Biomimetics, Volume 9, Issue 6 (June 2024) – 48 articles

The protection of plants in mountainous and hilly areas differs from that in plain areas due to the complex terrain, which divides the work plot into many narrow plots. When designing the path planning method for plant protection UAVs, it is important to consider the generality in different working environments. To address issues such as poor path optimization, long operation time, and excessive iterations required by traditional swarm intelligence algorithms, this paper proposes a bionic three-dimensional path planning algorithm for plant protection UAVs. This algorithm aims to plan safe and optimal flight paths between work plots obstructed by multiple obstacle areas. Inspired by krill group behavior and based on group intelligence algorithm theory, the bionic three-dimensional path planning algorithm consists of three states: “foraging behavior”, “avoiding enemy behavior”, and “cruising behavior”. The current position information of the UAV in the working environment is used to switch between these states, and the optimal path is found after several iterations, which realizes the adaptive global and local convergence of the track planning, and improves the convergence speed and accuracy of the algorithm. The optimal flight path is obtained by smoothing using a third-order B-spline curve. Three sets of comparative simulation experiments are designed to verify the performance of this proposed algorithm. The results show that the bionic swarm intelligence algorithm based on krill swarm behavior reduces the path length by 1.1~17.5%, the operation time by 27.56~75.15%, the path energy consumption by 13.91~27.35%, and the number of iterations by 46~75% compared with the existing algorithms. The proposed algorithm can shorten the distance of the planned path more effectively, improve the real-time performance, and reduce the energy consumption. Full article

A series of wind tunnel tests were performed to investigate the effect of turbulent inflows on the aerodynamic characteristics of variously modified trough incident leading-edge-protuberanced (LEP) wing configurations at various turbulence intensities. A self-developed passive grid made of parallel arrays of round bars was placed at different locations of the wind tunnel to generate desired turbulence intensity. The aerodynamic forces acting over the trough incidence LEP wing configuration where obtained from surface pressure measurements made over the wing at different turbulence intensities using an MPS4264 Scanivalve simultaneous pressure scanner corresponding to a sampling frequency of 700 Hz. All the test models were tested at a wide range of angles of attack ranging between $0^{°}\le \alpha \le {90}^{°}$ at turbulence intensities varying between 5.90% ≤ TI ≤ 10.54%. Results revealed that the time-averaged mean coefficient of lift (C_L) increased with the increase in the turbulence intensity associated with smooth stall characteristics rendering the modified LEP test models advantageous. Furthermore, based on the surface pressure coefficients, the underlying dynamics behind the stall delay tendency were discussed. Additionally, attempts were made to statistically quantify the aerodynamic forces using standard deviation at both the pre-stall and the post-stall angles. Full article

Enhancing human–robot interaction has been a primary focus in robotic gait assistance, with a thorough understanding of human motion being crucial for personalizing gait assistance. Traditional gait trajectory references from Clinical Gait Analysis (CGA) face limitations due to their inability to account for individual variability. Recent advancements in gait pattern generators, integrating regression models and Artificial Neural Network (ANN) techniques, have aimed at providing more personalized and dynamically adaptable solutions. This article introduces a novel approach that expands regression and ANN applications beyond mere angular estimations to include three-dimensional spatial predictions. Unlike previous methods, our approach provides comprehensive spatial trajectories for hip, knee and ankle tailored to individual kinematics, significantly enhancing end-effector rehabilitation robotic devices. Our models achieve state-of-the-art accuracy: overall RMSE of 13.40 mm and a correlation coefficient of 0.92 for the regression model, and RMSE of 12.57 mm and a correlation of 0.99 for the Long Short-Term Memory (LSTM) model. These advancements underscore the potential of these models to offer more personalized gait trajectory assistance, improving human–robot interactions. Full article

