s electromyographic (EMG) signals. The effectiveness of the proposed interface is demonstrated by the experimental results. Our approach presents a more effective method of interaction between a robotic control system and the human. Full article

(1) Background: The aim was to perform a literature review on customized subperiosteal implants (CSIs) and provide clinical guidelines based on the results of an expert consensus meeting held in 2023. (2) Methods: A literature search was performed in Pubmed (MEDLINE) in July 2023, including case series and cohort studies with a minimum follow-up of 6 months that analyzed totally or partially edentulous patients treated with CSIs. Previously, an expert consensus meeting had been held in May 2023 to establish the most relevant clinical guidelines. (3) Results: Six papers (four case series and two retrospective cohort studies) were finally included in the review. Biological and mechanical complication rates ranged from 5.7% to 43.8% and from 6.3% to 20%, respectively. Thorough digital planning to ensure the passive fit of the CSI is mandatory to avoid implant failure. (4) Conclusions: CSIs are a promising treatment option for rehabilitating edentulous patients with atrophic jaws; they seem to have an excellent short-term survival rate, a low incidence of major complications, and less morbidity in comparison with complex bone grafting procedures. As the available data on the use of CSIs are very scarce, it is not possible to establish clinical recommendations based on scientific evidence. Full article

In this paper, sorghum and reed, which possess light stem structures in nature, were selected as biomimetic prototypes. Based on their mechanical stability characteristics—the porous structure at the node feature and the porous feature in the outer skin— biomimetic optimization design, simulation, and experimental research on both the traditional hexagonal structure and a hexagonal honeycomb structure were carried out. According to the two types of straw microcell and chamber structure characteristics, as well as the cellular energy absorption structure for the bionic optimization design, 22 honeycomb structures in 6 categories were considered, including a corrugated cell wall bionic design, a modular cell design, a reinforcement plate structure, and a self-similar structure, as well as a porous cell wall structure and gradient structures of variable wall thickness. Among them, HTPC-3 (a combined honeycomb structure), HSHT (a self-similar honeycomb structure), and HBCT-257 (a radial gradient variable wall thickness honeycomb structure) had the best performance: their energy absorption was 41.06%, 17.84%, and 83.59% higher than that of HHT (the traditional hexagonal honeycomb decoupling unit), respectively. Compared with HHT (a traditional hexagon honeycomb decoupling unit), the specific energy absorption was increased by 39.98%, 17.24%, and 26.61%, respectively. Verification test analysis revealed that the combined honeycomb structure performed the best and that its specific energy absorption was 22.82% higher than that of the traditional hexagonal structure. Full article

The current study investigated the geometry optimization of a hybrid-driven (based on the combination of air pressure and tendon tension) soft robot for use in robot-assisted intra-bronchial intervention. Soft robots, made from compliant materials, have gained popularity for use in surgical interventions due to their dexterity and safety. The current study aimed to design a catheter-like soft robot with an improved performance by minimizing radial expansion during inflation and increasing the force exerted on targeted tissues through geometry optimization. To do so, a finite element analysis (FEA) was employed to optimize the soft robot’s geometry, considering a multi-objective goal function that incorporated factors such as chamber pressures, tendon tensions, and the cross-sectional area. To accomplish this, a cylindrical soft robot with three air chambers, three tendons, and a central working channel was considered. Then, the dimensions of the soft robot, including the length of the air chambers, the diameter of the air chambers, and the offsets of the air chambers and tendon routes, were optimized to minimize the goal function in an in-plane bending scenario. To accurately simulate the behavior of the soft robot, Ecoflex 00-50 samples were tested based on ISO 7743, and a hyperplastic model was fitted on the compression test data. The FEA simulations were performed using the response surface optimization (RSO) module in ANSYS software, which iteratively explored the design space based on defined objectives and constraints. Using RSO, 45 points of experiments were generated based on the geometrical and loading constraints. During the simulations, tendon force was applied to the tip of the soft robot, while simultaneously, air pressure was applied inside the chamber. Following the optimization of the geometry, a prototype of the soft robot with the optimized values was fabricated and tested in a phantom model, mimicking simulated surgical conditions. The decreased actuation effort and radial expansion of the soft robot resulting from the optimization process have the potential to increase the performance of the manipulator. This advancement led to improved control over the soft robot while additionally minimizing unnecessary cross-sectional expansion. The study demonstrates the effectiveness of the optimization methodology for refining the soft robot’s design and highlights its potential for enhancing surgical interventions. Full article

