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.

Social robots have been widely used to deliver emotional, cognitive and social support to humans. The exchange of affective gestures, instead, has been explored to a lesser extent, despite phyisical interaction with social robots could provide the same benefits as human-human interaction. Some studies that explored the touch and hugs gestures were found in literature, but there are no studies that investigate the possibility of delivering realistic caress gestures, which are, in turn, the easiest affective gestures that could be delivered with a robot. The first objective of this work was to study the kinematic and dynamic features of the caress gesture by conducting experimental acquisitions in which ten healthy volunteers were asked to caress the cheek of a mannequin in two conditions, i.e. standing and sitting. Average motion and force features were then analyzed and used to generate a realistic caress gesture with an anthropomorphic robot, with the aim of assessing the feasibility of reproducing the caress gesture with a robotic device. In addition, twenty-six healthy volunteers evaluated the anthropomorphism and perceived safety of the reproduced affective gesture by answering the Godspeed Questionnaire Series and a list of statements on the robot motion. The gesture reproduced by the robot was similar to the caress gesture performed by healthy volunteers both in terms of hand trajectory and orientation, and exchanged forces. Overall, volunteers perceived the robot motion as safe and positive emotions were elicited. The proposed approach could be adapted to humanoid robots to improve the perceived anthropomorphism and safety of the caress gesture.

Parylene-coated carbon fiber (CF) arrays with tunable inclination angles and heights were fabricated using oxygen plasma etching of composite wafers with embedded parallel CFs, followed by parylene coating via chemical vapor deposition. The effective elastic modulus of the CF arrays was found to decrease approximately in proportion to the square of the fiber length (5-60m), with the parylene coating (∼2m) further slightly reducing the modulus. Both experimental measurements and finite element simulations indicated that CF arrays with inclination angles below 75° exhibit ideal contact with glass wafers during electrostatic adhesion. However, the measured electrostatic adhesion between CF arrays and A4 paper was significantly lower than the predicted value for ideal contact, likely due to the porous nature of the paper. Electrostatic chuck prototypes based on the parylene-coated CF arrays demonstrated effective pick-and-place capabilities for A4 paper, plastic films, and glass wafers at voltages ranging from 500 to 900 V, without causing surface damage or leaving residue. These results highlight the potential of the parylene-coated CF arrays for applications in high-precision manufacturing and automated handling systems.

This article presents a novel bioinspired technology for the cooperation and coordination of heterogeneous robot swarms in uncontrolled environments, utilizing an artificial pheromone composed of magnetized ferrofluids. Communication between different types of robots is achieved indirectly through stigmergy, where messages are inherently associated with specific locations. This approach is advantageous for swarm experimentation outside controlled laboratory spaces, where localization is typically managed through centralized camera systems (e.g. infrared, RGB). Applying pheromone principles has also proven beneficial for various swarm behaviors. We introduce a detection methodology for the artificial ferrofluid pheromone using low-cost magnetic sensors, along with signal processing and parameter characterization. Experiments involved a heterogeneous swarm consisting of two types of robots: one equipped with camera and image processing capabilities and the other with basic sensor technologies. Validation in multiple uncontrolled environments (with varying floor surfaces, wind, and light conditions) demonstrated successful cooperation among robots with differing technological complexities using the proposed technology.

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 also present possible challenges to generating stable and responsive wing motions. The energetic efficiency from resonance in insect flight is measured by 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 with N) 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 from 1 < N < 10. The results indicate that spring-wing systems designed for maximum energetic efficiency also experience trade-offs in agility and stability as the Weis-Fogh number increases. Our results demonstrate that energetic efficiency and wing maneuverability are in conflict in resonant spring-wing systems suggesting that mechanical resonance presents tradeoffs in insect flight control and stability.

When swimming animals form cohesive groups, they can reap several benefits. Our understanding of collective animal motion has traditionally been driven by models based on phenomenological behavioral rules, but more recent work has highlighted the critical importance of hydrodynamic interactions among a group of inertial swimmers. To study how hydrodynamic interactions affect group cohesion, we develop a three-dimensional, inviscid, far-field model of a swimmer. In a group of two model swimmers, we observe several dynamical phases, including following, divergence, collision, and cohesion. Our results illustrate when cohesive groups can passively form through hydrodynamic interactions alone, and when other action is needed to maintain cohesion. We find that misalignment between swimmers makes passive cohesion less likely; nevertheless, it is possible for a cohesive group to form through passive hydrodynamic interactions alone. We also find that the geometry of swimmers critically affects the group dynamics due to its role in how swimmers sample the velocity gradient of the flow.