Path planning is an important research direction in the field of robotics; however, with the advancement of modern science and technology, the study of efficient, stable, and safe path-planning technology has become a realistic need in the field of robotics research. This paper introduces an improved sparrow search algorithm (ISSA) with a fusion strategy to further improve the ability to solve challenging tasks. First, the sparrow population is initialized using circle chaotic mapping to enhance diversity. Second, the location update formula of the northern goshawk is used in the exploration phase to replace the sparrow search algorithm’s location update formula in the security situation. This improves the discoverer model’s search breadth in the solution space and optimizes the problem-solving efficiency. Third, the algorithm adopts the Lévy flight strategy to improve the global optimization ability, so that the sparrow jumps out of the local optimum in the later stage of iteration. Finally, the adaptive T-distribution mutation strategy enhances the local exploration ability in late iterations, thus improving the sparrow search algorithm’s convergence speed. This was applied to the CEC2021 function set and compared with other standard intelligent optimization algorithms to test its performance. In addition, the ISSA was implemented in the path-planning problem of mobile robots. The comparative study shows that the proposed algorithm is superior to the SSA in terms of path length, running time, path optimality, and stability. The results show that the proposed method is more effective, robust, and feasible in mobile robot path planning. Full article

Causal discovery is central to human cognition, and learning directed acyclic graphs (DAGs) is its foundation. Recently, many nature-inspired meta-heuristic optimization algorithms have been proposed to serve as the basis for DAG learning. However, a single meta-heuristic algorithm requires specific domain knowledge and empirical parameter tuning and cannot guarantee good performance in all cases. Hyper-heuristics provide an alternative methodology to meta-heuristics, enabling multiple heuristic algorithms to be combined and optimized to achieve better generalization ability. In this paper, we propose a multi-population choice function hyper-heuristic to discover the causal relationships encoded in a DAG. This algorithm provides a reasonable solution for combining structural priors or possible expert knowledge with swarm intelligence. Under a linear structural equation model (SEM), we first identify the partial v-structures through partial correlation analysis as the structural priors of the next nature-inspired swarm intelligence approach. Then, through partial correlation analysis, we can limit the search space. Experimental results demonstrate the effectiveness of the proposed methods compared to the earlier state-of-the-art methods on six standard networks. Full article

A nature-inspired approach was employed through the development of dopamine-modified epoxy coating for anti-icing applications. The strong affinity of dopamine’s catechol groups for hydrogen bonding with water molecules at the ice/coating interface was utilized to induce an aqueous quasi-liquid layer (QLL) on the surface of the icephobic coatings, thereby reducing their ice adhesion strength. Epoxy resin modification was studied by attenuated total reflectance infrared spectroscopy (ATR-FTIR) and nuclear magnetic resonance spectroscopy (NMR). The surface and mechanical properties of the prepared coatings were studied by different characterization techniques. Low-temperature ATR-FTIR was employed to study the presence of QLL on the coating’s surface. Moreover, the freezing delay time and temperature of water droplets on the coatings were evaluated along with push-off and centrifuge ice adhesion strength to evaluate their icephobic properties. The surface of dopamine-modified epoxy coating presented enhanced hydrophilicity and QLL formation, addressed as the main reason for its remarkable icephobicity. The results demonstrated the potential of dopamine-modified epoxy resin as an effective binder for icephobic coatings, offering notable ice nucleation delay time (1316 s) and temperature (−19.7 °C), reduced ice adhesion strength (less than 40 kPa), and an ice adhesion reduction factor of 7.2 compared to the unmodified coating. Full article

Background and Objectives: Two of the most exciting new technologies are biotechnology and nanotechnology. The science of nanostructures, or nanotechnology, is concerned with the development, testing, and use of structures and molecules with nanoscale dimensions ranging from 1 to 100 nm. The development of materials and tools with high specificity that interact directly at the subcellular level is what makes nanotechnology valuable in the medical sciences. At the cellular or tissue level, this might be converted into focused clinical applications with the greatest possible therapeutic benefits and the fewest possible side effects. The purpose of the present study was to review the literature and explore the applicability of the nanostructured materials in the process of the regeneration of the soft and hard tissues of the oral cavity. Materials and Methods: An electronic search of articles was conducted in several databases, such as PubMed, Embase, and Web of Science, to conduct this study, and the 183 articles that were discovered were chosen and examined, and only 22 articles met the inclusion criteria in this review. Results: The findings of this study demonstrate that using nanoparticles can improve the mechanical properties, biocompatibility, and osteoinductivity of biomaterials. Conclusions: Most recently, breakthroughs in tissue engineering and nanotechnology have led to significant advancements in the design and production of bone graft substitutes and hold tremendous promise for the treatment of bone abnormalities. The creation of intelligent nanostructured materials is essential for various applications and therapies, as it allows for the precise and long-term delivery of medication, which yields better results. Full article

