Bioinspiration & Biomimetics最新文献

Sea turtle hatchlings display maneuvering capabilities across diverse aquatic and coastal terrains. While turning behavior is crucial in aquatic environments, it is equally vital for terrestrial locomotion by hatchlings that must quickly navigate obstacle-rich terrain on their way to the sea. This study introduces a robotic prototype that emulates the turning strategies of juvenile sea turtles to optimize turning rate and energy consumption across diverse terrestrial surfaces. The research investigates the rotational displacement capabilities of a bioinspired robot across five distinct gait configurations: one involving all flippers in a unique pattern, and four employing reduced flipper combinations, including front, diagonal, back, and single flippers. We investigated the robot's turning capabilities on diverse granular and compliant media, including four specified rock sizes, a consistent foam platform, and dry sand. Comparative analyses were conducted using rigid and soft flipper designs. Key locomotion features, including roll, pitch, yaw, and lift height, were quantified for each configuration. The results reveal significant differences in rotational behavior across terrains and gait styles, highlighting the interplay between flipper design, gait strategy, and environmental adaptability. This research advances the understanding of bioinspired robotics for applications in complex and variable environments.

Achieving robust and energy-efficient navigation in unknown fluid environments remains a key challenge for bioinspired underwater robots. In this study, we develop a reinforcement learning-based control framework that enables a fish-like swimmer to autonomously acquire effective navigation strategies within a high-fidelity computational fluid dynamics environment. By shaping the reward function to favor energy efficiency, the agent spontaneously discovers different locomotion patterns, ranging from continuous bursting to burst-and-coast gaits, all without prior knowledge of fluid mechanics. Although the agent is trained in a quiescent fluid environment, the learned swimming policies are generalized well in various navigation tasks and remain robust under complex flow perturbations, including uniform currents and unsteady vortex wakes. In all test scenarios, the agent achieves a 100%navigation success rate. These findings highlight the potential of integrating physics-based simulation with learning-based control strategy to advance the design of adaptive, efficient, and resilient aquatic robots inspired by biological swimmers.

Urban noise pollution is an increasingly pressing concern, driven by rapid infrastructural development and evolving environmental regulations. Among its most significant sources is the aeroacoustic emission from mechanical ventilation systems, where fan noise, comprising both tonal and broadband components, can be particularly disruptive. Inspired by the silent flight of owls, this study investigates the potential of trailing-edge serrations as a passive noise-reduction strategy for fan blades. A combined numerical and experimental approach is adopted. The acoustic performance is predicted using a hybrid methodology that couples large eddy simulations (LES) of the incompressible Navier-Stokes equations in their vorticity formulation with acoustic analogy models to capture far-field noise characteristics. A sensitivity study examines the influence of key geometrical parameters, specifically the number of serrations and the sawtooth ratio, defined in terms of pitch and depth. Results show that adjustments to these parameters allow for noticeable noise reductions, with improvements reaching up to 5 decibels. Although analyses are conducted at constant rotational speed, only marginal reductions in thrust and drag are observed, with aerodynamic efficiency remaining essentially unchanged. Flow analysis reveals that serrations enhance spanwise flow coherence, contributing to the passive stabilisation of turbulence near the trailing edge and blade tip. Experimental tests at varying rotational speeds support and extend the numerical findings, enabling a broader assessment across operating conditions. A multi-criteria evaluation framework is proposed to identify optimal serration configurations. These results provide valuable insights into bioinspired noise-control strategies and offer a foundation for the development of predictive tools for the design of next-generation low-noise fan systems.

