With the development of camera technology, high-speed cameras have greatly contributed to capturing the movement and posture of animals, which has dramatically promoted experimental biology research. At the same time, with the concept of bionics gradually gaining popularity among researchers, the design of robots is absorbing more and more biological features, where the interest in the bio-inspired robot is hewed out. Compared with the traditional robot, the bio-inspired robot imitates the motion pattern to achieve similar propulsion features, which may be more effective and reasonable. In this paper, the motion patterns of aquatic animals are divided into four categories according to their propulsion mechanisms: drag-based, lift-based, jet-based, and interface-based. And bio-inspired robots imitating aquatic prototypes are introduced and reviewed. Finally, the prospect of aquatic bio-inspired robots is discussed.

With the rapid development of unmanned aerial and underwater vehicles, various tasks, such as biodiversity monitoring, surveying, and mapping, as well as, search and rescue can now be completed in a single medium, either underwater or in the air. By systematically examining the water–air cross-medium locomotion of organisms, there has been growing interest in the development of aerial-aquatic vehicles. The goal of this review is to provide a detailed outline of the design and cross-medium theoretical research of the existing aerial-aquatic vehicles based on the research on the organisms capable of transiting between water and air. Although these designs and theoretical frameworks have been validated in many aerial-aquatic vehicles, there are still many problems that need to be addressed, such as inflexible underwater motion and unstable medium conversion. As a result, supplementation of the existing cross-medium biomimetic research, vehicle design, power selection, and cross-medium theory is urgently required to optimize the key technologies in detail. Therefore, by summarizing the existing designs and theoretical approaches on aerial-aquatic vehicles, including biomimetic research on water–air cross-medium locomotion in nature, different power selections, and cross-medium theoretical research, the relative problems and development trends on aerial-aquatic vehicles were thoroughly explored, providing significant help for the subsequent research process.

Birds in nature exhibit excellent long-distance flight capabilities through formation flight, which could reduce energy consumption and improve flight efficiency. Inspired by the biological habits of birds, this paper proposes an autonomous formation flight control method for Large-sized Flapping-Wing Flying Robots (LFWFRs), which can enhance their search range and flight efficiency. First, the kinematics model for LFWFRs is established. Then, an autonomous flight controller based on this model is designed, which has multiple flight control modes, including attitude stabilization, course keeping, hovering, and so on. Second, a formation flight control method is proposed based on the leader–follower strategy and periodic characteristics of flapping-wing flight. The up and down fluctuation of the fuselage of each LFWFR during wing flapping is considered in the control algorithm to keep the relative distance, which overcomes the trajectory divergence caused by sensor delay and fuselage fluctuation. Third, typical formation flight modes are realized, including straight formation, circular formation, and switching formation. Finally, the outdoor formation flight experiment is carried out, and the proposed autonomous formation flight control method is verified in real environment.

Soft in-pipe robot has good adaptability in tubular circumstances, while its rigidity is insufficient, which affects the traction performance. This paper proposes a novel worm-like in-pipe robot with a rigid and soft structure, which not only has strong traction ability but also flexible mobility in the shaped pipes. Imitating the structure features of the earthworm, the bionic in-pipe robot structure is designed including two soft anchor parts and one rigid telescopic part. The soft-supporting mechanism is the key factor for the in-pipe robot excellent performance, whose mathematical model is established and the mechanical characteristics are analyzed, which is used to optimize the structural parameters. The prototype is developed and the motion control strategy is planned. Various performances of the in-pipe robot are tested, such as the traction ability, moving velocity and adaptability. For comparative analysis, different operating scenarios are built including the horizontal pipe, the inclined pipe, the vertical pipe and other unstructured pipes. The experiment results show that the in-pipe robot is suitable for many kinds of pipe applications, the average traction is about 6.8N, the moving velocity is in the range of 9.5 to 12.7 mm/s.

