Journal of Bionic Engineering最新文献

{"title":"Design and Performance Analysis of a Bionic Squid Underwater Thruster","authors":"Xueting Pan,&nbsp;Yong Zhao,&nbsp;Fei Yang,&nbsp;Honghao Yue,&nbsp;Zhongtai Geng","doi":"10.1007/s42235-025-00686-9","DOIUrl":"10.1007/s42235-025-00686-9","url":null,"abstract":"<div><p>Compared with the propulsion mode using the fluctuation or swing of fins, the water-jet propulsion of cephalopods has attracted much attention because of its high swimming speed. This paper introduces a squid-like underwater thruster based on an origami structure, which can realize water-jet propulsion by changing the shape of its origami structure. At the same time, it is combined with a soft vector nozzle driven by negative pressure for underwater steering. In addition, a triboelectric sensor (TES) is embedded in the origami structure to monitor the shape change of the thruster in real time. The kinematics model of the origami structure is established, and the dihedral angle <span>(:{text{B}}_{text{0}}^{text{4}})</span>, which can be used to characterize the unique shape of the thruster, is put forward. The dihedral angle <span>(:{text{B}}_{text{0}}^{text{4}})</span> is monitored by the TES so that the shape change of the thruster can be feedback in real-time. Prototypes of the thruster and vector nozzle were fabricated, and the maximum error of TES in monitoring the shape of the thruster was less than 4.4%. At the same time, an underwater test platform was built to test the thruster’s propulsion performance and the vector nozzle’s deflection effect.</p></div>","PeriodicalId":614,"journal":{"name":"Journal of Bionic Engineering","volume":"22 3","pages":"1060 - 1070"},"PeriodicalIF":5.8,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145169940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Snow Leopard-inspired Lower Limb Exoskeleton for Adaptive Multi-terrain Locomotion: Design and Preliminary Experimental Evaluation","authors":"Yi Long,&nbsp;Xiaofeng Luo,&nbsp;Tianqi Zhou,&nbsp;Xiaopeng Hu,&nbsp;Long He,&nbsp;Wei Dong","doi":"10.1007/s42235-025-00687-8","DOIUrl":"10.1007/s42235-025-00687-8","url":null,"abstract":"<div><p>To overcome the limitations of traditional exoskeletons in complex outdoor terrains, this study introduces a novel lower limb exoskeleton inspired by the snow leopard’s forelimb musculoskeletal structure. It features a non-fully anthropomorphic design, attaching only at the thigh and ankle with a backward-knee configuration to mimic natural human knee movement. The design incorporates a single elastic element at the hip for gravity compensation and dual elastic elements at the knee for terrain adaptability, which adjust based on walking context. The design’s effectiveness was assessed by measuring metabolic cost reduction and motor output torque under various walking conditions. Results showed significant metabolic cost savings of 5.8–8.8% across different speeds and a 7.9% reduction during 9° incline walking on a flat indoor surface. Additionally, the spring element decreased hip motor output torque by 7–15.9% and knee torque by 8.1–14.2%. Outdoor tests confirmed the design’s robustness and effectiveness in reducing motor torque across terrains, highlighting its potential to advance multi-terrain adaptive exoskeleton research.</p></div>","PeriodicalId":614,"journal":{"name":"Journal of Bionic Engineering","volume":"22 3","pages":"1249 - 1264"},"PeriodicalIF":5.8,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145170561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bio-inspired Design Approach and Experimental Validation of a Holistic Lightweight Gear","authors":"Nils Niebuhr,&nbsp;Philipp Thomaneck,&nbsp;Lars Friedrichs,&nbsp;Marc Pillarz,&nbsp;Axel von Freyberg,&nbsp;Andreas Fischer","doi":"10.1007/s42235-025-00683-y","DOIUrl":"10.1007/s42235-025-00683-y","url":null,"abstract":"<div><p>Lightweight structures for gears enable a reduction in material usage while maintaining the technical function of the gear. Previous approaches have pursued the strategy of lightweight structures in the gear wheel body. By taking inspiration from biological models and utilizing material savings in the gear rim, new design approaches for the lightweight design of gears can be realized. For this reason, a holistic biological design approach for spur gears is presented. In addition to the method of topology optimization, a biologically inspired approach based on diatoms is introduced, which achieves a weight reduction of over 50% compared to conventional solid gears. Diatom structures are extracted from the oceans, digitally modelled, and adapted to the load conditions of a reference gear by parametric design and simulation optimization. For the experimental validation of the design, a manufactured gear is statically loaded in the nominal load range and analyzed using a tactile geometry gear measurement. The measurement results of selected standard gear parameters show that the gear does not exhibit any plastic deformation for the nominal load capacity of 383 Nm, validating the presented design approach.