In the biomedical fields of bone regenerative therapy, the immobilization of proteins on the bioceramic particles to maintain their highly ordered structures is significantly important. In this review, we comprehensively discussed the importance of the specific surface layer, which can be called “non-apatitic layer”, affecting the immobilization of proteins on particles such as hydroxyapatite and amorphous silica. It was suggested that the water molecules and ions contained in the non-apatitic layer can determine and control the protein immobilization states. In amorphous silica particles, the direct interactions between proteins and silanol groups make it difficult to immobilize the proteins and maintain their highly ordered structures. Thus, the importance of the formation of a surface layer consisting of water molecules and ions (i.e., a non-apatitic layer) on the particle surfaces for immobilizing proteins and maintaining their highly ordered structures was suggested and described. In particular, chlorine-containing amorphous silica particles were also described, which can effectively form the surface layer of protein immobilization carriers. The design of the bio-interactive and bio-compatible surfaces for protein immobilization while maintaining the highly ordered structures will improve cell adhesion and tissue formation, thereby contributing to the construction of social infrastructures to support super-aged society. Full article

As technology rapidly evolves, the application of bipedal robots in various environments has widely expanded. These robots, compared to their wheeled counterparts, exhibit a greater degree of freedom and a higher complexity in control, making the challenge of maintaining balance and stability under changing wind speeds particularly intricate. Overcoming this challenge is critical as it enables bipedal robots to sustain more stable gaits during outdoor tasks, thereby increasing safety and enhancing operational efficiency in outdoor settings. To transcend the constraints of existing methodologies, this research introduces an adaptive bio-inspired exploration framework for bipedal robots facing wind disturbances, which is based on the Deep Deterministic Policy Gradient (DDPG) approach. This framework allows the robots to perceive their bodily states through wind force inputs and adaptively modify their exploration coefficients. Additionally, to address the convergence challenges posed by sparse rewards, this study incorporates Hindsight Experience Replay (HER) and a reward-reshaping strategy to provide safer and more effective training guidance for the agents. Simulation outcomes reveal that robots utilizing this advanced method can more swiftly explore behaviors that contribute to stability in complex conditions, and demonstrate improvements in training speed and walking distance over traditional DDPG algorithms. Full article

This paper presents a biomimetic fish robot featuring a flexible spine driven by cables, which integrates the cable-driven mechanism with a flexible spine. The drive system separates the body and tail fin drives for control, offering enhanced flexibility and ease in achieving phase difference control between the body and tail fin movements compared to the conventional servo motor cascaded structure. A prototype of the biomimetic fish robot was developed, accompanied by the establishment of a kinematic model. Based on this model, a control method for the biomimetic fish is proposed. Additionally, we introduce the concept of prestress to establish a numerical model for the biomimetic fish. Using multi-physical field simulation software, we simulate the two-dimensional autonomous swimming process of the biomimetic fish under different flapping frequencies and solve for its swimming characteristics as well as hydrodynamic properties. Both the simulation and experimental results validate the accuracy of our kinematic model. Full article

This study aims to support designers in developing transformative solutions in the engineering discipline using the Design-by-Analogy ideation method. Design-by-Analogy involves drawing inspiration from the source domain and applying it to the target domain. Based on the conceptual distance between the two domains, analogies are classified as biological—(natural), cross—(distant-engineering), and within—(near-engineering) domain analogies. Real-world scenarios involve designers selecting analogies after seeking them across multiple domains. These selected analogies significantly influence the produced designs. However, the selection criteria of the analogy domain are unexplored in design research. We address this gap by investigating: (a) the influence of analogy domains on their selection frequency; and (b) the relationship between the frequency of selecting analogies from specific domains and the novelty of designs. The experiment involved twenty-six teams of novice product designers, who solved design problems aided by one analogical source from each domain. The results showed that biological analogies were frequently selected. While biological-domain analogies significantly increased the novelty of designs compared to the within-domain ones; no significant difference was found between the biological- and cross-domain analogies, suggesting that middle-domain analogies can be as effective as far-domain ones. The findings can support technological innovation by aiding the development of analogy search databases. Full article

