Bioinspiration & Biomimetics最新文献

A central pattern generator (CPG)-based controller enhances the adaptability of quadrupedal locomotion, for example, by controlling the trunk posture. The conventional CPG-based controllers with attitude control often utilized the posture angle as feedback information. However, if the robot's body is as soft as a musculoskeletal structure, it can detect the over-tilting of the trunk based on proprioceptive information of the muscles. In general, proprioceptive information such as muscle tension changes more rapidly than posture angle information. Therefore, a feedback loop based on proprioceptive information has great potential to respond to sudden disturbances that occur during locomotion over uneven terrain. In this research, we proposed a CPG-based controller utilizing the tension of soft pneumatic artificial muscles (PAMs). Musculoskeletal quadruped robots driven by PAMs are so soft, which prevents over-tilting of the trunk because the soft leg acts like a suspension. In addition, tension, one of the proprioceptive information of PAMs, exhibits high sensitivity to changes in trunk posture because the soft body's motion easily is affected by over-tilting of the trunk. To validate the efficacy of the proposed controller, we conducted numerical simulations with a simple quadruped model and experiments with a musculoskeletal quadruped robot. As a result, the tension feedback is not effective for posture stabilization on flat terrain whereas it is effective on uneven terrain. Moreover, the tension feedback improved the running velocity over uneven terrain. These results will enhance the locomotion capability of musculoskeletal quadruped robots, advancing their practical application.

Bird flight is often characterized by outstanding aerodynamic efficiency, agility and adaptivity in dynamic conditions. Feathers play an integral role in facilitating these aspects of performance, and the benefits feathers provide largely derive from their intricate and hierarchical structures. Although research has been attempted on developing membrane-type artificial feathers for bio-inspired aircraft and micro air vehicles (MAVs), fabricating anatomically accurate artificial feathers to fully exploit the advantages of feathers has not been achieved. Here, we present our 3D printed artificial feathers consisting of hierarchical vane structures with feature dimensions spanning from 10^-2to 10²mm, which have remarkable structural, mechanical and aerodynamic resemblance to natural feathers. The multi-step, multi-scale 3D printing process used in this work can provide scalability for the fabrication of artificial feathers tailored to the specific size requirements of aircraft wings. Moreover, we provide the printed feathers with embedded aerodynamic sensing ability through the integration of customized piezoresistive and piezoelectric transducers for strain and vibration measurements, respectively. Hence, the 3D printed feather transducers combine the aerodynamic advantages from the hierarchical feather structure design with additional aerodynamic sensing capabilities, which can be utilized in future biomechanical studies on birds and can contribute to advancements in high-performance adaptive MAVs.

A beluga-like model of click train signal is developed by observing beluga's sound recording. To reproduce the feature of the biosonar signal, this paper uses a signal extracting method with a correction factor of inter-click interval to acquire the parameter of click trains. The extracted clicks were analyzed in the time and frequency domain. Furthermore, a joint pulse-frequency representation was undertaken in order to provide a 2D energy distribution for an echolocation click train. The results from joint pulse-frequency representation indicate that click train can be adjusted its energy distribution by using a multi-component signal structure. To evaluate the capability of the click train to inform the whale of relevant target information perception for the click train, a finite element model is built to reproduce target discrimination by the bio-inspired click train. Numerical results indicate that the bio-inspired click train could enhance the echo-response by concentrating energy into the frequency bins for extracting target feature effectively. This proof-of-concept study suggests that the model of click train could be dynamically controlled to match the target properties, and show a promising way to use various types of echolocation click train to interrogate different features of the target by man-made sonar.

Locomotion on soft yielding grounds is more complicated and energetically demanding than on hard ground. Wet soft ground (such as mud or snow) is a particularly difficult substance because it dissipates energy when stepping and resists extrusion of the foot. Sinkage in mud forces walkers to make higher steps, thus, to spend more energy. Yet wet yielding terrains are part of the habitat of numerous even-toed ungulates (large mammals with split hooves). We hypothesized that split hooves provide an advantage on wet grounds and investigated the behavior of moose legs on a test rig. We found that split hooves of a moose reduce suction force at extrusion but could not find conclusive evidence that the hoof reduces sinkage. We then continued by designing artificial feet equipped with split-hoof-inspired protuberances and testing them under different conditions. These bio-inspired feet demonstrate an anisotropic behavior enabling reduction of sinkage depth up to 46.3%, suction force by 47.6%, and energy cost of stepping on mud by up to 70.4%. Finally, we mounted these artificial feet on a Go1 quadruped robot moving in mud and observed 38.7% reduction of the mechanical cost of transport and 55.0% increase of speed. Those results help us understand the physics of mud locomotion of animals and design better robots moving on wet terrains. We did not find any disadvantages of the split-hooves-inspired design on hard ground, which suggests that redesigning the feet of quadruped robots improves their overall versatility and efficiency on natural terrains.

Bird-like flapping-wing aerial vehicles (BFAVs) have attracted significant attention due to their advantages in endurance, range, and load capacity. For a long time, biologists have been studying the enigma of bird flight to understand its mechanism. In contrast, aviation designers focus more on bionic flight systems. This paper presents a comprehensive review of the development of BFAV design. The study aims to provide insights into building a flyable model from the perspective of aviation designers, focusing on the methods in the process of overall design, flapping wing design and drive system design. The review examines the annual progress of flight-capable BFAVs, analyzing changes in prototype size and performance over the years. Additionally, the paper highlights various applications of these vehicles. Furthermore, it discusses the challenges encountered in BFAV design and proposes several possible directions for future research, including perfecting design methods, improving component performance, and promoting practical application. This review will provide essential guidelines and insights for designing BFAVs with higher performance.