Bionic-based robotic legs enable the legged robots with elegant and agile mobility in multi-terrain environment, just like natural living beings. And the smart design could efficiently improve the performance of a robotic leg. Inspired by the simplified human leg structure, we present a 3-DOF robotic leg—OmniLeg, that is capable of making omnidirectional legged locomotion while keeping constant posture of the foot. Additionally, the concentrated drive mode, in which all the motor actuators are installed in the torso and do not move with the leg, minimizes the inertia of the robotic leg. In this paper, the modular design, the kinematics model, the structural analysis, the workspace, and the performance evaluation of the OmniLeg are discussed. Furthermore, we build a prototype based on the proposed design, and the precision of it is verified by the error calibration experiment which is conducted by tracking the trajectory of the prototype’s endpoint. Then, we present an OmniLeg-based single legged mobile robot. The capability of omnidirectional legged locomotion of the OmniLeg is demonstrated by the experiments.

By imitating the body structure and movement mode of the crab in nature, a novel stick–slip piezo-driven positioning platform was proposed by employing the bionic flexible hinge mechanism with a symmetrical structure and two piezoelectric stacks. The structural design and bionic motion principle were discussed, followed by analyzing the feasibility, safety, and output magnification ratio of the bionic flexible hinge mechanism via the stiffness matrix method and finite element simulation. To investigate the output performances of the positioning platform, a prototype was fabricated and an experiment system was established. Stepping characteristics of the positioning platform under various driving voltages were characterized, and the results indicated that the positioning platform could move steadily under various driving voltages. Within 1 s, the differences between the forward and reverse output displacement were less than 3% under different driving frequencies, proving the high bidirectional motion symmetry. The maximum driving speed of 5.44 mm/s was obtained under the driving voltage of 120 V and driving frequency of 5 Hz. In addition, the carrying load capacity of the positioning platform was tested by standard weights, and the results showed that when the carrying load reached 10 N, the driving speed could still reach 60 μm/s.

Inspired by the morphology of human fingers, this paper proposes an underactuated rigid-soft coupled robotic gripper whose finger is designed as the combination of a rigid skeleton and a soft tissue. Different from the current grippers who have multi-point contact or line contact with the target objects, the proposed robotic gripper enables surface contact and leads to flexible grasping and robust holding. The actuated mechanism, which is the palm of proposed gripper, is optimized for excellent operability based on a mathematical model. Soft material selection and rigid skeleton structure of fingers are then analyzed through a series of dynamic simulations by RecurDyn and Adams. After above design process including topology analysis, actuated mechanism optimization, soft material selection and rigid skeleton analysis, the rigid-soft coupled robotic gripper is fabricated via 3D printing. Finally, the grasping and holding capabilities are validated by experiments testing the stiffness of a single finger and the impact resistance of the gripper. Experimental results show that the proposed rigid-soft coupled robotic gripper can adapt to objects with different properties (shape, size, weight and softness) and hold them steadily. It confirms the feasibility of the design procedure, as well as the compliant and dexterous grasping capabilities of proposed rigid-soft coupled gripper.

In this article, a new optimization system that uses few features to recognize locomotion with high classifcation accuracy is proposed. The optimization system consists of three parts. First, the features of the mixed mechanical signal data are extracted from each analysis window of 200 ms after each foot contact event. This classifer has the advantages of high accuracy, few parameters as well as low memory burden. Based on data from eight patients with transfemoral amputations, the optimization system is evaluated. The numerical results indicate that the proposed model can recognize nine daily locomotion modes (i.e., low-, mid-, and fast-speed level-ground walking, ramp ascent/decent, stair ascent/descent, and sit/ stand) by only seven features, with an accuracy of 96.66%0.68%. As for real-time prediction on a powered knee prosthesis, the shortest prediction time is only 9.8 ms. These promising results reveal the potential of intention recognition based on the proposed system for high-level control of the prosthetic knee.