Soft robots, especially soft robotic hands, possess prominent potential for applications in close proximity and direct contact interaction with humans due to their softness and compliant nature. The safety perception of users during interactions with soft robots plays a crucial role in influencing trust, adaptability, and overall interaction outcomes in human–robot interaction (HRI). Although soft robots have been claimed to be safe for over a decade, research addressing the perceived safety of soft robots still needs to be undertaken. The current safety guidelines for rigid robots in HRI are unsuitable for soft robots. In this paper, we highlight the distinctive safety issues associated with soft robots and propose a framework for evaluating the perceived safety in human–soft robot interaction (HSRI). User experiments were conducted, employing a combination of quantitative and qualitative methods, to assess the perceived safety of 15 interactive motions executed by a soft humanoid robotic hand. We analyzed the characteristics of safe interactive motions, the primary factors influencing user safety assessments, and the impact of motion semantic clarity, user technical acceptance, and risk tolerance level on safety perception. Based on the analyzed characteristics, we summarize vital insights to provide valuable guidelines for designing safe, interactive motions in HSRI. The current results may pave the way for developing future soft machines that can safely interact with humans and their surroundings. Full article

Cutinase from Fusarium solani pisi is an enzyme that bridges functional properties between lipases and esterases, with applications in detergents, food processing, and the synthesis of fine chemicals. The purification procedure of recombinant cutinase from E. coil extracts is a well-established but time-consuming process, which involves a sequence of two anionic exchange chromatography steps followed by dialysis. Affinity chromatography is the most efficient method for protein purification, the major limitation of its use being often the availability of a ligand selective for a given target protein. Synthetic affinity ligands that specifically recognize certain sites on the surface of proteins are highly desirable for affinity processes due to their cost-effectiveness, durability, and reusability across multiple cycles. Additionally, these ligands establish moderate affinity interactions with the target protein, making it possible to purify proteins under gentle conditions while maintaining high levels of activity recovery. This study aimed to develop a new method for purifying cutinase, utilizing triazine-scaffolded biomimetic affinity ligands. These ligands were previously screened from a biased-combinatorial library to ensure their binding ability to cutinase without compromising its biological function. A lead ligand, designated as 11/3′, [4-({4-chloro-6-[(2-methylbutyl)amino]-1,3,5-triazin-2-yl}amino)benzoic acid], was chosen and directly synthesized onto agarose. Experiments conducted at different scales demonstrated that this ligand (with an affinity constant K_a ≈ 10⁴ M⁻¹) exhibited selectivity towards cutinase, enabling the purification of the enzyme from an E. coli crude production medium in a single step. Under optimized conditions, the protein and activity yields reached 25% and 90%, respectively, with a resulting cutinase purity of 85%. Full article

Rowing motion with paired propellers is an essential actuation mechanism for swimming robots. Previous work in this field has typically employed flexible propellers to generate a net thrust or torque by using changes in the compliance values of flexible structures under the influence of a fluid. The low stiffness values of the flexible structures restrict the upper limit of the oscillation frequency and amplitude, resulting in slow swimming speeds. Furthermore, complex coupling between the fluid and the propeller reduce the accuracy of flexible propeller simulations. A design of a flexible passive joint paddle was proposed in this study, and a dynamics model and simulation of the paddle were experimentally verified. In order to optimize the straight swimming speed, a data-driven model was proposed to improve the simulation accuracy. The effects of the joint number and controller parameters on the robot’s straight swimming speed were comprehensively investigated. The multi-joint paddle exhibited significantly improved thrust over the single-joint paddle in a symmetric driving mode. The data-driven model reduced the total error of the simulated data of the propulsive force in the range of control parameters to 0.51%. Swimming speed increased by 3.3 times compared to baseline. These findings demonstrate the utility of the proposed dynamics and data-driven models in the multi-objective design of swimming robots. Full article