Biomimetics is a powerful tool for problem solving in design and engineering. However, most biomimetic research is limited in the range of biological models considered, for instance with a frequent bias towards vertebrate animals. Diversifying the list of possible models increases the likelihood of discovering innovative solutions to a given problem and can overcome the limitations of sometimes imperfect design in biology. In this tutorial, we review key biology concepts that can assist students and practitioners of biomimetics in diversifying their list of biological models by expanding across evolutionary time and ecological space. First, we draw on evolutionary biology, particularly independent origins of a trait or function, which increases the chance of finding unique mechanisms underlying a function of interest. Second, we discuss core concepts from ecology for sampling across geographical space, considering different biomes or ecoregions where evolution may have played out in different ways to solve similar ecological issues. We show how to distill a biomimetic problem into abiotic and biotic components that have analogies in habitats and biomes across the globe. Finally, we consider both ecological and evolutionary processes jointly. Throughout this tutorial, we review useful and accessible tools, especially online databases, for putting these approaches into practice, even for a non-biologist. We hope to make the biomimetic approach more accessible and impactful by reviewing tools for sampling a broader range of potential biological models for a given biomimetic problem.

When groups of inertial swimmers move together, hydrodynamic interactions play a key role in shaping their collective dynamics, including the cohesion of the group. To explore how hydrodynamic interactions influence group cohesion, we develop a three-dimensional, inviscid, far-field model of a swimmer, neglecting the vortical wake produced by swimmers in order to determine the role that potential flow interactions play on group dynamics. Focusing on symmetric triangular, diamond, and circular group arrangements, we investigate whether passive hydrodynamics alone can promote cohesive behavior, and what role symmetry of the group plays. Under the idealized conditions of our model, we find that far-field interactions alone significantly impact the cohesion of groups of swimmers. This is an important result because, contrary to common belief, it shows that interactions with a vortical wake do not solely determine the cohesion of groups of swimmers. While small symmetric (and even asymmetric) groups can be cohesive, larger groups typically are not, instead breaking apart into smaller, self-organized subgroups that are cohesive. Notably, we discover circular arrangements of swimmers that chase each other around a circle, resembling the milling behavior of natural fish schools; we call this hydrodynamic milling. Hydrodynamic milling is cohesive in the sense that it is a fixed point of a particular Poincaré map, but it is unstable, especially to asymmetric perturbations. Our findings suggest that while passive hydrodynamics alone cannot sustain large-scale cohesion indefinitely, controlling interactions between subgroups, or controlling the behavior of only the periphery of a large group, could potentially enable stable collective behavior with minimal active input.

Evidence suggests that insects may utilize resonant mechanics during flight to optimize energetic efficiency, though whether this mechanism is universal across all insect species remains debated. Microinsects appear particularly intriguing in this context: they exhibit agility comparable to larger species despite experiencing higher aerodynamic damping forces on their wings. We investigated mechanical resonance dynamics focusing on the miniature waspTiphodytes gerriphagus-a remarkable species capable of both aerial flight and underwater locomotion, using wings in both cases. This dual-mode mobility introduces additional biomechanical constraints that simplify parameter identification in the analysis. We developed a reduced-order model incorporating muscle activation, internal inertial and viscous damping forces, thoracic elasticity, and inertial and fluid-dynamic forces acting on the wing. This model represents the insect flight apparatus as a one-dimensional oscillator. It employs capillary analogy modeling, integrated with a wing-thorax-muscle system undergoing periodic flapping motions. Our results demonstrate limited flight motor resonance potential in air, caused by strong damping effects, and unavoidably overdamped conditions underwater.

Recent neuroscience discoveries on human hand synergies have inspired the development of underactuated robotic hands, which replicate human-like grasping capabilities using a minimal number of actuators. However, a generalized methodology for determining the parameters of such bio-inspired underactuated hands to maximize anthropomorphic grasping abilities remains a significant challenge. To address this, we propose a novel framework based on Hertz contact theory to establish a general underactuated grasping model. Within this framework, we introduce evaluation indices and constraint conditions integrating morphological parameter ranges of the human hand derived from a scientific analysis in our prior work and an approximation index between human hand motions and robotic hand motions, aimed at: 1) biomimetic part: ensuring that the robotic hand's morphology, motion, and posture closely mimic those of the human hand, and 2) robotic part: maximizing the Euclidean norms of normal contact forces between the robotic hand and the object during grasping. To streamline the parameter optimization process, we devise a comprehensive, step-by-step strategy that groups parameters sequentially, enabling rapid convergence to optimal solutions. As a case study, we design and develop a dual-actuated robotic hand, comparing unaltered and optimized parameter schemes through extensive simulations and experimental validations. The results demonstrate the effectiveness of our method and suggest its potential applicability to a wide range of underactuated robots and bionic systems. This work provides a systematic approach to advancing the design and optimization of anthropomorphic robotic hands, bridging the gap between biological inspiration and engineering implementation.