The beetle, of the order Coleoptera, possesses outstanding flight capabilities. After completing flight, they can fold their hindwings under the elytra and swiftly unfold them again when they take off. This sophisticated hindwing structure is a result of biological evolution, showcasing the strong environmental adaptability of this species. The beetle’s hindwings can provide biomimetic inspiration for the design of flapping-wing micro air vehicles (FWMAVs). In this study, the Asian ladybird (Harmonia axyridis Pallas) was chosen as the bionic research object. Various kinematic parameters of its flapping flight were analyzed, including the flight characteristics of the hindwings, wing tip motion trajectories, and aerodynamic characteristics. Based on these results, a flapping kinematic model of the Asian ladybird was established. Then, three bionic deployable wing models were designed and their structural mechanical properties were analyzed. The results show that the structure of wing vein bars determined the mechanical properties of the bionic wing. This study can provide a theoretical basis and technical reference for further bionic wing design. Full article

Polylactic acid (PLA)-based cylindrical membranes for the controlled release of fluorescein sodium salt (FS) were prepared by bioprinting on systems with an initial FS concentration of 0.003763 gdm⁻³ and 37.63 gdm⁻³, and the drug release process was monitored in a bath at 37 °C. Photographs, acquired at regular intervals during the process, revealed marked osmotic swelling of the polymer. Osmotic swelling consists in the enlargement of the polymer structure and due to the influx of water molecules across the membrane. The cylindrical PLA membrane starts to significantly swell once a certain threshold range is crossed. Important amounts of FS can dissolve under these radically changed circumstances, and the dissolved FS molecules are mobile enough to diffuse out of the cylinder, thus allowing drug release. As a matter of fact, in this investigation, we ascertained that polymer swelling promotes the mass transport phenomenon by altering the conditions for drug dissolution and diffusion, hence facilitating FS release after a specific lag time. Furthermore, in order to compare the release kinetics, the half-release time, $t_{0.5}$, was taken into consideration. The data of this study evidence that, while increasing the initial concentration of FS by three orders of magnitude, the time parameter, $t_{0.5}$, is only reduced by 5/6. In addition, the yield of the release process is drastically reduced due to the strong aggregation ability of the dye. Finally, it is demonstrated that a compressed exponential kinetic model fits the experimental data well despite the varying physical conditions. Full article

This paper presents an enhanced crayfish optimization algorithm (ECOA). The ECOA includes four improvement strategies. Firstly, the Halton sequence was used to improve the population initialization of the crayfish optimization algorithm. Furthermore, the quasi opposition-based learning strategy is introduced to generate the opposite solution of the population, increasing the algorithm’s searching ability. Thirdly, the elite factor guides the predation stage to avoid blindness in this stage. Finally, the fish aggregation device effect is introduced to increase the ability of the algorithm to jump out of the local optimal. This paper performed tests on the widely used IEEE CEC2019 test function set to verify the validity of the proposed ECOA method. The experimental results show that the proposed ECOA has a faster convergence speed, greater performance stability, and a stronger ability to jump out of local optimal compared with other popular algorithms. Finally, the ECOA was applied to two real-world engineering optimization problems, verifying its ability to solve practical optimization problems and its superiority compared to other algorithms. Full article

Octopus tentacles are equipped with numerous suckers, wherein the muscles contract and expel air, creating a pressure difference. Subsequently, when the muscular tension is released, objects can be securely adhered to. This mechanism has been widely employed in the development of adhesive systems. However, most existing octopus-inspired structures are passive and static, lacking dynamic and controllable adhesive switching capabilities and excellent locomotion performance. Here, we present an octopus-inspired soft robot (OISR). Attracted by the magnetic gradient field, the suction cup structure inside the OISR can generate a strong adsorption force, producing dynamically controllable adsorption and separation in the gastrointestinal (GI) tract. The experimental results show that the OISR has a variety of controllable locomotion behaviors, including quick scrolling and rolling motions, generating fast locomotion responses, rolling over gastric folds, and tumbling and swimming inside liquids. By carrying drugs that are absorbable by GI epithelial cells to target areas, the OISR enables continuous drug delivery at lesions or inflamed regions of the GI tract. This research may be a potential approach for achieving localized slow drug release within the GI tract. Full article