Flying insects, such as flies and bees, have evolved the capability to rely solely on visual cues for smooth and secure landings on various surfaces. In the process of carrying out tasks, micro unmanned aerial vehicles (UAVs) may encounter various emergencies, and it is necessary to land safely in complex and unpredictable ground environments, especially when altitude information is not accurately obtained, which undoubtedly poses a significant challenge. Our study draws on the remarkable response mechanism of the Lobula Giant Movement Detector to looming scenarios to develop a novel UAV landing strategy. The proposed strategy does not require distance estimation, making it particularly suitable for payload-constrained micro aerial vehicles. Through a series of experiments, this strategy has proven to effectively achieve stable and high-performance landings in unknown and complex environments using only a monocular camera. Furthermore, a novel mechanism to trigger the final landing phase has been introduced, further ensuring the safe and stable touchdown of the drone.

The exploration of adaptive robotic systems capable of performing complex tasks in unstructured environments, such as underwater salvage operations, presents a significant challenge. Traditional rigid grippers often struggle with adaptability, whereas bioinspired soft grippers offer enhanced flexibility and adaptability to varied object shapes. In this study, we present a novel bioinspired soft robotic gripper integrated with a shape memory alloy (SMA) actuated suction cup, inspired by the versatile grasping strategies of octopus arms and suckers. Our design leverages a tendon-driven composite arm, enabling precise bending and adaptive grasping, combined with SMA technology to create a compact, efficient suction mechanism. We develop comprehensive kinematic and static models to predict the interaction between arm bending deflection and suction force, thereby optimizing the gripper's performance. Experimental validation demonstrates the efficacy of our integrated design, highlighting its potential for advanced manipulation tasks in challenging environments. This work provides a new perspective on the integration of bioinspired design principles with smart materials, paving the way for future innovations in adaptive robotic systems. .

When designing the internals of robotic fish, variations in the internal arrangements of power and control systems cause differences in external morphological structures, particularly the positions of maximum thickness. These differences considerably affect swimming performance. This study examines the impact of the topological structure of self-propelled fish-like swimmers on hydrodynamic performance using fluid-structure interaction techniques. Fish-like swimmers with maximum thickness closest to the head exhibit optimal swimming performance, characterized by modest energy consumption for fast-response acceleration during the starting phase and higher swimming velocity for high-speed travel during steady swimming. As the maximum thickness moves toward the middle, acceleration performance significantly weakens and swimming speed decreases, although maximum energy consumption is relatively reduced. This study will provide a notable reference for the morphological design of underwater robotic fish.

Insects' flight is imbued with endless mysteries, offering valuable inspiration to the flapping-wing aircrafts. Particularly, the multi-mode wingbeat motion such as flapping, sweeping and twisting in coordination presents advantages in promoting unsteady aerodynamics and enhancing lift force. To achieve the flapping-twisting-sweeping motion capability, this paper proposes an at-scale three-degree-of-freedom (3-DOF) mechanism driven by three piezoelectric actuators, which consists of three four-bar mechanisms and a parallel spherical mechanism. Compliant hinges are utilized as rotating joints for power transmission. The DOF and the kinematics analysis are per-formed. The aerodynamic model of the wing and the mechanical model of the compliant hinges are considered to investigate the required driving force response of the mechanism with wing loads. By employing nonlinear programming techniques, the geometric parameters of three piezo-electric actuators are reverse-designed to match the dynamic response of the mechanism in two flapping conditions. The significance of this work lies in proposing a novel concept of an at-scale multi-degree-of-freedom wingbeat mechanism, demonstrating the feasibility of this mechanism to mimic the flexible and multi-mode wingbeat movement of insects, and providing an initial mech-anism-drive solution.

Behaviors of animal bipedal locomotion can be described, in a simplified form, by the bipedal spring-mass model. The model provides predictive power, and helps us understand this complex dynamical behavior. In this paper, we analyzed a range of gaits generated by the bipedal spring-mass model during walking, and proposed a stabilizing touch-down condition for the swing leg. This policy is stabilizing against disturbances inside and outside the same energy level and requires only internal state information. In order to generalize the results to be independent of size and dimension of the system, we nondimensionalized the equations of motion for the bipedal spring-mass model. We presented the equilibrium gaits (a.k.a fixed point gaits) as a continuum on the walking state space showing how the different types of these gaits evolve and where they are located in the state space. Then, we showed the stability analysis of the proposed touch-down control policy for different energy levels and leg stiffness values. The results showed that the proposed touch-down control policy can stabilize towards all types of the symmetric equilibrium gaits. Moreover, we presented how the peak leg force change within an energy level and as it changes due to the type of the gait; peak force is important as a measurement of injury or damage risk on a robot or animal. Finally, we presented simulations of the bipedal spring-mass model walking on level ground and rough terrain transitioning between different equilibrium gaits as the energy level of the system changes with respect to the ground height. The analysis in this paper is theoretical, and thus applicable to further our understanding of animal bipedal locomotion and the design and control of robotic systems like ATRIAS, Cassie, and Digit.