Inspired by the stabilization of a bird's head by the arc-shaped supporting structure of its neck, a nonlinear vibration isolator that imitates these properties is proposed. The geometry and stiffness properties of the isolator, which consists of three rods connected by torsional springs, are designed for a specific payload to realize an isolator with a very low natural frequency offering good vibration isolation properties over a wide frequency range. A prototype is constructed to isolate a smart phone camera mounted on a bicycle from vibration excitation due to a rough road. The results show that the isolator is effective above a frequency of approximately 1 Hz.

Riblets inspired by the dermal denticles of shark skin are widely recognized for their drag-reducing performance. Although previous research has predominantly focused on two-dimensional riblet geometries, three-dimensional (3D) topographies remain underexplored due to the complex architecture of denticle-inspired surfaces. Natural riblet arrays, comprising thousands of interconnected dermal denticles, pose challenges in terms of parameterization, simulation, and fabrication. This work addresses these challenges by introducing a 3D, riblet-reinforced surface topography design that reduces drag, suppresses flow-induced noise, and simplifies both parameterization and prototyping, ultimately providing a scalable solution for towed array sonar applications. Leveraging Bayesian optimization, our computational fluid dynamics (CFD) results reveal that the optimal design decreases the overall sound pressure level by 6.87 dB and reduces drag by 0.34%, effectively balancing noise mitigation with hydrodynamic performance. The design that achieves the greatest noise reduction lowers flow noise by 8.81 dB, albeit with a slight increase in drag. The most effective design for drag reduction yields a 5.18% decrease, accompanied by significant noise suppression across key frequency bands. Flow field analysis demonstrates that our design alters the near-wall vorticity dynamics by promoting the formation of vortex rings that detach from the surface, thereby reducing turbulent energy transfer and limiting sound pressure fluctuations relative to a smooth surface design. To this end, the combination of CFD simulations and Bayesian optimization offers an efficient pathway to refine riblets-reinforced surface topographies, paving the way for advanced bioinspired designs that improve acoustic performance and efficiency in underwater applications.

The passive compliance of a soft worm-like body can be a key advantage for traversal of complex confined spaces, but in practice, the body's stiffness and contact friction often require experimental adjustments. Here, for the first time, we develop a dynamic, 3D simulation that enables systematic testing of robot parameters (e.g. stiffness and friction) in different radius of curvature environments, which will help us better understand design trade-offs in creating soft robots that mimic worm-like locomotion. Specifically, we use the open-source physics engine MuJoCo because it is established for both biomechanical and robotic modeling, as well as multi-point contact dynamics, which are present in confined spaces. The model has sensory capabilities analogous to the stretch and tactile proprioception of an earthworm and is amenable to both feedforward and feedback control. After validating our model by comparing to our previous physical robot, we quantify locomotion performance over a range of friction coefficients, structural stiffnesses, and turning radii. We found that speed increased with friction coefficient on flat ground for higher stiffness models, but decreased with friction coefficient for lower stiffness models, both on flat ground and in pipe bends. For turning radii greater than 0.45 m, speed and stiffness also had a positive correlation, however, below the critical turning radius of 0.45 m, increasing stiffness had no appreciable influence on speed. This simulation can potentially be used to optimize designs for particular environments, to better understand the influence of passive vs. active control on individual and coupled segments, and perhaps offer a deeper understanding of how animals and robots can employ soft structures. For example, we can posit from our results that changing stiffness will not increase speed below the critical turning radius, meaning further experiments should focus on other parameters or actively controlled turning to improve speed through tighter turns.