A numerical method for generating dynamic stall using ANSYS Fluent and a user-defined function (UDF), with the complete script shared for reference, is introduced and tested. The study draws inspiration from bird flight, exploring dynamic stall as a method for achieving enhanced aerodynamic performance. The numerical method was tested on NACA 0012 airfoils with corresponding chord lengths of $c_1=40\mathrm{m}\mathrm{m}$, $c_2=150\mathrm{m}\mathrm{m}$, and $c_3=300\mathrm{m}\mathrm{m}$ at Reynolds numbers ranging from ${Re}_1=2.8\times {10}^4$ up to ${Re}_5=1.04\times {10}^6$. Airfoil oscillations were settled for all cases at $\omega =0.55\mathrm{H}\mathrm{z}$. Detached eddy simulation (DES) is employed as the turbulence model for the simulations presented, ensuring the accurate representation of the flow characteristics and dynamic stall phenomena. The study provides a detailed methodology, encouraging further exploration by researchers, especially young academics and students. Full article

The ability of bone biomaterials to promote osteogenic differentiation is crucial for the repair and regeneration of osseous tissue. The development of a temporary bone substitute is of major importance in enhancing the growth and differentiation of human-derived stem cells into an osteogenic lineage. In this study, nanocomposite hydrogels composed of gelatin methacryloyl (GelMA), bioactive glass (BG), and multiwall carbon nanotubes (MWCNT) were developed to create a bone biomaterial that mimics the structural and electrically conductive nature of bone that can promote the differentiation of human-derived stem cells. GelMA-BG-MWCNT nanocomposite hydrogels supported mesenchymal stem cells derived from human induced pluripotent stem cells, hereinafter named iMSCs. Cell adhesion was improved upon coating nanocomposite hydrogels with fibronectin and was further enhanced when seeding pre-differentiated iMSCs. Osteogenic differentiation and mature mineralization were promoted in GelMA-BG-MWCNT nanocomposite hydrogels and were most evidently observed in the 70-30-2 hydrogels, which could be due to the stiff topography characteristic from the addition of MWCNT. Overall, the results of this study showed that GelMA-BG-MWCNT nanocomposite hydrogels coated with fibronectin possessed a favorable environment in which pre-differentiated iMSCs could better attach, proliferate, and further mature into an osteogenic lineage, which was crucial for the repair and regeneration of bone. Full article

Mycelium-based green composites (MBCs) represent an eco-friendly material innovation with vast potential across diverse applications. This paper provides a thorough review of the factors influencing the production and properties of MBCs, with a particular focus on interdisciplinary collaboration and long-term sustainability goals. It delves into critical aspects such as fungal species selection, substrate type selection, substrate preparation, optimal conditions, dehydrating methods, post-processing techniques, mold design, sterilization processes, cost comparison, key recommendations, and other necessary factors. Regarding fungal species selection, the paper highlights the significance of considering factors like mycelium species, decay type, hyphal network systems, growth rate, and bonding properties in ensuring the safety and suitability of MBCs fabrication. Substrate type selection is discussed, emphasizing the importance of chemical characteristics such as cellulose, hemicellulose, lignin content, pH, organic carbon, total nitrogen, and the C: N ratio in determining mycelium growth and MBC properties. Substrate preparation methods, optimal growth conditions, and post-processing techniques are thoroughly examined, along with their impacts on MBCs quality and performance. Moreover, the paper discusses the importance of designing molds and implementing effective sterilization processes to ensure clean environments for mycelium growth. It also evaluates the costs associated with MBCs production compared to traditional materials, highlighting potential cost savings and economic advantages. Additionally, the paper provides key recommendations and precautions for improving MBC properties, including addressing fungal strain degeneration, encouraging research collaboration, establishing biosecurity protocols, ensuring regulatory compliance, optimizing storage conditions, implementing waste management practices, conducting life cycle assessments, and suggesting parameters for desirable MBC properties. Overall, this review offers valuable insights into the complex interplay of factors influencing MBCs production and provides guidance for optimizing processes to achieve sustainable, high-quality composites for diverse applications. Full article