Cable-driven ankle–foot exoskeletons have attracted numerous researchers over the previous decade. The assistive forces of most exoskeletons pulled the back bottom of the shoes, across talocrural and subtalar joints. The talocrural joint is inherently mediolateral unstable at the plantarflexion position due to its sliding mortise structure, while the subtalar joint allows inversion/eversion. In this paper, a biologically inspired cross-type double-cable-driven ankle–foot exotendon was proposed to assist not only the plantarflexion moment but also the movement stability. The novel structure was bio-inspired by the behind-calf anatomically symmetric layout and under-foot cross-configuration of the ankle–foot muscles. To examine the combined functions, we conducted a forward pelvis perturbed standing experiment on five subjects without and with exotendon assistance and recorded the biomechanical data. Compared to the unpowered condition, the biological ankle plantarflexion moment was reduced by 39% with 0.1 Nm/kg exotendon assistance for one leg. Besides, the forward margin of stability was increased by 17% during the late perturbation period, which indicated the improvement of balance in the sagittal plane. In addition, the standard deviation of the lateral CoP and three-dimensional marker trajectories for the ankle condylar and heel all descended, which provided evidence for ankle–foot stability improvement. The results suggested that the proposed biological exotendon can provide the compound ankle–foot assistance, reducing plantarflexion moment and improving movement stability.

Neural interfaces based on surface Electromyography (EMG) decomposition have been widely used in upper limb prosthetic systems. In the current EMG decomposition framework, most Blind Source Separation (BSS) algorithms require EMG with a large number of channels (generally larger than 64) as input, while users of prosthetic limbs can generally only provide less skin surface for electrode placement than healthy people. We performed decomposition tests to demonstrate the performance of the new framework with the simulated EMG signal. The results show that the new framework identified more Motor Units (MUs) compared to the control group and it is suitable for decomposing EMG signals with low channel numbers. In order to verify the application value of the new framework in the upper limb prosthesis system, we tested its performance in decomposing experimental EMG signals in force fitting experiments as well as pattern recognition experiments. The average Pearson coefficient between the fitted finger forces and the ground truth forces is 0.9079 and the average accuracy of gesture classification is 95.11%. The results show that the decomposition results obtained by the new framework can be used in the control of the upper limb prosthesis while only requiring EMG signals with fewer channels.

According to clinical studies, upper limb robotic suits are vital to reduce therapist fatigue and accelerate patient rehabilitation. Soft pneumatic actuators have drawn increasing attention for the development of wearable robots due to their low weight, flexibility, and high power-to-weight ratio. However, most of current actuators were designed for the flexion assistance of a specific joint, and that for joint extension requires further investigation. Furthermore, designing an actuator for diverse working scenarios remains a challenge. In this paper, we propose an all-fabric bi-directional actuator to assist the flexion and extension of the elbow, wrist, and fingers. A mathematical model is presented that predicts the deformation and guides the design of the proposed bi-directional actuator. To further validate the applicability and adaptability of the proposed actuator for different joints, we developed a 3-DOF soft robotic suit. Preliminary results show that the robotic suit can assist the motion of the elbow, wrist, and finger of the subject.

The exoskeleton robot is a typical man–machine integration system in the human loop. The ideal man–machine state is to achieve motion coordination, stable output, strong personalization, and reduce man–machine confrontation during motion. In order to achieve an ideal man–machine state, a Time-varying Adaptive Gait Trajectory Generator (TAGT) is designed to estimate the motion intention of the wearer and generate a personalized gait trajectory. TAGT can enhance the hybrid intelligent decision-making ability under human–machine collaboration, promote good motion coordination between the exoskeleton and the wearer, and reduce metabolic consumption. An important feature of this controller is that it utilizes a multi-layer control strategy to provide locomotion assistance to the wearer, while allowing the user to control the gait trajectory based on human–robot Interaction (HRI) force and locomotion information. In this article, a Temporal Convolutional Gait Prediction (TCGP) model is designed to learn the personalized gait trajectory of the wearer, and the control performance of the model is further improved by fusing the predefined gait trajectory method with an adaptive interactive force control model. A human-in-the-loop control strategy is formed with the feedback information to stabilize the motion trajectory of the output joints and update the system state in real time based on the feedback from the inertial and interactive force signal. The experimental study employs able-bodied subjects wearing the exoskeleton for motion trajectory control to evaluate the performance of the proposed TAGT model in online adjustments. Data from these evaluations demonstrate that the controller TAGT has good motor coordination and can satisfy the subject to control the motor within a certain range according to the walking habit, guaranteeing the stability of the closed-loop system.