</p></div>","PeriodicalId":614,"journal":{"name":"Journal of Bionic Engineering","volume":"22 3","pages":"1304 - 1321"},"PeriodicalIF":5.8,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s42235-025-00683-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145170146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Porous Bone Structure Inspired Biomimetic Flexible Piezoresistive Sensor with High Sensitivity for Motion Monitoring","authors":"Hengyi Yuan,&nbsp;Qingfang Zhang,&nbsp;Yi Li,&nbsp;Xiaoyu Zhang,&nbsp;Da Li,&nbsp;Zhihui Qian,&nbsp;Lei Ren,&nbsp;Luquan Ren","doi":"10.1007/s42235-025-00691-y","DOIUrl":"10.1007/s42235-025-00691-y","url":null,"abstract":"<div><p>Flexible piezoresistive sensors based on biomimetic microstructures are prospective for broad application in motion monitoring. However, the design and preparation processes of most biomimetic microstructures in the existing studies are complicated, and there are few studies on pore size control. Herein, the porous structure of human bones was used as a biomimetic prototype, and optimally designed by creating a theoretical equivalent sensor model and a finite element model. Soluble raw materials such as sugar and salt in different particle sizes were pressed into porous templates. Based on the template method, porous structures in different pore sizes were prepared using polydimethylsiloxane (PDMS) polymer as the substrate. On this basis, graphene oxide conductive coating was prepared with the modified Hummers method and then deposited via dip coating onto the substrate. Finally, a PDMS-based porous structure biomimetic flexible piezoresistive sensor was developed. Mechanically, the deformation of the sensor under the same load increased with the pore size rising from 0.3 to 1.5 mm. Electrically, the resistance rang of the sensor was enlarged as the pore size rose. The resistance variation rates of samples with pore sizes of 0.3, 1.0, and 1.5 mm at approximately the 200th cycle were 63%, 79%, and 81%, respectively; at the 500th cycle, these values were 63%, 77%, and 79%; and at the 1000th cycle, they stabilized at 63%, 74%, and 76%. These results indicate that the fabricated sensor exhibits high stability and fatigue resistance. At the pressure of 0–25 kPa, the sensitivity rose from 0.0688 to 0.1260 kPa⁻¹, and the performance was enhanced by 83%. After 1,000 cycles of compression testing, the signal output was stable, and no damage was caused to the substrate. Further application tests showed the biomimetic sensor accurately and effectively identified human joint motions and gestures, and has potential application value in human motion monitoring.</p></div>","PeriodicalId":614,"journal":{"name":"Journal of Bionic Engineering","volume":"22 3","pages":"1322 - 1337"},"PeriodicalIF":5.8,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145167317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Active Disturbance Rejection Control Based on Twin-Delayed Deep Deterministic Policy Gradient for an Exoskeleton","authors":"Zhong Li,&nbsp;Xiaorong Guan,&nbsp;Chunyang Liu,&nbsp;Dingzhe Li,&nbsp;Long He,&nbsp;Yanfeng Cao,&nbsp;Yi Long","doi":"10.1007/s42235-025-00676-x","DOIUrl":"10.1007/s42235-025-00676-x","url":null,"abstract":"<div><p>The study of exoskeletons has been a popular topic worldwide. However, there is still a long way to go before exoskeletons can be widely used. One of the major challenges is control, and there is no specific research trend for controlling exoskeletons. In this paper, we propose a novel exoskeleton control strategy that combines Active Disturbance Rejection Control (ADRC) and Deep Reinforcement Learning (DRL). The dynamic model of the exoskeleton is constructed, followed with the design of the ADRC. To automatically adjust the control parameters of the ADRC, the Twin-Delayed Deep Deterministic Policy Gradient (TD3) is utilized. Then a reward function is defined in terms of the joint angle, angular velocity, and their errors to the desired values, to maximize the accuracy of the joint angle. In the simulations and experiments, a conventional ADRC, and ADRC based on Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) were carried out for comparison with the proposed control method. The results of the tests show that TD3-ADRC has a rapid response, small overshoot, and low Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) followed with the desired, demonstrating the superiority of the proposed control method for the self-learning control of exoskeleton.