Bioinspiration & Biomimetics最新文献

The focus of this work is to investigate the influence of stiffness distribution in the fish tail on swimming performance and to determine the optimal stiffness distribution. Targeting fish employing the body and/or caudal fin (BCF) swimming mode, we constructed an fluid-structure interaction (FSI) simulation model based on the characteristics of BCF locomotion. Using this FSI model, we systematically examined multiple typical stiffness distributions along the inter-ray and ray-aligned directions, summarizing the underlying patterns in these two directions. Subsequently, we expanded the dataset obtained from the FSI simulations. Based on the expanded dataset, we developed a surrogate model using support vector regression (SVR) enhanced by the young's double-slit experiment optimization algorithm (YDSE). An improved particle swarm optimization algorithm was then applied to this surrogate model to identify the stiffness distributions corresponding to maximum thrust and highest efficiency, respectively. Compared to the original dataset, the optimized solutions obtained through YDSE-SVR iteration increased thrust by 4.94% and efficiency by 6.86%. Finally, we analyzed the mechanisms behind the differences in thrust and efficiency using pressure contours and streamline diagrams. The derived patterns regarding the influence of fish tail stiffness distribution on swimming performance can provide insights for robotic fish design.

Collective intelligence in biological groups can be employed to inspire the control of artificial complex systems, such as swarm robotics. However, modeling for the social interactions between individuals is still a challenging task. Without loss of generality, we propose a deep attention network model that incorporates the principles of biological Hard Attention mechanisms, that means an individual only pay attention to one or two neighbors for collective motion decision in large group. The model is trained by the collective movement data of five rummy-nose tetra fish (Hemigrammus rhodostomus). The structure of the model enforces individual agents to consider information from at most two neighboring agents. Meanwhile, the model can reveal hidden locations, where highly influential neighbors frequently appear. These findings demonstrate that the proposed Hard Attention Model aligns with the information processing mechanisms, which is observed in fish schooling. Experimental results indicate that the model exhibits a strong ability to decouple sparse information for collective movement with robust metrics. It can also perform excellent scalability in different group sizes. The simulation and real robots experiment show that the model provides a powerful tool for analyzing multi-level behaviors in complex systems and offers significant insights for the distributed control of swarm robotics.

The energetic consequences of swimming within a neighboring fish's vortex street remain a central question in collective locomotion. Recent flume experiments in which a flapping hydrofoil generated a biomimetic wake demonstrated that a trout can station-keep behind the foil while displaying kinematics markedly different from those used in uniform flow. To examine the underlying hydrodynamics, we accurately replicate the fish-foil system by first reproducing the experimentally recorded motions using a joint-based kinematic reconstruction method, and then we simulate the fluid dynamics with three-dimensional computational fluid dynamics. A companion simulation without the foil is also conducted to isolate wake effects. Relative to uniform-flow swimming, the presence of the foil wake reduces the trout's cycle-averaged hydrodynamic power expenditure by 11.4 ± 0.0003%, a benefit that arises because vortex columns shed by the foil create coherent negative-pressure corridors along the fish's lateral surface. Power reduction is realized when the trout's long-wavelength body wave remains phase-locked with the downstream advection of these vortex structures, enabling the fish to harvest pressure-induced thrust while minimizing added-mass losses. These findings provide a mechanistic explanation for wake exploitation in schooling fish, establish phase synchrony as a key control parameter for hydrodynamic benefit, and offer design guidelines for paired biomimetic underwater vehicles that seek to emulate schooling to improve propulsive efficiency.

Conventional rigid grippers remain the most-used robotic grippers in industrial assembly tasks. However, they are limited in their ability to handle a diverse range of objects. This study draws inspiration from nature to address these limitations, employing multidisciplinary methods, such as computer-aided design, parametric modeling, finite element analysis, 3D printing, and mechanical testing. Computational analysis of three distinct mandible morphs from the stag beetleCyclommatus mniszechirevealed that key geometric features-specifically mandible curvature and denticle arrangement-govern a functional trade-off between grasping ability and structural safety. This analysis identified a specific morphology optimized for superior grabbing performance, which served as the template for our design. Leveraging these biological principles, we used parametric modeling to design, and 3D printing to fabricate, a series of novel, mechanically intelligent grippers. Mechanical testing of these prototypes validated our design approach, demonstrating that specific modifications to curvature could significantly enhance the gripper's load-bearing capacity while minimizing object damage. This work establishes a clear pathway from biomechanical analysis to engineered application, offering a robust and cost-efficient blueprint for developing next-generation grippers that operate effectively without complex sensing or actuation systems for tasks in manufacturing, logistics, and healthcare.