The vibrissae of harbor seals exhibit a distinct three-dimensional structure compared to circular cylinders, resulting in a wave-shaped configuration that effectively reduces drag and suppresses vortex shedding in the wake. However, this unique cylinder design has not yet been applied to wind power technologies. Therefore, this study applies this concept to the design of downwind wind turbines and employs wind tunnel testing to compare the wake flow characteristics of a single-cylinder model while also investigating the output power and wake performance of the model wind turbine. Herein, we demonstrate that in the single-cylinder test, the bionic case shows reduced turbulence intensity in its wake compared to that observed with the circular cylinder case. The difference in the energy distribution in the frequency domain behind the cylinder was mainly manifested in the near-wake region. Moreover, our findings indicate that differences in power coefficient are predominantly noticeable with high tip speed ratios. Furthermore, as output power increases, this bionic cylindrical structure induces greater velocity deficit and higher turbulence intensity behind the rotor. These results provide valuable insights for optimizing aerodynamic designs of wind turbines towards achieving enhanced efficiency for converting wind energy. Full article

To mimic the homeostatic functionality of biological neurons, a split-gate field-effect transistor (S-G FET) with a charge trap layer is proposed within a neuron circuit. By adjusting the number of charges trapped in the Si₃N₄ layer, the threshold voltage (V_th) of the S-G FET changes. To prevent degradation of the gate dielectric due to program/erase pulses, the gates for read operation and V_th control were separated through the fin structure. A circuit that modulates the width and amplitude of the pulse was constructed to generate a Program/Erase pulse for the S-G FET as the output pulse of the neuron circuit. By adjusting the V_th of the neuron circuit, the firing rate can be lowered by increasing the V_th of the neuron circuit with a high firing rate. To verify the performance of the neural network based on S-G FET, a simulation of online unsupervised learning and classification in a 2-layer SNN is performed. The results show that the recognition rate was improved by 8% by increasing the threshold of the neuron circuit fired. Full article

As the fields of engineering, energy, and geology become increasingly complex, decision makers face escalating challenges that require skilled solutions to meet practical production needs. Evolutionary algorithms, inspired by biological evolution, have emerged as powerful methods for tackling intricate optimization problems without relying on gradient data. Among these, the tree-seed algorithm (TSA) distinguishes itself due to its unique mechanism and efficient searching capabilities. However, an imbalance between its exploitation and exploration phases can lead it to be stuck in local optima, impeding the discovery of globally optimal solutions. This study introduces an improved TSA that incorporates water-cycling and quantum rotation-gate mechanisms. These enhancements assist the algorithm in escaping local peaks and achieving a more harmonious balance between its exploitation and exploration phases. Comparative experimental evaluations, using the CEC 2017 benchmarks and a well-known metaheuristic algorithm, demonstrate the upgraded algorithm’s faster convergence rate and enhanced ability to locate global optima. Additionally, its application in optimizing reservoir production models underscores its superior performance compared to competing methods, further validating its real-world optimization capabilities. Full article

Mycelium-based composites (MBCs) are biomaterials with scientifically proven potential to improve sustainability in construction. Although mycelium-based products are not entirely new, their use in engineering presents challenges due to the inherent properties of this fungal material. This study investigated professional architects’ and interior designers’ perceptions of MBCs, focusing on familiarity, aesthetic appeal, and willingness to use. The first phase of the survey explored respondents’ views on material-related ecological design principles. In the second phase, respondents evaluated ten small architectural objects crafted from MBCs, focusing on form, detail, and visual appeal. The last phase of the survey measured their interest in using mycelium in their design work. The results revealed that MBCs were relatively unknown among the surveyed professionals; only every second respondent knew this material. Despite this, 90% found MBCs visually appealing after seeing the examples. Interestingly, the natural, unprocessed appearance of the material was assessed as less aesthetically pleasing, with thermal treatment improving its perceived value. Architects were more receptive to using MBCs in their professional projects for customers than for personal use. This observation points to a ‘double standard’: professional architects are more open to using MBCs in projects not intended for their own use. Full article