The successful regeneration of large-size bone defects remains one of the most critical challenges faced in orthopaedics. Recently, 3D printing technology has been widely used to fabricate reliable, reproducible and economically affordable scaffolds with specifically designed shapes and porosity, capable of providing sufficient biomimetic cues for a desired cellular behaviour. Natural or synthetic polymers reinforced with active bioceramics and/or graphene derivatives have demonstrated adequate mechanical properties and a proper cellular response, attracting the attention of researchers in the bone regeneration field. In the present work, 3D-printed graphene nanoplatelet (GNP)-reinforced polylactic acid (PLA)/hydroxyapatite (HA) composite scaffolds were fabricated using the fused deposition modelling (FDM) technique. The in vitro response of the MC3T3-E1 pre-osteoblasts and RAW 264.7 macrophages revealed that these newly designed scaffolds exhibited various survival rates and a sustained proliferation. Moreover, as expected, the addition of HA into the PLA matrix contributed to mimicking a bone extracellular matrix, leading to positive effects on the pre-osteoblast osteogenic differentiation. In addition, a limited inflammatory response was also observed. Overall, the results suggest the great potential of the newly developed 3D-printed composite materials as suitable candidates for bone tissue engineering applications. Full article

The Aquila Optimizer (AO) is a metaheuristic algorithm that is inspired by the hunting behavior of the Aquila bird. The AO approach has been proven to perform effectively on a range of benchmark optimization issues. However, the AO algorithm may suffer from limited exploration ability in specific situations. To increase the exploration ability of the AO algorithm, this work offers a hybrid approach that employs the alpha position of the Grey Wolf Optimizer (GWO) to drive the search process of the AO algorithm. At the same time, we applied the quasi-opposition-based learning (QOBL) strategy in each phase of the Aquila Optimizer algorithm. This strategy develops quasi-oppositional solutions to current solutions. The quasi-oppositional solutions are then utilized to direct the search phase of the AO algorithm. The GWO method is also notable for its resistance to noise. This means that it can perform effectively even when the objective function is noisy. The AO algorithm, on the other hand, may be sensitive to noise. By integrating the GWO approach into the AO algorithm, we can strengthen its robustness to noise, and hence, improve its performance in real-world issues. In order to evaluate the effectiveness of the technique, the algorithm was benchmarked on 23 well-known test functions and CEC2017 test functions and compared with other popular metaheuristic algorithms. The findings demonstrate that our proposed method has excellent efficacy. Finally, it was applied to five practical engineering issues, and the results showed that the technique is suitable for tough problems with uncertain search spaces. Full article

An ICIE16-bioactive glass (BG) composition (in mol%: 49.5 SiO₂, 6.6 Na₂O, 36.3 CaO, 1.1 P₂O₅, and 6.6 K₂O) has demonstrated excellent in vitro cytocompatibility when cultured with human bone marrow-derived mesenchymal stromal cells (BMSCs). However, its impact on the development of an osseous extracellular matrix (ECM) is limited. Since zinc (Zn) is known to enhance ECM formation and maturation, two ICIE16-BG-based Zn-supplemented BG compositions, namely 1.5 Zn-BG and 3Zn-BG (in mol%: 49.5 SiO₂, 6.6 Na₂O, 34.8/33.3 CaO, 1.1 P₂O₅, 6.6 K₂O, and 1.5/3.0 ZnO) were developed, and their influence on BMSC viability, osteogenic differentiation, and ECM formation was assessed. Compared to ICIE16-BG, the Zn-doped BGs showed improved cytocompatibility and significantly enhanced osteogenic differentiation. The expression level of the osteopontin gene was significantly higher in the presence of Zn-doped BGs. A larger increase in collagen production was observed when the BMSCs were exposed to the Zn-doped BGs compared to that of the ICIE16-BG. The calcification of the ECM was increased by all the BG compositions; however, calcification was significantly enhanced by the Zn-doped BGs in the early stages of cultivation. Zn constitutes an attractive addition to ICIE16-BG, since it improves its ability to build and calcify an ECM. Future studies should assess whether these positive properties remain in an in vivo environment. Full article

