Bioinspiration & Biomimetics最新文献

Inspired by killer whale hunting strategies, this study presents a biomimetic algorithm for controlled subgroup fission in swarms. The swarm agents adopt the classic social force model with some practical modifications. The proposed algorithm consists of three phases: cluster selection phase via a constrained K-means algorithm, driven phase with strategic agent movement, including center pushing, coordinated oscillation, and flank pushing by specialized driven agents, and judgment phase confirming subgroup separation using the Kruskal algorithm. Simulation results confirm the algorithm's high success rate and efficiency in subgroup division, demonstrating its potential for advancing swarm-based technologies.

This paper describes the tailless control system design of a flapping-wing micro air vehicle in a four-winged configuration, which can provide high control authority to be stable and agile in flight conditions from hovering to maneuvering flights. The tailless control system consists of variable flapping frequency and wing twist modulation. The variable flapping frequency creates rolling moments through differential vertical force from flapping mechanisms that can be independently driven on the left and right sides. The wing twist modulation changes wing tension, resulting in vertical and horizontal force variations during one flap cycle and generating pitching and yaw moments. We presume that the wing geometry and implementation method of wing-root actuation are related to the control authority of wing twist modulation. Then, the control system's performance is analyzed for various wing geometries and implementation methods, including wing length, leading-edge thickness, camber angle, and vein configuration. Furthermore, the cross-coupling effect is examined for the wing twist modulation, and a control surface interconnect is designed to compensate for the decrease of pitch control authority and adverse rolling moment. The refined wing and control mechanism demonstrated its high control authority without significant loss of vertical force and power efficiency. The flight experiments validated that the control system based on wing twist modulation is suitable for four-winged flapping-wing micro air vehicles, providing sufficient control moment and minimizing the cross-coupling effect.

The cable-driven hyper-redundant manipulator (CDHM), distinguished by its high flexibility and adjustable stiffness, is extensively utilized in confined and obstacle-rich environments such as aerospace and nuclear facilities. This paper introduces a novel CDHM inspired by the trunk of elephants, which changes the arm structure from cylindrical to conical. This alteration diminishes the arm's self-weight, reduces the moment arm of gravity, decreases the volume of the end joint, narrows the stroke of the driving cables, and boosts the maximum joint speed of the manipulator. Additionally, this study examines the impact of the manipulator's taper on its overall performance from both dynamic and kinematic perspectives. Finally, three prototype manipulators with varying tapers are confirmed, and tests are conducted on each manipulator's motion performance and cable tension. By comparing experimental data, the accuracy of the theoretical analysis and the rationality of the conical structure are confirmed. The results suggest that the proposed new configuration offers certain advantages in terms of cable stroke, joint speed and maximum driving force.

Flying insects have developed two distinct adaptive strategies to minimize wing damage during collisions. One strategy includes an elastic joint at the leading edge, which is evident in wasps and beetles, while another strategy features an adaptive and deformable leading edge, as seen in bumblebees and honeybees. Inspired by the latter, a novel approach has been developed for improving collision recovery in micro aerial vehicles (MAVs) by mimicking the principle of stiffness anisotropy present in the leading edges of these insects. This study introduces a passive, flexible, folding wing design with adaptive leading edges. The impact of these adaptive folding leading edges on the flight performance of flapping-wing MAVs was systematically evaluated. Variations in lift generation and obstacle-crossing capabilities between rigid wings and adaptive deformable wings were quantified. Additionally, the mechanical stiffness of the wings was assessed to validate their functional effectiveness. The proposed mechanism was incorporated into the wings of a dual-layer flapping-wing robot, which demonstrated successful flight recovery after collision. The experimental results indicate that a robot with a 30 cm wingspan can effectively traverse a gap of 16.2 cm during flight, thereby demonstrating its enhanced ability to overcome collision challenges. These findings underscore the potential of adaptive wing designs in enhancing the resilience and performance of MAVs in dynamic environments.

Interlocking metasurfaces (ILMs) are patterned arrays of mating features that enable the joining of bodies by constraining motion and transmitting force. They offer an alternative to traditional joining solutions such as mechanical fasteners, welds, and adhesives. This study explores the development of bio-inspired ILMs using a problem-driven bioinspired design (BID) framework. We develop a taxonomy of attachment solutions that considers both biological and engineered systems and derive conventional design principles for ILM design. We develop two engineering implementations to demonstrate concept development using the taxonomy and ILM conventional design principle through the BID framework: one for rapidly assembled bridge truss members and another for modular microrobots. These implementations highlight the potential of BID to enhance performance, functionality, and tunability in ILMs.