</p></div>","PeriodicalId":614,"journal":{"name":"Journal of Bionic Engineering","volume":"22 3","pages":"1211 - 1230"},"PeriodicalIF":5.8,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145167318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bio-inspired Excavator Digging Trajectory Planning: Insights from Mole Digging Patterns","authors":"Xiaodan Tan,&nbsp;Chen Chen,&nbsp;Zongwei Yao,&nbsp;Guoqiang Wang,&nbsp;Qingxue Huang","doi":"10.1007/s42235-025-00685-w","DOIUrl":"10.1007/s42235-025-00685-w","url":null,"abstract":"<div><p>The automatic and rapid generation of excavation trajectories is the foundation for achieving an intelligent excavator. To obtain high-performance trajectories that enhance operational capacity while avoiding the numerous issues present in existing methods for generating effective excavation paths, this paper proposes a trajectory generation method for excavators based on imitation learning, using the mole as a bionic prototype. Given the high excavation efficiency of moles, this paper first analyzes the structural characteristics of the mole’s forelimbs, its digging principles, morphology, and trajectory patterns. Subsequently, a higher-order polynomial is employed to fit and optimize the mole’s excavation trajectory. Next, imitation learning is conducted on sample trajectories based on Dynamic Movement Primitives, followed by the introduction of an obstacle avoidance algorithm. Simulation experiments and comparisons demonstrate that the mole-inspired trajectory method used in this paper performs well and possesses the ability to generate obstacle avoidance trajectories, as well as the convenience of transferring across different machine models.</p></div>","PeriodicalId":614,"journal":{"name":"Journal of Bionic Engineering","volume":"22 3","pages":"1287 - 1303"},"PeriodicalIF":5.8,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145165704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Collaborative Multi-target Search of Multiple Bionic Robotic Fish Based on Distributed Model Predictive Control","authors":"Ruilong Wang,&nbsp;Ming Wang,&nbsp;Lingchen Zuo,&nbsp;Yanling Gong,&nbsp;Guangxin Lv,&nbsp;Qianchuan Zhao,&nbsp;He Gao","doi":"10.1007/s42235-025-00680-1","DOIUrl":"10.1007/s42235-025-00680-1","url":null,"abstract":"<div><p>In complex water environments, search tasks often involve multiple Autonomous Underwater Vehicles (AUVs), and a single centralized control cannot handle the complexity and computational burden of large-scale systems. Target search in complex water environments has always been a major challenge in the field of underwater robots. To address this problem, this paper proposes a multi-biomimetic robot fish collaborative target search method based on Distributed Model Predictive Control (DMPC). First, we established a bionic robot fish kinematic model and a multi-biomimetic robot fish communication model; second, this paper proposed a distributed model predictive control algorithm based on the distributed search theory framework, so that the bionic robot fish can dynamically adjust their search path according to each other’s position information and search status, avoid repeated coverage or missing areas, and thus improve the search efficiency; third, we conducted simulation experiments based on DMPC, and the results showed that the proposed method has a target search success rate of more than 90% in static targets, dynamic targets, and obstacle environments. Finally, we compared this method with Centralized Model Predictive Control (CMPC) and Random Walk (RW) algorithms. The DMPC approach demonstrates significant advantages, achieving a remarkable target search success rate of 94.17%. These findings comprehensively validate the effectiveness and superiority of the proposed methodology. It can be seen that DMPC can effectively dispatch multiple bionic robot fish to work together to achieve efficient search of vast waters. It can significantly improve the flexibility, scalability, robustness and cooperation efficiency of the system and has broad application prospects.</p></div>","PeriodicalId":614,"journal":{"name":"Journal of Bionic Engineering","volume":"22 3","pages":"1194 - 1210"},"PeriodicalIF":5.8,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145165705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing Cancer Classification and Gene Discovery with an Adaptive Learning Search Algorithm for Microarray Analysis","authors":"Chiwen Qu,&nbsp;Heng Yao,&nbsp;Tingjiang Pan,&nbsp;Zenghui Lu","doi":"10.1007/s42235-025-00656-1","DOIUrl":"10.1007/s42235-025-00656-1","url":null,"abstract":"<div><p>DNA microarrays, a cornerstone in biomedicine, measure gene expression across thousands to tens of thousands of genes. Identifying the genes vital for accurate cancer classification is a key challenge. Here, we present Fs-LSA (F-score based Learning Search Algorithm), a novel gene selection algorithm designed to enhance the precision and efficiency of target gene identification from microarray data for cancer classification. This algorithm is divided into two phases: the first leverages F-score values to prioritize and select feature genes with the most significant differential expression; the second phase introduces our Learning Search Algorithm (LSA), which harnesses swarm intelligence to identify the optimal subset among the remaining genes. Inspired by human social learning, LSA integrates historical data and collective intelligence for a thorough search, with a dynamic control mechanism that balances exploration and