The quasi-static regime of friction between a rigid steel indenter and a soft elastomer with high adhesion is studied experimentally. An analysis of the formally calculated dependencies of a friction coefficient on an external load (normal force) shows that the friction coefficient monotonically decreases with an increase in the load, following a power law relationship. Over the entire range of contact loads, a friction mode is realized in which constant shear stresses are maintained in the tangential contact, which corresponds to the “adhesive” friction mode. In this mode, Amonton’s law is inapplicable, and the friction coefficient loses its original meaning. Some classical works, which show the existence of a transition between “adhesive” and “normal” friction, were analyzed. It is shown that, in fact, there is no such transition. A computer simulation of the indentation process was carried out within the framework of the boundary element method, which confirmed the experimental results. Full article

In this paper, we propose a reinforcement learning-based end-to-end learning method for the autonomous driving of a mobile robot in a dynamic environment with obstacles. Applying two additional techniques for reinforcement learning simultaneously helps the mobile robot in finding an optimal policy to reach the destination without collisions. First, the multifunctional reward-shaping technique guides the agent toward the goal by utilizing information about the destination and obstacles. Next, employing the hindsight experience replay technique to address the experience imbalance caused by the sparse reward problem assists the agent in finding the optimal policy. We validated the proposed technique in both simulation and real-world environments. To assess the effectiveness of the proposed method, we compared experiments for five different cases. Full article

Radiative cooling is a promising strategy to address energy challenges arising from global warming. Nevertheless, integrating optimal cooling performance with commercial applications is a considerable challenge. Here, we demonstrate a scalable and straightforward approach for fabricating green radiative cooling coating consisting of methyl cellulose matrix-random diatomites with water as a solvent. Because of the efficient scattering of the porous morphology of diatomite and the inherent absorption properties of both diatomite and cellulose, the aqueous coating exhibits an excellent solar reflectance of 94% in the range of 0.25–2.5 μm and a thermal emissivity of 0.9 in the range of 8–14 µm. During exposure to direct sunlight at noon, the obtained coating achieved a maximum subambient temperature drop of 6.1 °C on sunny days and 2.5 °C on cloudy days. Furthermore, diatomite is a naturally sourced material that requires minimal pre-processing, and our coatings can be prepared free from harmful organic compounds. Combined with cost-effectiveness and environmental friendliness, it offers a viable path for the commercial application of radiative cooling. Full article

This paper presents a monocular biological microscope with colorful 3D reconstruction and an extended depth of field using an electrically tunable lens. It is based on a 4f optical system with an electrically tunable lens at the confocal plane. Rapid and extensive depth scanning while maintaining consistent magnification without mechanical movement is achieved. We propose an improved Laplacian operator that considers pixels in diagonal directions to provide enhanced fusion effects and obtain more details of the object. Accurate 3D reconstruction is achieved using the shape-from-focus method by tuning the focal power of the electrically tunable lens. We validate the proposed method by performing experiments on biological samples. The 3D reconstructed images obtained from the biological samples match the actual shrimp larvae and bee antenna samples. Two standard gauge blocks are used to evaluate the 3D reconstruction performance of the proposed method. The experimental results show that the extended depth of fields are 120 µm, 240 µm, and 1440 µm for shrimp larvae, bee tentacle samples, and gauge blocks, respectively. The maximum absolute errors are −39.9 μm and −30.6 μm for the first and second gauge blocks, which indicates 3D reconstruction deviations are 0.78% and 1.52%, respectively. Since the procedure does not require any custom hardware, it can be used to transform a biological microscope into one that effectively extends the depth of field and achieves highly accurate 3D reconstruction results, as long as the requirements are met. Such a microscope presents a broad range of applications, such as biological detection and microbiological diagnosis, where colorful 3D reconstruction and an extended depth of field are critical. Full article