In this paper, we present a design optimization framework for a fluidic artificial muscle (FAM) bundle subject to geometric constraints. The architecture of natural skeletal muscles allows for compact actuation packaging by distributing a substantial number of actuation elements, or muscle fiber motor units, which are to be arranged, oriented, and sized in various formations. Many researchers have drawn inspiration from these natural muscle architectures to assist in designing soft robotic systems safe for human-robot interaction. Although there are known tradeoffs identified between different muscle architectures, this optimization framework offers a method to map these architectural tradeoffs to soft actuator designs. The actuation elements selected for this study are fluidic artificial muscles (FAMs) or McKibben muscles due to their inherent compliance, cheap construction, high force-to-weight ratio, and muscle-like force-contraction behavior. Preceding studies analytically modeled the behavior of arranging FAMs in parallel, asymmetrical unipennate, and symmetrical bipennate topologies inspired by the fiber architectures found in human muscle tissues. A more recent study examined the implications of spatial constraints on bipennate FAM bundle actuation and found that by careful design, a bipennate FAM bundle can produce more force, contraction, stiffness, and work output than that of a parallel FAM bundle under equivalent spatial bounds. This multi-objective genetic algorithm-based optimization framework is used to realize desirable topological properties of a FAM bundle for maximum force and stroke for a given spatial envelope. The results help identify tradeoffs to inform design decisions based on the force and stroke demand from the desired operating task. This study further demonstrates how the desirable topological properties of the optimized FAM bundle change with different spatial bounds. .

This paper presents the development and control of a dynamic model for a plant-inspired growing robot, termed the 'vine-robot', using the Euler-Lagrangian method. The unique growth mechanism of the vine-robot enables it to navigate complex environments by extending its body. We derive the dynamic equations of motion and employ model predictive control to regulate the task space position, orientation, and interaction forces. Simulation experiments are conducted to evaluate the performance of the proposed model and control strategy. The results demonstrate that the model effectively achieves sub-millimeter precision in the position control in both static and time varying refrence trajectroies, and sub micronewton in force control.

The robotic fish utilizes a bio-inspired undulatory propulsion system to achieve high swimming performance. However, significant roll motion has been observed at the head when the tail oscillates at certain frequencies, adversely affecting both perception accuracy and propulsion efficiency. In this paper, the roll torque acting on the robotic fish is theoretically analyzed and decomposed into gravitational, inertial, and hydrodynamic components. Resonance is identified as a key factor amplifying the roll response. To mitigate this roll and enhance stability, a passive roll absorber based on tuned mass damper is designed. A simplified rolling structure is dynamically modeled to optimize absorber parameters. Experiments are conducted to quantify the roll torque experienced by the robotic fish, with the effectiveness of the absorber verified on both the simplified model and the robotic fish. Results show that the maximum roll angle of the simplified system under harmonic load decreases from 98 degrees to 29 degrees, representing a reduction of over 70%, while a 25.1% reduction is achieved on the robotic fish.

Recently, vision-based unmanned aerial vehicle (UAV) swarming has emerged as a promising alternative that can overcome the adaptability and scalability limitations of distributed and communication-based UAV swarm systems. While most vision-based control algorithms are predicated on the detection of neighboring objects, they often overlook key perceptual factors such as visual occlusion and the impact of visual sensor limitations on swarm performance. To address the interaction problem of neighbor selection at the core of self-organizing UAV swarm control, a perceptually realistic finite perception visual (FPV) neighbor selection model is proposed, which is based on the lateral visual characteristics of birds, incorporates adjustable lateral visual field widths and orientations, and is able to ignore occluded agents. Based on the FPV model, a neighbor selection method based on the acute angle test (AAT) is proposed, which overcomes the limitation that the traditional neighbor selection mechanism can only interact with the nearest neighboring agents. A large number of Monte Carlo simulation comparison experiments show that the proposed FPV+AAT neighbor selection mechanism can reduce the redundant communication burden between large-scale self-organized UAV swarms, and outperforms the traditional neighbor selection method in terms of order, safety, union, connectivity, and noise resistance.