This paper presents a novel control approach for achieving robust posture control in legged locomotion, specifically for SLIP-like bipedal running and quadrupedal bounding with trunk stabilization. The approach is based on the virtual pendulum concept observed in human and animal locomotion experiments, which redirects ground reaction forces to a virtual support point called the Virtual Pivot Point (VPP) during the stance phase. Using the hybrid averaging theorem, we prove the upright posture stability of bipedal running with a fixed VPP position and propose a VPP angle feedback controller for online VPP adjustment to improve performance and convergence speed. Additionally, we present the first application of the VPP concept to quadrupedal posture control and design a VPP position feedback control law to enhance robustness in quadrupedal bounding. We evaluate the effectiveness of the proposed VPP-based controllers through various simulations, demonstrating their effectiveness in posture control of both bipedal running and quadrupedal bounding. The performance of the VPP-based control approach is further validated through experimental validation on a quadruped robot, SCIT Dog, for stable bounding motion generation at different forward speeds.

Added mass provided irregular interference towards human movement and shifted the force generated by lower limb muscles. However, the association between mass and muscle activities is not well recognized. Our study aims at investigating the influence of added mass on lower limbs. In our study, five young, healthy walkers performed walking trials under three load conditions (unload; C1: 0.25 pounds on feet, 1 pound on calves, and 2 pounds on thighs; C2: 1 pound on feet, 2 pounds on calves, and 4 pounds on thighs). During walking, three-dimensional kinematics, sEMG signals, and oxygen consumption were collected which allowed us to understand the effects of added mass on muscles. We also generated OpenSim simulation, designed to comprehend the relationship between added mass and muscles. With the increase of added mass, maximum sEMG signal and peak joint torque increased; whereas, the horizontal stride time reduced (unload: 1.697?±?0.02 s, C1: 1.651?±?0.02 s, C2: 1.622?±?0.02 s). Energy expenditure raised correspondingly (C1: 6.53%, C2: 24.85%). Moreover, joint moment increased, while same change occurred in muscle force. Overall, our results show that participants responded positively to additional mass by adjusting muscle activities, joint movement, and stride frequency, which demonstrates the relationship between energy consumption and added mass.

For the past several years, calcium phosphate cement was used in the biomedical applications. Outstanding biocompatibility, good bioactivity, self-setting qualities, minimum setting degree, appropriate toughness, and simple shape to accommodate any difficult geometry are among their most notable attributes. Calcium phosphate has some types and brushite is one of the most attractive mineral for bone repair application. Brushite is extensively employed in filling fractures and trauma treatments as a bone substituted material. This kind of material can potentially be used as a medicine delivery device. The replacement of metal, such as magnesium, zinc, and strontium ions, into the calcium phosphate structure is a major research topic these days. Brushite cement has low mechanical strength and quick setting rate. It is possible to produce biomaterials with higher mechanical characteristics. By adding metal that are great potential in controlling cellular density when included into biomaterials. As a result, it is a successful method to develop quite well regenerative medicine. This paper provides a detailed summary of the present achievements of metal-doped brushite cement for bone repair and healing process. The major purpose of this work is to give a simple but thorough analysis of current successes in brushite cement doped with Zn, Mg, Sr, and other ions as well as to highlight new advancements and prospects. The impact of metal replacement on cement physical and chemical properties, including microstructure, setting time, injectability, mechanical property, and ion release, is explored. The metal-doped cement has osteogenesis, angiogenesis, and antibacterial properties, as well as their prospective utility as drug carriers, also considered.