In the field of three-dimensional object design and fabrication, this paper explores the transformative potential at the intersection of biomaterials, biopolymers, and additive manufacturing. Drawing inspiration from the intricate designs found in the natural world, this study contributes to the evolving landscape of manufacturing and design paradigms. Biomimicry, rooted in emulating nature’s sophisticated solutions, serves as the foundational framework for developing materials endowed with remarkable characteristics, including adaptability, responsiveness, and self-transformation. These advanced engineered biomimetic materials, featuring attributes such as shape memory and self-healing properties, undergo rigorous synthesis and characterization procedures, with the overarching goal of seamless integration into the field of additive manufacturing. The resulting synergy between advanced manufacturing techniques and nature-inspired materials promises to revolutionize the production of objects capable of dynamic responses to environmental stimuli. Extending beyond the confines of laboratory experimentation, these self-transforming objects hold significant potential across diverse industries, showcasing innovative applications with profound implications for object design and fabrication. Through the reduction of waste generation, minimization of energy consumption, and the reduction of environmental footprint, the integration of biomaterials, biopolymers, and additive manufacturing signifies a pivotal step towards fostering ecologically conscious design and manufacturing practices. Within this context, inanimate three-dimensional objects will possess the ability to transcend their static nature and emerge as dynamic entities capable of evolution, self-repair, and adaptive responses in harmony with their surroundings. The confluence of biomimicry and additive manufacturing techniques establishes a seminal precedent for a profound reconfiguration of contemporary approaches to design, manufacturing, and ecological stewardship, thereby decisively shaping a more resilient and innovative global milieu. Full article

Pistol shrimp generate cavitation bubbles. Cavitation impacts due to bubble collapses are harmful phenomena, as they cause severe damage to hydraulic machinery such as pumps and valves. However, cavitation impacts can be utilized for mechanical surface treatment to improve the fatigue strength of metallic materials, which is called “cavitation peening”. Through conventional cavitation peening, cavitation is generated by a submerged water jet, i.e., a cavitating jet or a pulsed laser. The fatigue strength of magnesium alloy when treated by the pulsed laser is larger than that of the jet. In order to drastically increase the processing efficiency of cavitation peening, the mechanism of pistol shrimp (specifically when used to create a cavitation bubble), i.e., Alpheus randalli, was quantitatively investigated. It was found that a pulsed water jet generates a cavitation bubble when a shrimp snaps its claws. Furthermore, two types of cavitation generators were developed, namely, one that uses a pulsed laser and one that uses a piezo actuator, and this was achieved by mimicking a pistol shrimp. The generation of cavitation bubbles was demonstrated by using both types of cavitation generators: the pulsed laser and the piezo actuator. Full article

The intricate and highly complex morphologies of diatom frustules have long captured the attention of biomimetic researchers, initiating innovation in engineering solutions. This study investigates the potential of diatom-inspired surface stiffeners to determine whether the introduced innovative strategy is a viable alternative for addressing engineering challenges demanding enhanced stiffness. This interdisciplinary study focuses on the computer-aided generation of stress-adaptive lightweight structures aimed at optimizing bending stiffness. Through a comprehensive microscopical analysis, morphological characteristics of diatom frustules were identified and abstracted to be applied to a reference model using computer-aided methods and simulated to analyze their mechanical behavior under load-bearing conditions. Afterwards, the models are compared against a conventional engineering approach. The most promising biomimetic approach is successfully automated, extending its applicability to non-planar surfaces and diverse boundary conditions. It yields notable improvement in bending stiffness, which manifests in a decrease of displacement by approximately 93% in comparison to the reference model with an equivalent total mass. Nonetheless, for the specific load case considered, the engineering approach yields the least displacement. Although certain applications may favor conventional methods, the presented approach holds promise for scenarios subjected to varying stresses, necessitating lightweight and robust solutions. Full article