The wings of birds contain complex morphing mechanisms that enable them to perform remarkable aerial maneuvers. Wing morphing is often described using five wingbeat motion parameters: flapping, bending, folding, sweeping, and twisting. However, the specific impact of these motions on the aerodynamic performance of wings throughout the wingbeat cycle, and their potential to inform engineering applications, remains insufficiently explored. To bridge this gap and better incorporate the properties of coupled motions into the design of biomimetic aircraft, we present a numerical investigation of four flapping-based coupled motions during different flight phases (i.e. take-off, level flight, and landing) using a pigeon-like airfoil model. The wingbeat motion data for these four coupled motions were based on real flying pigeons and divided into: flap-bending, flap-folding, flap-sweeping, and flap-twisting. We used computational fluid dynamic simulations to study the effects of these coupled motions on the flow field, generation of transient aerodynamic forces, and work done by different motions on flapping. It was found that, first, the flap-bending motion causes unstable changes in the effective angle of attack (AoA), which affects the attachment of the leading-edge vortex (LEV), thereby producing more lift at smaller bending angles. Next, the flap-folding motion causes the LEV to attach to the wing earlier and regulates the detachment of vortices. Significant changes in the folding angle are used to influence lift generation and the flap-sweeping motion has minimal effect on the flow field structure across the three flight phases. Finally, flap-twisting motion leads to notable changes in the effective AoA, allowing for dynamic adjustments to control aerodynamics at different stroke stages, resulting in less drag during take-off and more drag during landing. This study enhances the understanding of the aerodynamic performance of bird with coupled motions in different flight phases and provides theoretical guidance for the design of bionic flapping-wing aircraft with multi-degree-of-freedom wings.

The study of fish swimming behaviours and locomotion mechanisms holds significant scientific and engineering value. With the rapid advancements in artificial intelligence, a new method combining deep reinforcement learning (DRL) with computational fluid dynamics has emerged and been applied to simulate the fish's adaptive swimming behaviour, where the complex fish behaviour is decoupled to focus on the fish's response to the hydrodynamic field, and the simulation is driven by reward-based objectives to model the fish's swimming behaviour. However, the scale of this cross-disciplinary method is directly affected by the efficiency of the DRL model. To promote it to more general application scenarios, there is a pressing need for further research on more efficient and economical network architectures to address the challenge of approximating state-value function in high-dimensional, dynamic, and uncertain environments. Building upon a previously proposed computational platform for the simulation of fish autonomous swimming behaviour, we integrated Kolmogorov-Arnold Networks(KANs) and tested their performance in point-to-point swimming and Kármán gait swimming environments. Experimental results demonstrated that, compared to long short-term memory Networks(LSTMs) and multilayer perceptron networks(MLPs), the introduction of KANs significantly enhanced the perception and decision-making abilities of the intelligent fish in complex fluid environments. With a smaller network scale, in the point-to-point swimming case, KANs effectively approximated the state-value function, achieving average reward improvements of up to 88.0% and 94.1% over MLPs and LSTMs networks, respectively, and increased by 766.7% and 105.6% in the Kármán gait swimming case. Under comparable network sizes, the intelligent fish with KANs exhibited faster learning capabilities and more stable swimming performance in complex fluid settings.

The special hindleg structure and swimming setae of a water boatman give it a high degree of maneuverability, which plays an important role in swimming. This paper used a high-speed photography platform to extract key points from videos, obtaining the forward and turning movement patterns of the water boatman's hindlegs, as well as the transformation patterns of the setae. A Fourier series was used to establish the movement models of each hindleg joint, and a kinematic model of the hindlegs was established to study the continuous movement characteristics of the hindlegs. This paper provides basic data and theoretical support for the design of underwater bio-inspired robots.

The field of pneumatic soft robotics is on the rise. However, most pneumatic soft robots still heavily rely on rigid valves and conventional electronics for control, which detracts from their natural flexibility and adaptability. Efforts have focused on substituting electronic controllers with pneumatic counterparts to address this limitation. Despite significant progress, contemporary soft control systems still face considerable challenges, as they predominantly depend on pre-programmed commands instead of real-time sensory feedback. To confront these challenges, we propose an electronic-free soft actuator system capable of achieving basic sensorimotor behaviors. The soft actuator employs a fluidic strain sensor to obtain proprioception, detecting changes in air impedance resulting from stretching and compression. Integration of this sensor with a pneumatic valve enables the soft actuator possessing basic sensing and control capabilities. Drawing inspiration from the somatosensory and neuromuscular systems found in biological organisms, we implement both open-loop and closed-loop motion modes using different connection configurations. They facilitate cyclic movement and sensory feedback-regulated motion control using 'material intelligence'. We envisage that this system has the potential to expand to accommodate multiple limbs, thereby pioneering the development of fully fluidic soft robots.

Flying insects are thought to achieve energy-efficient flapping flight by storing and releasing elastic energy in their muscles, tendons, and thorax. However, 'spring-wing' flight systems consisting of elastic elements coupled to nonlinear, unsteady aerodynamic forces present possible challenges to generating stable and responsive wing motion. The energetic efficiency from resonance in insect flight is tied to the Weis-Fogh number (N), which is the ratio of peak inertial force to aerodynamic force. In this paper, we present experiments and modeling to study how resonance efficiency (which increases withN) influences the control responsiveness and perturbation resistance of flapping wingbeats. In our first experiments, we provide a step change in the input forcing amplitude to a series-elastic spring-wing system and observe the response time of the wing amplitude increase. In our second experiments we provide an external fluid flow directed at the flapping wing and study the perturbed steady-state wing motion. We evaluate both experiments across Weis-Fogh numbers from1