Inspired by animals that co-adapt their brain and body to interact with the environment, we present a tendon-driven and over-actuated (i.e.njoint,n+1 actuators) bipedal robot that (i) exploits its backdrivable mechanical properties to manage body-environment interactions without explicit control,and(ii) uses a simple 3-layer neural network to learn to walk after only 2 min of 'natural' motor babbling (i.e. an exploration strategy that is compatible with leg and task dynamics; akin to childsplay). This brain-body collaboration first learns to produce feet cyclical movements 'in air' and, without further tuning, can produce locomotion when the biped is lowered to be in slight contact with the ground. In contrast, training with 2 min of 'naïve' motor babbling (i.e. an exploration strategy that ignores leg task dynamics), does not produce consistent cyclical movements 'in air', and produces erratic movements and no locomotion when in slight contact with the ground. When further lowering the biped and making the desired leg trajectories reach 1 cm below ground (causing the desired-vs-obtained trajectories error to be unavoidable), cyclical movements based on either natural or naïve babbling presented almost equally persistent trends, and locomotion emerged with naïve babbling. Therefore, we show how continual learning of walking in unforeseen circumstances can be driven by continual physical adaptation rooted in the backdrivable properties of the plant and enhanced by exploration strategies that exploit plant dynamics. Our studies also demonstrate that the bio-inspired co-design and co-adaptations of limbs and control strategies can produce locomotion without explicit control of trajectory errors.

Soft peristaltic pumps, which use soft ring actuators instead of mechanical pistons or rollers, offer advantages in transporting liquids with non-uniform solids, such as slurry, food, and sewage. Recent advances in 3D printing with flexible thermoplastic polyurethane (TPU) present the potential for single-step fabrication of these pumps, distinguished from handcrafted, multistep traditional silicone casting methods. However, because of the relatively high hardness of TPU, TPU-based soft peristaltic pumps contract insufficiently and thus cannot perform as well as silicone-based ones. Improving the performance is crucial for fully automated, one-step manufactured soft pumps to lead to industrial use. This study aims to enhance TPU-based soft pumps through bioinspired design. Specifically, it proposed a design inspired by embryonic tubular hearts, in contrast to previous studies that mimicked digestive tracts. The new design facilitated long-axis stretching of an elliptical lumen during non-concentric contractile motion, akin to embryonic tubular hearts. The design was optimized for ring actuators and pumps 3D-printed with shore hardness 85 A TPU filament. The ring actuator achieved over 99% lumen closure with the best designs. The soft pumps transported water at flow rates of up to 218 ml min^-1and generated a maximum discharge pressure of 355 mm Hg, comparable to the performance of blood pumps used in continuous renal replacement therapy.

For decades, the field of biologically inspired robotics has leveraged insights from animal locomotion to improve the walking ability of legged robots. Recently, 'biomimetic' robots have been developed to model how specific animals walk. By prioritizing biological accuracy to the target organism rather than the application of general principles from biology, these robots can be used to develop detailed biological hypotheses for animal experiments, ultimately improving our understanding of the biological control of legs while improving technical solutions. In this work, we report the development and validation of the robot Drosophibot II, a meso-scale robotic model of an adult fruit fly,Drosophila melanogaster. This robot is novel for its close attention to the kinematics and dynamics ofDrosophila, an increasingly important model of legged locomotion. Each leg's proportions and degrees of freedom have been modeled afterDrosophila3D pose estimation data. We developed a program to automatically solve the inverse kinematics necessary for walking and solve the inverse dynamics necessary for mechatronic design. By applying this solver to a fly-scale body structure, we demonstrate that the robot's dynamics fit those modeled for the fly. We validate the robot's ability to walk forward and backward via open-loop straight line walking with biologically inspired foot trajectories. This robot will be used to test biologically inspired walking controllers informed by the morphology and dynamics of the insect nervous system, which will increase our understanding of how the nervous system controls legged locomotion.

The contact behaviour of mushroom-shaped pillars has been extensively studied for their superior adhesive properties, often inspired by natural attachment systems observed in insects. Typically, pillars are modeled with linear elastic materials in the literature; in reality, the soft materials used for their fabrication exhibit a rate-dependent constitutive behaviour. Additionally, conventional models focus solely on the detachment phase of the pillar, overlooking the analysis of the attachment phase. As a result, they are unable to estimate the energy loss during a complete loading-unloading cycle. This study investigates the role of viscoelasticity in the adhesion between a mushroom-shaped pillar and a rigid flat countersurface. Interactions at the interface are assumed to be governed by van der Waals forces, and the material is modeled using a standard linear solid model. Normal push and release contact cycles are simulated at different approaching and retracting speeds. Results reveal that, in the presence of an interfacial defect, a monotonically increasing trend in the pull-off force with pulling speed is observed. The corresponding change in the contact pressure distribution suggests a transition from short-range to long-range adhesion, corroborating recent experimental and theoretical investigations. Moreover, the pull-off force remains invariant to the loading history due to our assumption of a flat-flat contact interface. Conversely, in the absence of defects and under the parameters used in this study, detachment occurs after reaching the theoretical contact strength, and the corresponding pull-off force is found to be rate independent. Notably, the hysteretic loss exhibits a peak at intermediate detachment speeds, where viscous dissipation occurs, which holds true in both the presence and absence of a defect. However, the presence of a defect shifts the region where the majority of viscous dissipation takes place.