Research into how fish and other aquatic organisms propel themselves offers valuable natural references for enhancing technology related to underwater devices like vehicles, propellers, and biomimetic robotics. Additionally, such research provides insights into fish evolution and ecological dynamics. This work carried out a numerical investigation of the most relevant dimensionless parameters in a fish swimming environment (Reynolds $Re$, Strouhal $St$, and $Slip$ numbers) to provide valuable knowledge in terms of biomechanics behavior. Thus, a three-dimensional numerical study of the fish-like lambari, a BCF swimmer with carangiform kinematics, was conducted using the URANS approach with the k-$\omega$-SST transition turbulence closure model in the OpenFOAM software. In this study, we initially reported the equilibrium Strouhal number, which is represented by $S{t}^{\ast }$, and its dependence on the Reynolds number, denoted as $Re$. This was performed following a power–law relationship of $St\propto R{e}^{(-\alpha )}$. We also conducted a comprehensive analysis of the hydrodynamic forces and the effect of body undulation in fish on the production of swimming drag and thrust. Additionally, we computed propulsive and quasi-propulsive efficiencies, as well as examined the influence of the Reynolds number and $Slip$ number on fish performance. Finally, we performed a vortex dynamics analysis, in which different wake configurations were revealed under variations of the dimensionless parameters $St$, $Re$, and $Slip$. Furthermore, we explored the relationship between the generation of a leading-edge vortex via the caudal fin and the peak thrust production within the motion cycle. Full article

We have designed and synthesized a series of bioinspired pyrano[2,3-f]coumarin-based Calanolide A analogs with anti-HIV activity. The design of these new calanolide analogs involved incorporating nitrogen heterocycles or aromatic groups in lieu of ring C, effectively mimicking and preserving their bioactive properties. Three directions for the synthesis were explored: reaction of 5-hydroxy-2,2-dimethyl-10-propyl-2H,8H-pyrano[2,3-f]chromen-8-one with (i) 1,2,4-triazines, (ii) sulfonylation followed by Suzuki cross-coupling with (het)aryl boronic acids, and (iii) aminomethylation by Mannich reaction. Antiviral assay of the synthesized compounds showed that compound 4 has moderate activity against HIV-1 on enzymes and poor activity on the cell model. A molecular docking study demonstrates a good correlation between in silico and in vitro HIV-1 reverse transcriptase (RT) activity of the compounds when docked to the nonnucleoside RT inhibitor binding site, and alternative binding modes of the considered analogs of Calanolide A were established. Full article

The wings of birds exhibit multi-degree-of-freedom motions during flight. Among them, the flapping folding motion and chordwise passive deformation of the wings are prominent features of large birds in flight, contributing to their exceptional flight capabilities. This article presents a method for the fast and accurate calculation of folding passive torsional flapping wings in the early design stage. The method utilizes the unsteady three-dimensional panel method to solve the aerodynamic force and the linear beam element model to analyze the fluid–structure coupling problem. Performance comparisons of folding flapping wings with different kinematics are conducted, and the effects of various kinematic parameters on folding flapping wings are analyzed. The results indicate that kinematic parameters significantly influence the lift coefficient, thrust coefficient, and propulsion efficiency. Selecting the appropriate kinematic and geometric parameters is crucial for enhancing the efficiency of the folding flapping wing. Full article

The essence of biomimetics in human–computer interaction (HCI) is the inspiration derived from natural systems to drive innovations in modern-day technologies. With this in mind, this paper introduces a biomimetic adaptive pure pursuit (A-PP) algorithm tailored for the four-wheel differential drive robot (FWDDR). Drawing inspiration from the intricate natural motions subjected to constraints, the FWDDR’s kinematic model mirrors non-holonomic constraints found in biological entities. Recognizing the limitations of traditional pure pursuit (PP) algorithms, which often mimic a static behavioral approach, our proposed A-PP algorithm infuses adaptive techniques observed in nature. Integrated with a quadratic polynomial, this algorithm introduces adaptability in both lateral and longitudinal dimensions. Experimental validations demonstrate that our biomimetically inspired A-PP approach achieves superior path-following accuracy, mirroring the efficiency and fluidity seen in natural organisms. Full article