Nut shells have good impact and fracture resistance, but many kinds of nut shells have suture structures with low bonding strength. Therefore, the mechanism of impact and fracture resistance of nut shells as a whole is important to study, particularly given that sutures maintain low bonding strength. In this study, we investigated the effect of the geometrical characteristics of sutures (morphology, thickness, and number) on the overall fracture resistance of walnuts, based on mechanical tests of C-ring samples, microstructure analysis after cracking, quantitative analysis of suture geometric model, and numerical simulations. We found that the cracking of walnuts was mainly caused by tensile stress, and the bonding strength was approximately 2.48?±?0.64 MPa. We discovered that the thickness of the suture was 1.55?±?0.32 times thicker than the shell, which improved the fracture resistance ability by more than 28.4%. The undulating and inclined morphology of the walnut suture also increased the fracture force. Additionally, an appropriate suture number reduced the cracking of walnuts. In conclusion, our study sheds light on the physiological function of walnut sutures from a biomechanical perspective and provides useful references for designing fracture resistance measures in thin shell structures.

Superhydrophobic materials are severely limited in their applications due to their weak mechanical properties and complex preparation process. In this paper, polystyrene/fluorinated silica (PS/SiO2) superhydrophobic composite coatings were prepared on the surface of 304 stainless steel using a simple one-step spraying method. The effects of different PS contents on the wettability as well as the wear properties of the samples were investigated. SiO2 was encapsulated in polystyrene to form a structure similar to cement encapsulated stones. With the addition of PS, a mound-like structure was formed on the sample surface, and a more optimized micro–nano structure was obtained when the content of PS was 0.6 g. At this time, the sample exhibited excellent wettability with a contact angle of 157.86° and a sliding angle of 0.84°. In addition, the contact angle of 151.09° was achieved after 180 cm of friction under a 100 g load and the composite coating prepared by this method also has excellent chemical stability, water impact resistance, corrosion resistance, and self-cleaning properties. This opens up new possibilities for the development of simple and robust superhydrophobic materials.

Electrochemical actuators based on conductive polymers are emerging as a strong competitive in the field of soft actuators because of their intrinsically conformable/elastic nature, low cost, low operating voltage and air-working ability. Recent development has shown that adding electroactive materials, such as CNT and graphene, can improve their actuation performance. Despite the complex material systems used, their output strains (one of the key factors) are generally lower than 1%, which limited further applications of them in multiple scenarios. Here, we report soft electrochemical actuators based on conductive polymer ionogels by embedding polyaniline particles between the PEDOT:PSS nanosheets. Results show that such a hierarchical structure not only leads to a high conductivity (1250 S/cm) but also improved electrochemical activities. At a low operating voltage of 1 V, the maximum strain of these soft actuators reaches an exceptional value of 1.5%, with a high blocking force of 1.3 mN. Using these high-performance electrochemical actuators, we demonstrate soft grippers for manipulating object and a bionic flower stimulated by an electrical signal. This work sets an important step towards enabling the enhanced performance of el

Mechanoreceptors play a vital role for animals to sense and monitor environmental parameters, like flow speed, tactile resistance, and pressure. The hairy-structured trichoid sensillum, a common type of mechanoreceptor in insects, is generally non-motile, embedded in a socket connected with cuticular substrate. However, we discover that the trichoid sensilla on the tongue of western bees (Apis mellifera L.) is rotatable and can be actively maneuvered by bees. The trichoid sensilla together with the socket base are mounted on the origami-like sheath of the tongue, and can rotate outwards along with the deformation of the tongue sheath. We illustrate that the rotation of the tongue sensilla hairs can locally generate shear force in the liquid to sense the viscosity, which may facilitate bees to adjust their feeding strategies. The viscosity sensitivity of the rotatable trichoid sensilla based on the origami-like mechanism, according to our mechanical model, is 13 times greater than that of the fixed sensilla. In addition, our finite element analysis shows that strain would concentrate on the trichoid sensilla base when rotating in the liquid, which may structurally enhance its perception sensitivity. This study reports a new mechanism of active mechanoreceptors and may have implications for origami mechanisms with correlative functional components, especially for micro-robotic systems used in underwater viscosity sensing.

