Bioinspiration & Biomimetics最新文献

Limited research exists on the 3D geometric models and as a consequence the aerodynamic characteristics of the grey-headed albatross (GHA). Despite existing methods for extracting bird wing cross-sections, few studies consider deflections due to aerodynamic pressure. With the GHA known for its exceptional flight speed and purported wing-lock mechanism, it offers a valuable subject for studying fixed-wing aerodynamics in nature. This study aims to develop and validate a numerical approach to estimate the GHA's wing cross-section in flight. The PARSEC method is combined with a scanned 3D point cloud of a dried GHA wing to create a 3D model and analyse an averaged aerofoil section. Using a pseudo-2D computational fluid dynamics model, the study explores passive morphing of bird wings due to aerodynamic pressure. Results show that the aerofoil morphs to achieve maximum potential aerodynamic efficiency at a Reynolds number of2×105, decreasing in camber. The maximum lift-to-drag ratio ((CL/CD)max) increases from 3 to 44, primarily due to pressure drag reduction. However, the lack of comparison to true bird geometry in flight remains a limitation. Future research should compare the predicted morphing with actual bird specimens in flight.

Earthworm-like robots have excellent locomotion capability in confined environments. Central pattern generator (CPG) based controllers utilize the dynamics of coupled nonlinear oscillators to spontaneously generate actuation signals for all segments, which offer significant merits over conventional locomotion control strategies. There are a number of oscillators that can be exploited for CPG control, while their performance in controlling peristaltic locomotion has not been systematically evaluated. To advance the state of the art, this study comprehensively evaluates the performance of four widely used nonlinear oscillators-Hopf, Van der Pol (VDP), Matsuoka, and Kuramoto-in controlling the planar locomotion of metameric earthworm-like robots. Specifically, the amplitude and phase characteristics of the continuous control signals used by the robot for achieving rectilinear, sidewinding, and arcuate locomotion are first summarized. On this basis, the sufficient parametric conditions for the four oscillator networks to generate the corresponding control signals are derived. Using a six-segment earthworm-like robot prototype as a platform, experiments confirm that the signals output by these oscillator networks can effectively control the robot to achieve the specified planar motion. Furthermore, the effects of the output signal waveforms of different oscillator networks on locomotion trajectories and performance metrics, as well as the effects of transient dynamics on the smoothness of gait transitions when the parameters are varied, are analyzed. The results demonstrate that their applicability varies in terms of locomotion efficiency, trajectory modulation, and smooth gait transitions. The Matsuoka oscillator lacks explicit rules for parameter modulation, the VDP oscillator is advantageous in enhancing the average speed and turning efficiency, and the Hopf and Kuramoto oscillators are advantageous in terms of smooth gait transition. These findings provide valuable insights into the selection of appropriate oscillators in CPG-based controllers and lay the foundation for future CPG-based adaptive control of earthworm-like robots in complex environments.

Animals have to navigate complex environments and perform intricate swimming maneuvers in the real world. To conquer these challenges, animals evolved a variety of motion control strategies. While it is known that many factors contribute to motion control, we specifically focus on the role of stretch sensory feedback. We investigate how stretch feedback potentially serves as a way to coordinate locomotion, and how different stretch feedback topologies, such as networks spanning varying ranges along the spinal cord, impact the locomotion. We conduct our studies on a simulated robot model of the lamprey consisting of an articulated spine with eleven segments connected by actuated joints. The stretch feedback is modeled with neural networks trained with deep reinforcement learning. We find that the topology of the feedback influences the energy efficiency and smoothness of the swimming, along with various other metrics characterizing the locomotion, such as frequency, amplitude and stride length. By analyzing the learned feedback networks, we highlight the importances of very local, caudally-directed, as well as stretch derivative information. Our results deliver valuable insights into the potential mechanisms and benefits of stretch feedback control and inspire novel decentralized control strategies for complex robots.

Due to the complexity of deformations in soft manipulators, achieving precise control of their orientation is particularly challenging, especially in the presence of external disturbances and human interactions. Inspired by the decentralized growth mechanism of plant gravitropism, which enables plants' roots and stems to grow in the direction of gravity despite complex environmental interactions, this study proposes a decentralized control strategy for robust orientation control of multi-segment soft manipulators. This gravitropism-inspired decentralized controller was validated through simulations for convergence and robustness, and benchmarked against the traditional inverse Jacobian-based controller on a large-scale multi-segment soft manipulator. Experimental results demonstrate that the decentralized controller achieves comparable convergence and better control precision to the inverse Jacobian-based controller, while significantly outperforming it in disturbance rejection. Even in the presence of partial damage and human interaction, the decentralized controller provides robust control. This study provides a robust new approach for managing disturbances in complex environments, laying the foundation for further exploration of decentralized control strategies in soft robotics.