In response to the need for multiple complete bearing degradation datasets in traditional deep learning networks to predict the impact on individual bearings, a novel deep learning-based rolling bearing remaining life prediction method is proposed in the absence of fully degraded bearng data. This method involves processing the raw vibration data through Channel-wise Attention Encoder (CAE) from the Encoder-Channel Attention (ECA), extracting features related to mutual correlation and relevance, selecting the desired characteristics, and incorporating the selected features into the constructed Autoformer-based time prediction model to forecast the degradation trend of bearings’ remaining time. The feature extraction method proposed in this approach outperforms CAE and multilayer perceptual-Attention Encoder in terms of feature extraction capabilities, resulting in reductions of 0.0059 and 0.0402 in mean square error, respectively. Additionally, the indirect prediction approach for the degradation trend of the target bearing demonstrates higher accuracy compared to Informer and Transformer models, with mean square error reductions of 0.3352 and 0.1174, respectively. This suggests that the combined deep learning model proposed in this paper for predicting rolling bearing life may be a more effective life prediction method deserving further research and application. Full article

With the wide application of mobile robots, mobile robot path planning (MRPP) has attracted the attention of scholars, and many metaheuristic algorithms have been used to solve MRPP. Swarm-based algorithms are suitable for solving MRPP due to their population-based computational approach. Hence, this paper utilizes the Whale Optimization Algorithm (WOA) to address the problem, aiming to improve the solution accuracy. Whale optimization algorithm (WOA) is an algorithm that imitates whale foraging behavior, and the firefly algorithm (FA) is an algorithm that imitates firefly behavior. This paper proposes a hybrid firefly-whale optimization algorithm (FWOA) based on multi-population and opposite-based learning using the above algorithms. This algorithm can quickly find the optimal path in the complex mobile robot working environment and can balance exploitation and exploration. In order to verify the FWOA’s performance, 23 benchmark functions have been used to test the FWOA, and they are used to optimize the MRPP. The FWOA is compared with ten other classical metaheuristic algorithms. The results clearly highlight the remarkable performance of the Whale Optimization Algorithm (WOA) in terms of convergence speed and exploration capability, surpassing other algorithms. Consequently, when compared to the most advanced metaheuristic algorithm, FWOA proves to be a strong competitor. Full article

Inspired by the natural skeletal muscles, this paper presents a novel shape memory alloy-based artificial muscle matrix (AMM) with advantages of a large output force and displacement, flexibility, and compactness. According to the composition of the AMM, we propose a matrix control strategy to achieve independent control of the output force and displacement of the AMM. Based on the kinematics simulation and experiments, we obtained the output displacement and bearing capacity of the smart digital structure (SDS) and confirmed the effectiveness of the matrix control strategy to achieve force and displacement output independently and controllably. A bionic mechanical ankle actuated by AMM was proposed to demonstrate the actuating capability of the AMM. Experimental results show that the angle and force of the bionic mechanical ankle are output independently and have a significant gradient. In addition, by using a self-sensing method (resistance self-feedback) and PD control strategy, the output angle and force of the bionic mechanical ankle can be maintained for a long time without overheating of the AMM. Full article

Reinforcement learning (RL)-based controllers have been applied to the high-speed movement of quadruped robots on uneven terrains. The external disturbances increase as the robot moves faster on such terrains, affecting the stability of the robot. Many existing RL-based methods adopt higher control frequencies to respond quickly to the disturbance, which requires a significant computational cost. We propose a control framework that consists of an RL-based control policy updating at a low frequency and a model-based joint controller updating at a high frequency. Unlike previous methods, our policy outputs the control law for each joint, executed by the corresponding high-frequency joint controller to reduce the impact of external disturbances on the robot. We evaluated our method on various simulated terrains with height differences of up to 6 cm. We achieved a running motion of $1.8$ m/s in the simulation using the Unitree A1 quadruped. The RL-based control policy updates at 50 Hz with a latency of 20 ms, while the model-based joint controller runs at 1000 Hz. The experimental results show that the proposed framework can overcome the latency caused by low-frequency updates, making it applicable for real-robot deployment. Full article