Learning hydrophobic phenomena from nature is always a promising approach to design the superhydrophobic surface. Purple orchid leaf which processes superhydrophobicity is an ideal plant model, and through mimicking its structure, the surface with excellent hydrophobicity is able to be obtained. However, the unclear of the diversity in wettability during the different vegetation stages and the absence of its relation to the surface morphology limits the further enhancement of the inspired structure. Here, we analyze the wettability difference as the leaf grows from tender to mature and then to senescent. Combining with the variation of surface morphology and chemical composition, the well-developed micro-scale basic unit bumps with dense nano-scale waxy layer on the surface are proven to be responsible for the best hydrophobicity of the mature leaf. The presence of the undeveloped or damaged micro-nano hierarchical structure reduces the formation of air pockets at the interface, leading to the decrease of the wettability for leaves at other stages. Moreover, by fabricating artificial leaves, the nano-waxy layer is proved to be more effective than that of the micro-bumps on the surface wettability. The results of study are of a great significance for guiding the design and fabrication of plant-inspired bionic superhydrophobic surface.

Flexible materials are essential in bionic fields such as soft robots. However, the lack of stiffness limits the mechanical performance of soft robots and makes them difficult to develop in many extreme working conditions, such as lifting and excavation operations. To address this issue, we prepared a stiffness-tunable composite by dispersing low-melting-point alloy into thermosetting epoxy resin. A dramatic and rapid change in stiffness was achieved by changing the state of matter at lower temperatures, and accurate control of the composite modulus was achieved by controlling the temperature. When the alloy content is at 30vol%, the tensile modulus changes 41.6 times, while the compressive modulus changes 58.9 times. By applying the composite to a flexible actuator, the initial stiffness of the actuator was improved by 124 times, reaching 332 mN/mm. In addition, the use of stiffness-tunable materials in the wheel allowed for timely changes in the grounding area to improve friction. These flexible materials with manageable mechanical properties have wide applicability in fields including bionics, robotics, and sensing. Our findings provide a new approach to designing and developing flexible materials with improved stiffness and controllability

As a global concern, environmental protection and energy conservation have attracted significant attention. Due to the large carbon emission of electricity, promoting green and low-carbon transformation of the power industry via the synergistic development of clean energy sources is essential. Rotating machinery plays a crucial role in pumped storage, hydropower generation, and nuclear power generation. Inspired by bionics, non-smooth features of creatures in nature have been introduced into the structure design of efficient rotating machines. First, the concept and classification of bionics are described. Then, the representative applications of non-smooth surface bionic structures in rotating machineries are systematically and comprehensively reviewed, such as groove structure, pit structure, and other non-smooth surfaces. Finally, conclusions are drawn and future directions are presented. The effective design of a bionic structure contributes toward noise reduction, drag reduction and efficiency improvement of rotating machineries. Green and ecological rotating machinery will remarkably reduce energy consumption and contribute to the realization of the “double carbon” goal.

he biomechanical efects of acetabular revision with jumbo cups are unclear. This study aimed to compare the biomechanical efects of bionic trabecular metal vs. titanium jumbo cups for the revision of acetabular bone defects. We designed and reconstructed American Academy of Orthopaedic Surgeons (AAOS) type I–III acetabular bone defect models using computed tomography scans of a man without acetabular bone defects. The implantation of titanium and trabecular metal jumbo cups was simulated. Stress distribution and relative micromotion between the cup and host bone were assessed using fnite element analysis. Contact stress on the screws fxing the cups was also analyzed. The contact stress analysis showed that the peak contact stress between the titanium jumbo cup and the host bone was 21.7, 20.1, and 23.8 MPa in the AAOS I–III models, respectively; the corresponding values for bionic tantalum jumbo cups decreased to 4.7, 6.7, and 11.1 MPa. Analysis of the relative micromotion showed that the peak relative micromotion between the host bone and the titanium metal cup was 10.2, 9.1, and 11.5 μm in the AAOS I–III models, respectively; the corresponding values for bionic trabecular metal cups were 17.2, 18.2, and 31.3 μm. The peak contact stress on the screws was similar for the 2 cup types, and was concentrated on the screw rods. Hence, acetabular reconstruction with jumbo cups is biomechanically feasible. We recommend trabecular metal cups due to their superior stress distribution and higher relative micromotion, which is within the threshold for adequate bone ingrowth.