Dual humanoid robot collaborative control systems possess better flexibility and adaptability in complex environments due to their similar structures to humans. This paper adopts a distributed model predictive controller based on the leader–follower approach to address the collaborative transportation control issue of dual humanoid robots. In the dual-robot collaborative control system, network latency issues may arise due to unstable network conditions, affecting the consistency of dual-robot collaboration. To solve this issue, a communication protocol was constructed through socket communication for dual-robot collaborative consistency, thereby resolving the problem of consistency in dual humanoid robot collaboration. Additionally, due to the complex structure of humanoid robots, there are deficiencies in position tracking accuracy during movement. To address the poor accuracy in position tracking, this paper proposes a distributed model predictive control that considers historical cumulative error, thus enhancing the position tracking accuracy of dual-robot collaborative control. Full article

In humanitarian aid scenarios, the model of cumulative capacitated vehicle routing problem can be used in vehicle scheduling, aiming at delivering materials to recipients as quickly as possible, thus minimizing their wait time. Traditional approaches focus on this metric, but practical implementations must also consider factors such as driver labor intensity and the capacity for on-site decision-making. To evaluate driver workload, the operation times of relief vehicles are typically used, and multi-objective modeling is employed to facilitate on-site decision-making. This paper introduces a multi-objective cumulative capacitated vehicle routing problem considering operation time (MO-CCVRP-OT). Our model is bi-objective, aiming to minimize both the cumulative wait time of disaster-affected areas and the extra expenditures incurred by the excess operation time of rescue vehicles. Based on the traditional grey wolf optimizer algorithm, this paper proposes a dynamic grey wolf optimizer algorithm with floating 2-opt (DGWO-F2OPT), which combines real number encoding with an equal-division random key and ROV rules for decoding; in addition, a dynamic non-dominated solution set update strategy is introduced. To solve MO-CCVRP-OT efficiently and increase the algorithm’s convergence speed, a multi-objective improved floating 2-opt (F2OPT) local search strategy is proposed. The utopia optimum solution of DGWO-F2OPT has an average value of two fitness values that is 6.22% lower than that of DGWO-2OPT. DGWO-F2OPT’s average fitness value in the algorithm comparison trials is 16.49% less than that of NS-2OPT. In the model comparison studies, MO-CCVRP-OT is 18.72% closer to the utopian point in Euclidean distance than CVRP-OT. Full article

We propose a genetic algorithm for optimizing oil skimmer assignments, introducing a tailored repair operation for constrained assignments. Methods essentially involve simulation-based evaluation to ensure adherence to South Korea’s regulations. Results show that the optimized assignments, compared to current ones, reduced work time on average and led to a significant reduction in total skimmer capacity. Additionally, we present a deep neural network-based surrogate model, greatly enhancing efficiency compared to simulation-based optimization. Addressing inefficiencies in mobilizing locations that store oil skimmers, further optimization aimed to minimize mobilized locations and was validated through scenario-based simulations resembling actual situations. Based on major oil spills in South Korea, this strategy significantly reduced work time and required locations. These findings demonstrate the effectiveness of the proposed genetic algorithm and mobilized location minimization strategy in enhancing oil spill response operations. Full article

Submerged aquatic vegetation plays a fundamental role as a habitat for the biodiversity of marine species. To carry out the research and monitoring of submerged aquatic vegetation more efficiently and accurately, it is important to use advanced technologies such as underwater robots. However, when conducting underwater missions to capture photographs and videos near submerged aquatic vegetation meadows, algae can become entangled in the propellers and cause vehicle failure. In this context, a neurobiologically inspired control architecture is proposed for the control of unmanned underwater vehicles with redundant thrusters. The proposed control architecture learns to control the underwater robot in a non-stationary environment and combines the associative learning method and vector associative map learning to generate transformations between the spatial and velocity coordinates in the robot actuator. The experimental results obtained show that the proposed control architecture exhibits notable resilience capabilities while maintaining its operation in the face of thruster failures. In the discussion of the results obtained, the importance of the proposed control architecture is highlighted in the context of the monitoring and conservation of underwater vegetation meadows. Its resilience, robustness, and adaptability capabilities make it an effective tool to face challenges and meet mission objectives in such critical environments. Full article

