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 measure 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-extension of the leg and over-tilting of the trunk to some extent. 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 changes due to over-titing 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 was effective for posture stabilization when the robot's locomotion was subjected to disturbances. Moreover, the tension feedback was effective in improving the running velocity over uneven terrain. These results will enhance the locomotion capability of musculoskeletal quadruped robots, advancing their practical application. .

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 85A 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 and generated a maximum discharge pressure of 355 mmHg, comparable to the performance of blood pumps used in continuous renal replacement therapy. .

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.

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 of Drosophila, an increasingly important model of legged locomotion. Each leg's proportions and degrees of freedom have been modeled after Drosophila 3D 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.

A remarkable variety of organisms use metachronal coordination (i.e. numerous neighboring appendages beating sequentially with a fixed phase lag) to swim or pump fluid. This coordination strategy is used by microorganisms to break symmetry at small scales where viscous effects dominate and flow is time-reversible. Some larger organisms use this swimming strategy at intermediate scales, where viscosity and inertia both play important roles. However, the role of individual propulsor kinematics-especially across hydrodynamic scales-is not well-understood, though the details of propulsor motion can be crucial for the efficient generation of flow. To investigate this behavior, we developed a new soft robotic platform using magnetoactive silicone elastomers to mimic the metachronally coordinated propulsors found in swimming organisms. Furthermore, we present a method to passively encode spatially asymmetric beating patterns in our artificial propulsors. We investigated the kinematics and hydrodynamics of three propulsor types, with varying degrees of asymmetry, using Particle Image Velocimetry and high-speed videography. We find that asymmetric beating patterns can move considerably more fluid relative to symmetric beating at the same frequency and phase lag, and that asymmetry can be passively encoded into propulsors via the interplay between elastic and magnetic torques. Our results demonstrate that nuanced differences in propulsor kinematics can substantially impact fluid pumping performance. Our soft robotic platform also provides an avenue to explore metachronal coordination at the meso-scale, which in turn can inform the design of future bioinspired pumping devices and swimming robots.

To analyse walking, running or hopping motions, models with high degrees of freedom are usually used. However simple reductionist models are advantageous within certain limits. In a simple manner, the hopping motion is generally modelled by a spring-mass system, resulting in piecewise smooth dynamics with marginally stable periodic solutions. For a more realistic behaviour, the spring is replaced by a variety of muscle models due to which asymptotically stable periodic motions may occur. The intrinsic properties of the muscle model, i.e. preflexes, are usually taken into account in three complexities-constant, linear and Hill-type. In this paper, we propose a semi-closed form feed-forward control which represents the muscle activation and results in symmetrical hopping motion. The research question is whether hopping motions with symmetric force-time history have advantages over asymmetric ones in two aspects. The first aspect is its applicability for describing human motion. The second aspect is related to robotics where the efficiency is expressed in term of performance measures. The symmetric systems are compared with each other and with those from the literature using performance measures such as hopping height, energetic efficiency, stability of the periodic orbit, and dynamical robustness estimated by the local integrity measure (LIM). The paper also demonstrates that the DynIn MatLab Toolbox that has been developed for the estimation of the LIM of equilibrium points is applicable for periodic orbits.

Like other odontocetes, Risso's dolphins actively emit clicks and passively listen to the echoes during echolocation. However, the head anatomy of Risso's dolphins differs from that of other odontocetes by a unique vertical cleft along the anterior surface of the forehead and a differently-shaped lower jaw. In this study, 3D finite-element sound reception and production models were constructed based on computed tomography (CT) data of a deceased Risso's dolphin. Our results were verified by finding good agreement with experimental measurements of hearing sensitivity. Moreover, the acoustic pathway for sounds to travel from the seawater into the dolphin's tympanoperiotic complexes (TPCs) was computed. The gular reception mechanism, previously discovered inDelphinus delphisandZiphius cavirostris, was also found in this species. The received sound pressure levels and relative displacement at TPC surfaces were compared between the cases with and without the mandibular fats or mandible. The results demonstrate a pronounced wave-guiding role of the mandibular fats and a limited bone-conductor role of the mandible. For sound production modelling, we digitally filled the cleft with neighbouring soft tissues, creating a hypothetical 'cleftless' head. Comparison between sound travelling through a 'cleftless' head vs. an original head indicates that the distinctive cleft plays a limited role in biosonar sound propagation.

Autonomous ocean-exploring vehicles have begun to take advantage of onboard sensor measurements of water properties such as salinity and temperature to locate oceanic features in real time. Such targeted sampling strategies enable more rapid study of ocean environments by actively steering towards areas of high scientific value. Inspired by the ability of aquatic animals to navigate via flow sensing, this work investigates hydrodynamic cues for accomplishing targeted sampling using a palm-sized robotic swimmer. As proof-of-concept analogy for tracking hydrothermal vent plumes in the ocean, the robot is tasked with locating the center of turbulent jet flows in a 13,000-liter water tank using data from onboard pressure sensors. To learn a navigation strategy, we first implemented RL on a simulated version of the robot navigating in proximity to turbulent jets. After training, the RL algorithm discovered an effective strategy for locating the jets by following transverse velocity gradients sensed by pressure sensors located on opposite sides of the robot. When implemented on the physical robot, this gradient following strategy enabled the robot to successfully locate the turbulent plumes at more than twice the rate of random searching. Additionally, we found that navigation performance improved as the distance between the pressure sensors increased, which can inform the design of distributed flow sensors in ocean robots. Our results demonstrate the effectiveness and limits of flow-based navigation for autonomously locating hydrodynamic features of interest.