In this study, an integrative bioinspired coating system for antifouling and corrosion resistance was investigated, in which self-healing nanocapsules (tung oil calcium alginate, TO@CA), doped polyaniline and nano-titanium dioxide nanocomposites (SPAn–TiO2) and a biostructure metal surface were combined. The antifouling property of the bioinspired coating resulted from the synergistic antifouling efect of nano-TiO2 and acid-doped polyaniline in SPAn–TiO2. The protonated nitrogen with a positive charge in SPAn–TiO2 and the intrinsic bactericidal property of nano-TiO2 could damage negatively charged single-celled chlorella, endowing the composite coating with good antifouling performance (less algae attached on the surfaces after a 90-day antifouling test and a conductivity test). The composite bioinspired coating had excellent corrosion resistance, which was due to the good synergistic anticorrosion barrier efect of SPAn–TiO2 with TO@CA nanocapsules and the repairing ability of microcracks of TO@CA nanocapsules during the corrosion process. The bioinspired coating with 2 wt% SPAn–TiO2 and 2 wt% TO@CA nanocapsules exhibited a better adhesion, corrosion resistance and antifouling performance than the other coatings did.

Chimp Optimization Algorithm (ChOA) is one of the recent metaheuristics swarm intelligence methods. It has been widely tailored for a wide variety of optimization problems due to its impressive characteristics over other swarm intelligence methods: it has very few parameters, and no derivation information is required in the initial search. Also, it is simple, easy to use, fexible, scalable, and has a special capability to strike the right balance between exploration and exploitation during the search which leads to favorable convergence. Therefore, the ChOA has recently gained a very big research interest with tremendous audiences from several domains in a very short time. Thus, in this review paper, several research publications using ChOA have been overviewed and summarized. Initially, introductory information about ChOA is provided which illustrates the natural foundation context and its related optimization conceptual framework. The main operations of ChOA are procedurally discussed, and the theoretical foundation is described. Furthermore, the recent versions of ChOA are discussed in detail which are categorized into modifed, hybridized, and paralleled versions. The main applications of ChOA are also thoroughly described. The applications belong to the domains of economics, image processing, engineering, neural network, power and energy, networks, etc. Evaluation of ChOA is also provided. The review paper will be helpful for the researchers and practitioners of ChOA belonging to a wide range of audiences from the domains of optimization, engineering, medical, data mining, and clustering. As well, it is wealthy in research on health, environment, and public safety. Also, it will aid those who are interested by providing them with potential future research.

Reducing pollutant emissions from electricity production in the power system positively impacts the control of greenhouse gas emissions. Boosting kernel search optimizer (BKSO) is introduced in this research to solve the combined economic emission dispatch (CEED) problem. Inspired by the foraging behavior in the slime mould algorithm (SMA), the kernel matrix of the kernel search optimizer (KSO) is intensifed. The proposed BKSO is superior to the standard KSO in terms of exploitation ability, robustness, and convergence rate. The CEC2013 test function is used to assess the improved KSO's performance and compared to 11 well-known optimization algorithms. BKSO performs better in statistical results and convergence curves. At the same time, BKSO achieves better fuel costs and fewer pollution emissions by testing with four real CEED cases, and the Pareto solution obtained is also better than other MAs. Based on the experimental results, BKSO has better performance than other comparable MAs and can provide more economical, robust, and cleaner solutions to CEED problems.

Chimp Optimization Algorithm (ChOA) is one of the most efcient recent optimization algorithms, which proved its ability to deal with diferent problems in various do- mains. However, ChOA sufers from the weakness of the local search technique which leads to a loss of diversity, getting stuck in a local minimum, and procuring premature convergence. In response to these defects, this paper proposes an improved ChOA algorithm based on using Opposition-based learning (OBL) to enhance the choice of better solutions, written as OChOA. Then, utilizing Reinforcement Learning (RL) to improve the local research technique of OChOA, called RLOChOA. This way efectively avoids the algorithm falling into local optimum. The performance of the proposed RLOChOA algorithm is evaluated using the Friedman rank test on a set of CEC 2015 and CEC 2017 benchmark functions problems and a set of CEC 2011 real-world problems. Numerical results and statistical experiments show that RLOChOA provides better solution quality, convergence accuracy and stability compared with other state-of-the-art algorithms.