One of the most ancient and evolutionarily conserved behaviors in the animal kingdom involves utilizing wind-borne odor plumes to track essential elements such as food, mates, and predators. Insects, particularly flies, demonstrate a remarkable proficiency in this behavior, efficiently processing complex odor information encompassing concentrations, direction, and speed through their olfactory system, thereby facilitating effective odor-guided navigation. Recent years have witnessed substantial research explaining the impact of wing flexibility and kinematics on the aerodynamics and flow field physics governing the flight of insects. However, the relationship between the flow field and olfactory functions remains largely unexplored, presenting an attractive frontier with numerous intriguing questions. One such question pertains to whether flies intentionally manipulate the flow field around their antennae using their wing structure and kinematics to augment their olfactory capabilities. To address this question, we first reconstructed the wing kinematics based on high-speed video recordings of wing surface deformation. Subsequently, we simulated the unsteady flow field and odorant transport during the forward flight of blue bottle flies (Calliphora vomitoria) by solving the Navier-Stokes equations and odorant advection-diffusion equations using an in-house computational fluid dynamics (CFD) solver. Our simulation results demonstrated that flexible wings generated greater cycle-averaged aerodynamic forces compared to purely rigid flapping wings, underscoring the aerodynamic advantages of wing flexibility. Additionally, flexible wings produced 25% greater odor intensity, enhancing the insect's ability to detect and interpret olfactory cues. This study not only advances our understanding of the intricate interplay between wing motion, aerodynamics, and olfactory capabilities in flying insects but also raises intriguing questions about the intentional modulation of flow fields for sensory purposes in other behaviors.

Resilience is a vital aspect of modern systems, especially in multi-agent systems, where faulted agents (agents who do not behave properly) can compromise system performance. In response to this need for resilience, we turn to biological inspiration. Eusocial insects are a subset of insects that have caste-based labor distribution and cooperative brood care. These insects face analogous challenges in maintaining and improving resilience to external threats, making them prime examples to find unique biological solutions to resilience problems. Thus, the central question of this work is:How can eusocial insect behavior be used to inspire new approaches to prevent or limit faulted agents from impacting the performance of multi-agent systems? Engineers, however, do not always have the necessary biological expertise to identify behaviors to mimic. This article seeks to fill the following identified gap in current research and resources:There is need to study the impact of biologically inspired behaviors on faulted agent resilience, but engineers may struggle to identify sources in the biological literature to translate into engineering applications.To address this question and the identified gap, we provide a guide identifying a large range of insect resilience behaviors and examples of possible implementation of these behaviors. This guide is a functional decomposition examining how eusocial insects prevent disease propagation that engineers can transfer to their systems when seeking to mitigate faulted agents. The presented functional decomposition is made of 148 identified functions across 7 levels, organized into 5 primary categories. This provides a guide for engineers to use when looking for sources of inspiration to improve system resilience. Additional discussion is also provided to offer potential implementations of these 148 functions, so as to encourage further work and usage of this work.

Natural photonic structures allow us to reveal and mold the thermophoretic effect at the nanoscale within condensed matter systems. In this paper, for the first time, holography has been exploited to disclose conditions that determine the strength and dynamics of the thermophoretic effect. We experimentally revealed the link between geometry and nano-corrugation of biological structures that shapes the power of thermophoresis. The presented study opens enormous possibilities for harnessing thermophoretic effect in various bioinspired sensing applications uniquely merging the fields of photonics and mechanics. .

A transverse ledge brachiation robot is designed to move transversely along a ledge on a vertical wall by generating energy from the swinging motion of its lower limbs. This method reduces the force required by the upper limbs to propel the robot forward. However, previously developed robots often encounter a common issue: lateral posture deviation, which is typically caused by slippage when the grippers grasp the ledge. Without compensation, this deviation can increase the risk of falling during continuous brachiation cycles. To address this problem, we propose an active wrist joint mechanism utilizing a feedback control approach as the compensator to effectively correct gripper position deviations. In our robot design, we develop a motion control strategy that coordinates the upper and lower limbs in order to maintain the swing energy that can be transferred to the subsequent cycles. Then we propose a potential energy-based phase switching condition in the motion control strategy in order to simplify the computation process. Simulation results demonstrate that the optimized parameter for compensation effectively maintains the gripper's position relative to the ledge throughout 55 brachiation cycles. Furthermore, experiment validation shows that this posture compensation reduces deviation by one-third compared to results without compensation. This study has demonstrated a 68% improvement in energy consumption efficiency for continuous transverse brachiation compared to the previous generation, as well as a 37% improvement over transverse ricochetal brachiation locomotion.

When the beetle lands on the target, the hind wings fold regularly to form smaller wing packages and are hidden on the ventral side of the elytra due to the interaction between the elytra and abdomen. Its complex folding pattern is attributed to the flexibility of the hind wings, the super-elasticity of the folding joints, and the special geometric morphology of the veins. The corrugation and folding pattern of the hind wings can provide new insights for the design of folding anti-collision mechanisms and the improvement of aerodynamic performance of ornithopter. This paper first proposes a beetle-type ornithopter with foldable wings based on the folding mechanism and kinematic characteristics of the beetle's hind wings. Subsequently, a series of numerical simulations were conducted on flapping wing robot to explore its flapping kinematics, folding stability, structural stiffness. Finally, the force generation of flapping wings was tested on the fabricated prototype.

Bionic flapping wing robots achieve flight by imitating animal flapping wings, which are safe, flexible, and efficient. Their practicality and human-machine symbiosis in narrow and complex environments are better than those of traditional fixed-wing or multirotor drones, which shows a broader application prospect. By systematic and biomimetic methods, a bionic dragonfly robot with four independent drive flapping wings, called DFly-I, was designed. First of all, the mechanical structure of the robot was introduced, especially the fluttering structure and the wing structure. Then, a new motion controller based on multi-channel field-oriented control (FOC) is proposed for its motion mechanism, which relies on four sets of brushless DC motors (BLDCs) based on FOC control and four sets of servos to achieve independent control of the flapping speed, rhythm, and angle of four flapping wings. In addition, the system model is analyzed, and on this basis, the robot motion and posture control are realized by an proportional-integral-derivative and active disturbance rejection (PID-ADRC) based controller. Lastly, a physical prototype was made, and the system was feasible through flight experiments in indoor venues.