Harbor seals possess a remarkable ability to detect hydrodynamic footprints left by moving objects, even long after the objects have passed, through interactions between wake flows and their uniquely shaped whiskers. While the flow-induced vibration of harbor seal whisker models has been extensively studied, their response to unsteady wakes generated by upstream moving bodies remains poorly understood. This study investigates the wake-induced vibration (WIV) of a flexibly mounted harbor seal-inspired whisker positioned downstream of a forced-oscillating circular cylinder, simulating the hydrodynamic footprint of a moving object. Unlike conventional WIV studies, where the upstream wake is passively formed behind a stationary body and governed solely by its geometry and flow speed, the upstream cylinder in this work undergoes prescribed oscillations. This approach enables independent control over the wake characteristics-such as wake width and shedding frequency-decoupling them from the physical attributes of the upstream source and allowing a more direct assessment of the whisker's sensing response to dynamic wake conditions. Experiments were conducted across a range of reduced velocities (U∗= 3.4-25) and Reynolds numbers (Re= 500-2700), with upstream oscillation frequencies varied from 0.5 to 2 times the natural frequency of the whisker. Volumetric particle tracking velocimetry (PTV) was used to characterize the flow field, complemented byQ-criterion and proper orthogonal decomposition analyses. Results show that while the whisker suppresses its own vortex-induced vibration in open flow, it oscillates strongly at the frequency of the upstream forcing when exposed to wake disturbances, demonstrating its capability to detect and respond to hydrodynamic trails of moving objects. These findings highlight the potential of harbor seal whisker-inspired designs for biomimetic underwater sensing and navigation systems.

The field of soft robotics has shown unprecedented growth in research efforts, scientific achievements, and technological advancements. Bioinspiration and biomimetics have played an instrumental role in the birth and growth of soft robotics. What is next for this field? To promote soft robotics research to the next level and have a broader impact in robotics and engineering fields, in this roadmap, we argue that two research directions should be strengthened i) more structured, formal methods and tools for designing and developing soft robots and bioinspired robots ii) more concrete applications of bioinspired soft robots in diverse sectors of human activities. This article provides a roadmap for the design of bioinspired soft robots, the integration of soft robot systems, and their applications in industry and services. Scientists and experts describe the state-of-the art and the perspectives of bioinspired, model-informed design of soft robots, outlining the challenges in developing complex soft robotic systems, and applications of soft robots in diverse fields. .

Nature has remained one of the key sources of inspiration for human technology. While striking for higher efficiency, design improvements in power-generating turbines have started to reach a saturation point. Biomimicry- learning from nature, has great potential for significant performance improvements. This paper provides a comprehensive review of the current trends in research of bioinspired technology on wind and hydrokinetic turbines. The aim is to identify the most effective bioinspired methods and the factors affecting the turbine performance. Various methods adopted are inspired by animals and plants and their interaction with fluid to enhance aero/hydrodynamic properties. These promising methods include the humpback whale tubercle and bird wing, where flow characteristics can be improved such as delaying the stall conditions and suppressing flow separation. Methods inspired by dragonfly wings, sea pen leaves, and plant seeds showed substantial merit for operating at low wind speeds, as a better glide ratio, enabling them to be suitable for low wind speed turbines. Furthermore, additional surface and structural modifications are explored, and their contributions are discussed in this paper. Various biomimicry methods were compared and critically analysed. This paper closes with a brief overview of future development options.

Euplectella aspergillum(E.a.) is a remarkable deep-sea glass sponge that has attracted attention from researchers across various disciplines. This review paper provides a comprehensive overview of E.a., focusing on its unique structural and mechanical properties. This sponge species is found mostly in the Pacific Ocean's deep waters at depths ranging from 100 to 1000 m. They have complicated hierarchical structures that span the nanoscale to the macroscale. The sponge's cylindrical, lattice-like structure is made up of silica spicules arranged in a square grid pattern and strengthened by diagonal and helical components. The composition and geometry of individual spicules are also summarised and discussed. Each spicule consists of concentric silica layers separated by organic interlayers. This hierarchical structure contributes to the spicules' exceptional mechanical properties, including enhanced bending capacity, tensile strength, and fracture toughness. The review also explores the spicule bundle interlocking system, which provides additional structural integrity to the overall skeleton. This review also gathers and depicts various experimental techniques and modelling approaches used to investigate the mechanical behaviour of E.a., including nanoindentation, and finite element analysis. These studies have revealed toughening mechanisms that allow the sponge to withstand the challenging deep-sea environment. Some real-world applications inspired by E.a.'s structure, with great potential in architectural designs and advanced materials for the aerospace and automotive industries, are highlighted.

Jellyfish achieve efficient pulse jetting through large-amplitude, low-frequency deformations of a soft bell. This is made possible through large localised deformations at the bell margin. This paper develops a novel soft-robotic underwater pulse jetting method that harnesses the buckling of flexible tubes to generate thrust. Soft material instability is controlled through variation of internal water pressure in the tubes, where we demonstrate repeatable large-amplitude deformations with bell flexion angles of 29 ± 1.5^∘over a frequency range of 0.2-1.1 Hz. The actuator is used to propel a soft robotic platform through water, achieving instantaneous velocities of up to 5 cm s^-1with no noticeable degradation in performance over 1000 pressure cycles.

Multimodal miniature soft robots, with their higher movement flexibility and environmental adaptability, represent a crucial direction for the future development of soft robots. Magnetic-driven robots, owing to their advantages such as excellent remote wireless control, fast response speed, and ease of integrated manufacturing, are the main driving method for robots to achieve multimodal locomotion. However, challenges persist in the development of magnetic miniature soft robots (MMSRs) with multimodal locomotion, including issues like interference between locomotion modes and low load capacity. Efforts are still required to design more balanced and refined performance in multimodal MMSRs. In this perspective, we review the recent progress of magnetic-driven soft robots with different locomotion modes, as well as multimodal MMSRs integrating 2-4 locomotion modes, and propose potential future directions for the development of multimodal MMSRs.