This study focused on designing a single-degree-of-freedom (1-DoF) mechanism emulating the wings of rock pigeons. Three wing models were created: one with REAL feathers from a pigeon, and the other two models with 3D-printed artificial remiges made using different strengths of material, PLA and PETG. Aerodynamic performance was assessed in a wind tunnel under both stationary (0 m/s) and cruising speed (16 m/s) with flapping frequencies from 3.0 to 6.0 Hz. The stiffness of remiges was examined through three-point bending tests. The artificial feathers made of PLA have greater rigidity than REAL feathers, while PETG, on the other hand, exhibits the weakest strength. At cruising speed, although the artificial feathers exhibit more noticeable feather splitting and more pronounced fluctuations in lift during the flapping process compared to REAL feathers due to the differences in weight and stiffness distribution, the PETG feathered wing showed the highest lift enhancement (28% of pigeon body weight), while the PLA feathered wing had high thrust but doubled drag, making them inefficient in cruising. The PETG feathered wing provided better propulsion efficiency than the REAL feathered wing. Despite their weight, artificial feathered wings outperformed REAL feathers in 1-DoF flapping motion. This study shows the potential for artificial feathers in improving the flight performance of Flapping Wing Micro Air Vehicles (FWMAVs). Full article

Automated guided vehicles (AGVs) are vital for optimizing the transport of material in modern industry. AGVs have been widely used in production, logistics, transportation, and commerce, enhancing productivity, lowering labor costs, improving energy efficiency, and ensuring safety. However, path planning for AGVs in complex and dynamic environments remains challenging due to the computation of obstacle avoidance and efficient transport. This study proposes a novel approach that combines multi-objective particle swarm optimization (MOPSO) and the dynamic-window approach (DWA) to enhance AGV path planning. Optimal AGV trajectories considering energy consumption, travel time, and collision avoidance were used to model the multi-objective functions for dealing with the outcome-feasible optimal solution. Empirical findings and results demonstrate the approach’s effectiveness and efficiency, highlighting its potential for improving AGV navigation in real-world scenarios. Full article

The severe climate and energy issues require more environmentally friendly and efficient cooling methods. Radiative cooling offers a cooling solution with significant advantages. However, current radiative cooling technologies focus primarily on seeking perfect materials to achieve complete wavelength absorption. However, numerous research studies have shown that achieving such a perfect scenario is not feasible. Here, inspired by the surface of the Cerambycini Latreille, the inherent mechanism of radiative cooling functionality in the unique structure of these hairs is revealed using effective medium theory and Finite Difference Time Domain (FDTD) optical simulation analysis. Through alkaline etching and template methods, a biomimetic radiative cooling film (BRCF) was successfully fabricated. The BRCF not only efficiently reflects solar radiation but also enhances absorption in the atmospheric window wavelength range. The radiative cooling mechanism proposed in this study and the BRCF presented here may inspire researchers to further explore the field of structural radiative cooling. Full article

Biological fish often swim in a schooling manner, the mechanism of which comes from the fact that these schooling movements can improve the fishes’ hydrodynamic efficiency. Inspired by this phenomenon, a target-following control framework for a biomimetic autonomous system is proposed in this paper. Firstly, a following motion model is established based on the mechanism of fish schooling swimming, in which the follower robotic fish keeps a certain distance and orientation from the leader robotic fish. Second, by incorporating a predictive concept into reinforcement learning, a predictive deep deterministic policy gradient-following controller is provided with the normalized state space, action space, reward, and prediction design. It can avoid overshoot to a certain extent. A nonlinear model predictive controller is designed and can be selected for the follower robotic fish, together with the predictive reinforcement learning. Finally, extensive simulations are conducted, including the fix point and dynamic target following for single robotic fish, as well as cooperative following with the leader robotic fish. The obtained results indicate the effectiveness of the proposed methods, providing a valuable sight for the cooperative control of underwater robots to explore the ocean. Full article