Partitional clustering techniques such as K-Means (KM), Fuzzy C-Means (FCM), and Rough K-Means (RKM) are very simple and efective techniques for image segmentation. But, because their initial cluster centers are randomly determined, it is often seen that certain clusters converge to local optima. In addition to that, pathology image segmentation is also problematic due to uneven lighting, stain, and camera settings during the microscopic image capturing process. Therefore, this study proposes an Improved Slime Mould Algorithm (ISMA) based on opposition based learning and diferential evolution’s mutation strategy to perform illumination-free White Blood Cell (WBC) segmentation. The ISMA helps to overcome the local optima trapping problem of the partitional clustering techniques to some extent. This paper also performs a depth analysis by considering only color components of many well-known color spaces for clustering to fnd the efect of illumination over color pathology image clustering. Numerical and visual results encourage the utilization of illumination-free or color component-based clustering approaches for image segmentation. ISMA-KM and “ab” color channels of CIELab color space provide best results with above-99% accuracy for only nucleus segmentation. Whereas, for entire WBC segmentation, ISMA-KM and the “CbCr” color component of YCbCr color space provide the best results with an accuracy of above 99%. Furthermore, ISMA-KM and ISMA-RKM have the lowest and highest execution times, respectively. On the other hand, ISMA provides competitive outcomes over CEC2019 benchmark test functions compared to recent well-established and efcient Nature-Inspired Optimization Algorithms (NIOAs).

This paper presents a Butterfy Optimization Algorithm (BOA) with a wind-driven mechanism for avoiding natural enemies known as WDBOA. To further balance the basic BOA algorithm's exploration and exploitation capabilities, the butterfy actions were divided into downwind and upwind states. The algorithm of exploration ability was improved with the wind, while the algorithm of exploitation ability was improved against the wind. Also, a mechanism of avoiding natural enemies based on Lévy fight was introduced for the purpose of enhancing its global searching ability. Aiming at improving the explorative performance at the initial stages and later stages, the fragrance generation method was modifed. To evaluate the efectiveness of the suggested algorithm, a comparative study was done with six classical metaheuristic algorithms and three BOA variant optimization techniques on 18 benchmark functions. Further, the performance of the suggested technique in addressing some complicated problems in various dimensions was evaluated using CEC 2017 and CEC 2020. Finally, the WDBOA algorithm is used proportional-integral-derivative (PID) controller parameter optimization. Experimental results demonstrate that the WDBOA based PID controller has better control performance in comparison with other PID controllers tuned by the Genetic Algorithm (GA), Flower Pollination Algorithm (FPA), Cuckoo Search (CS) and BOA.

Feature selection (FS) is an adequate data pre-processing method that reduces the dimensionality of datasets and is used in bioinformatics, fnance, and medicine. Traditional FS approaches, however, frequently struggle to identify the most important characteristics when dealing with high-dimensional information. To alleviate the imbalance of explore search ability and exploit search ability of the Whale Optimization Algorithm (WOA), we propose an enhanced WOA, namely SCLWOA, that incorporates sine chaos and comprehensive learning (CL) strategies. Among them, the CL mechanism contributes to improving the ability to explore. At the same time, the sine chaos is used to enhance the exploitation capacity and help the optimizer to gain a better initial solution. The hybrid performance of SCLWOA was evaluated comprehensively on IEEE CEC2017 test functions, including its qualitative analysis and comparisons with other optimizers. The results demonstrate that SCLWOA is superior to other algorithms in accuracy and converges faster than others. Besides, the variant of Binary SCLWOA (BSCLWOA) and other binary optimizers obtained by the mapping function was evaluated on 12 UCI data sets. Subsequently, BSCLWOA has proven very competitive in classifcation precision and feature reduction.