Ever since Varela and Maturana proposed the concept of autopoiesis as the minimal requirement for life, there has been a focus on cellular systems that erect topological boundaries to separate themselves from their surrounding environment. Here, we reconsider whether the existence of such a spatial boundary is strictly necessary for self-producing entities. This work presents a novel computational model of a minimal autopoietic system inspired by dendrites and molecular dynamic simulations in three-dimensional space. A series of simulation experiments where the metabolic pathways of a particular autocatalytic set are successively inhibited until autocatalytic entities that could be considered autopoietic are produced. These entities maintain their distinctness in an environment containing multiple identical instances of the entities without the existence of a topological boundary. This gives rise to the concept of a metabolic boundary which manifests as emergent self-selection criteria for the processes of self-production without any need for unique identifiers. However, the adoption of such a boundary comes at a cost, as these autopoietic entities are less suited to their simulated environment than their autocatalytic counterparts. Finally, this work showcases a generalized metabolism-centered approach to the study of autopoiesis that can be applied to both physical and abstract systems alike. Full article

The complex structure, chemical composition, and biomechanical properties of craniofacial cartilaginous structures make them challenging to reconstruct. Autologous grafts have limited tissue availability and can cause significant donor-site morbidity, homologous grafts often require immunosuppression, and alloplastic grafts may have high rates of infection or displacement. Furthermore, all these grafting techniques require a high level of surgical skill to ensure that the reconstruction matches the original structure. Current research indicates that additive manufacturing shows promise in overcoming these limitations. Autologous stem cells have been developed into cartilage when exposed to the appropriate growth factors and culture conditions, such as mechanical stress and oxygen deprivation. Additive manufacturing allows for increased precision when engineering scaffolds for stem cell cultures. Fine control over the porosity and structure of a material ensures adequate cell adhesion and fit between the graft and the defect. Several recent tissue engineering studies have focused on the trachea, nose, and ear, as these structures are often damaged by congenital conditions, trauma, and malignancy. This article reviews the limitations of current reconstructive techniques and the new developments in additive manufacturing for tracheal, nasal, and auricular cartilages. Full article

This work introduces a neuromorphic sensor (NS) based on force-sensing resistors (FSR) and spiking neurons for robotic systems. The proposed sensor integrates the FSR in the schematic of the spiking neuron in order to make the sensor generate spikes with a frequency that depends on the applied force. The performance of the proposed sensor is evaluated in the control of a SMA-actuated robotic finger by monitoring the force during a steady state when the finger pushes on a tweezer. For comparison purposes, we performed a similar evaluation when the SNN received input from a widely used compression load cell (CLC). The results show that the proposed FSR-based neuromorphic sensor has very good sensitivity to low forces and the function between the spiking rate and the applied force is continuous, with good variation range. However, when compared to the CLC, the response of the NS follows a logarithmic-like function with improved sensitivity for small forces. In addition, the power consumption of NS is 128 µW that is 270 times lower than that of the CLC which needs 3.5 mW to operate. These characteristics make the neuromorphic sensor with FSR suitable for bioinspired control of humanoid robotics, representing a low-power and low-cost alternative to the widely used sensors. Full article

The aging population and increasing incidence of trauma among younger age groups have heightened the increasing demand for reliable implant materials. Effective implant materials must demonstrate rapid osseointegration and strong antibacterial properties to ensure optimal patient outcomes and decrease the chance of implant rejection. This study aims to enhance the bone–implant interface by utilizing 45S5 bioglass modified with various concentrations of Fe₃O₄ as a coating material. The effect of the insertion of Fe₃O₄ into the bioglass structure was studied using Raman spectroscopy which shows that with the increase in Fe₃O₄ concentration, new vibration bands associated with Fe-related structural units appeared within the sample. The bioactivity of the prepared glasses was evaluated using immersion tests in simulated body fluid, revealing the formation of a calcium phosphate-rich layer within 24 h on the samples, indicating their potential for enhanced tissue integration. However, the sample modified with 8 mol% of Fe₃O₄ showed low reactivity, developing a calcium phosphate-rich layer within 96 h. All the bioglasses showed antibacterial activity against the Gram-positive and Gram-negative bacteria. The modified bioglass did not present significant antibacterial properties compared to the bioglass base. Full article