refinement, thereby enhancing the gene selection process. We conducted a rigorous validation of Fs-LSA’s performance using eight publicly available cancer microarray expression datasets. Fs-LSA achieved accuracy, precision, sensitivity, and F1-score values of 0.9932, 0.9923, 0.9962, and 0.994, respectively. Comparative analyses with state-of-the-art algorithms revealed Fs-LSA’s superior performance in terms of simplicity and efficiency. Additionally, we validated the algorithm’s efficacy independently using glioblastoma data from GEO and TCGA databases. It was significantly superior to those of the comparison algorithms. Importantly, the driver genes identified by Fs-LSA were instrumental in developing a predictive model as an independent prognostic indicator for glioblastoma, underscoring Fs-LSA’s transformative potential in genomics and personalized medicine.</p></div>","PeriodicalId":614,"journal":{"name":"Journal of Bionic Engineering","volume":"22 2","pages":"901 - 930"},"PeriodicalIF":4.9,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143655239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on Mirror-Assisted Rehabilitation Training Method Based on Dual-Arm Robots","authors":"Xiaolong Yang,&nbsp;Qing Sun,&nbsp;Shuai Guo","doi":"10.1007/s42235-025-00665-0","DOIUrl":"10.1007/s42235-025-00665-0","url":null,"abstract":"<div><p>This paper studies a mirror-assisted rehabilitation training method based on a dual-arm robot, which aims to provide an effective rehabilitation training program for patients with upper limb dysfunction due to stroke or other causes. During the mirror training task scenario, the subjects are visually guided to perform the mirror movement of both arms, and the dual-arm robot is used to facilitate the mirror-assisted rehabilitation from the healthy side to the affected side. Adaptive impedance control and force field channel design ensure the stability and safety of the rehabilitation process. In the rehabilitation training, appropriate assistance forces are provided within the channel to correct trajectory deviations, ensuring that the subjects’ movement path aligns with the predetermined trajectory. Outside the channel, the superposition of stiffness and correction force fields prevents the subjects from deviating from the predetermined trajectory, thus avoiding injuries. In addition, the adaptive impedance control is capable of dynamically adjusting the impedance parameters according to the real-time state of the subjects, providing a personalized rehabilitation training program. This method significantly enhances both the safety and effectiveness of the rehabilitation training. The experimental results showed that the subjects’ motion flexibility and safety were significantly improved during the mirror-assisted rehabilitation training. This study offers a new approach for the future development of rehabilitation robotics with broad application potential.</p></div>","PeriodicalId":614,"journal":{"name":"Journal of Bionic Engineering","volume":"22 2","pages":"670 - 683"},"PeriodicalIF":4.9,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143655238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Improved Multi-objective Artificial Hummingbird Algorithm for Capacity Allocation of Supercapacitor Energy Storage Systems in Urban Rail Transit","authors":"Xin Wang,&nbsp;Jian Feng,&nbsp;Yuxin Qin","doi":"10.1007/s42235-025-00653-4","DOIUrl":"10.1007/s42235-025-00653-4","url":null,"abstract":"<div><p>To address issues such as poor initial population diversity, low stability and local convergence accuracy, and easy local optima in the traditional Multi-Objective Artificial Hummingbird Algorithm (MOAHA), an Improved MOAHA (IMOAHA) was proposed. The improvements involve Tent mapping based on random variables to initialize the population, a logarithmic decrease strategy for inertia weight to balance search capability, and the improved search operators in the territory foraging phase to enhance the ability to escape from local optima and increase convergence accuracy. The effectiveness of IMOAHA was verified through Matlab/Simulink. The results demonstrate that IMOAHA exhibits superior convergence, diversity, uniformity, and coverage of solutions across 6 test functions, outperforming 4 comparative algorithms. A Wilcoxon rank-sum test further confirmed its exceptional performance. To assess IMOAHA’s ability to solve engineering problems, an optimization model for a multi-track, multi-train urban rail traction power supply system with Supercapacitor Energy Storage Systems (SCESSs) was established, and IMOAHA was successfully applied to solving the capacity allocation problem of SCESSs, demonstrating that it is an effective tool for solving complex Multi-Objective Optimization Problems (MOOPs) in engineering domains.</p></div>","PeriodicalId":614,"journal":{"name":"Journal of Bionic Engineering","volume":"22 2","pages":"866 - 883"},"PeriodicalIF":4.9,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143655236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}