This paper presents a numerical investigation into the aerodynamic characteristics and fluid dynamics of a flying snake-like model employing vertical bending locomotion during aerial undulation in steady gliding. In addition to its typical horizontal undulation, the modeled kinematics incorporates vertical undulations and dorsal-to-ventral bending movements while in motion. Using a computational approach with an incompressible flow solver based on the immersed-boundary method, this study employs Topological Local Mesh Refinement (TLMR) mesh blocks to ensure the high resolution of the grid around the moving body. Initially, we applied a vertical wave undulation to a snake model undulating horizontally, investigating the effects of vertical wave amplitudes (ψ_m). The vortex dynamics analysis unveiled alterations in leading-edge vortices (LEV) formation within the midplane due to changes in the effective angle of attack resulting from vertical bending, directly influencing lift generation. Our findings highlighted peak lift production at ψ_m=2.5° and the highest lift-to-drag ratio at ψ_m=5°, with aerodynamic performance declining beyond this threshold. Subsequently, we studied the effects of the dorsal-ventral bending amplitude (ψ_DV), showing that the tail-up/down body posture can result in different fore-aft body interactions. Compared to the baseline configuration, the lift generation is observed to increase by 17.3% at ψ_DV = 5°, while a preferable lift-to-drag ratio is found at ψ_DV = -5°. This study explains the flow dynamics associated with vertical bending and uncovers fundamental mechanisms governing body-body interaction, contributing to the enhancement of lift production and efficiency of aerial undulation in snake-inspired gliding.

In recent years, the micro air vehicle (MAV) oscillations caused by thrust imbalances have received more attention. This paper proposes a dual-wing thrust balance model (DTBM) that can solve the above problem by iterating the modified rotation angle formula. The core control parameter of the DTBM model is the au angle, which refers to the angle between the wing surface and the stroke plane at the mid-stroke position during the upstroke. For each degree change in the au angle, the range of variation in the dimensionless average thrust coefficient is between 0.0225-0.0268. A thrust coefficient of 0.0225 causes the dragonfly to move forward by 9.037 cm in one second, which is equivalent to 1.29 times its body length. By using DTBM, the average thrust coefficient can be reduced to below 0.001 in just a few iterations. No matter how complex the motion pattern is, the DTBM can achieve thrust balance within 0.278 s. Through our research, when selecting the deviation angle motion of real dragonflies, the dual-wing au angles exhibit a highly linear correlation with wing spacing, called linear motion. In contrast, the nonlinear variation of the au angle appears in the hindwing of the no-deviation motion and the forewing of the elliptical deviation motion. All of the nonlinear changes are referred to as nonlinear motion. Nonlinear variation of the au angle arises from larger disturbances of the lateral force during the upstroke. The stronger lateral force is closely related to the flapping trajectory. When the flapping trajectory causes the dual-wing to closely approach each other in the mid-stroke, a continuous positive pressure zone forms between the dual-wing. The collision of the leading-edge vortex and the shedding of the trailing-edge vortex is the special flow field structure in the nonlinear motion. Guided by the DTBM, future designs of MAVs will be able to better achieve thrust balance during hovering flight, requiring only the embedding of the iteration algorithm and prediction function of the DTBM in the internal chip.

Probes that penetrate soil are used in fields such as geotechnical engineering, agriculture, and ecology to classify soils and characterize their properties. Conventional tools such as the Cone Penetration Test (CPT) often face challenges due to the lack of reaction force needed to penetrate stiff or dense soil layers, necessitating the use of large drill rigs. This paper investigates more efficient means of penetrating soil by taking inspiration from a plant-root motion known as circumnutation. Experimental penetration tests on sands are performed with circumnutation-inspired (CI) probes that advance at a constant vertical velocity (v) while simultaneously rotating at a constant angular velocity (ω). These probes have bent tips with a given bent angle (α) and bent length (L1). The variation of the mobilized vertical force (Fz), torque (Tz.), and the mechanical work components with the ratio of tangential to vertical velocity (/, whereis the distance of the tip of the probe from the vertical axis of rotation) is investigated along with the effects of probe geometry, vertical velocity, and soil relative density (DR). The results show that the soil penetration resistance does not vary withv, but it increases asα,L1, andDRare increased.Fzdecays exponentially with increasingωR/v,Tzinitially increases and then plateaus, while total work (WT) shows little magnitude changes initially but later increases monotonically. The mechanisms leading to these trends are identified as the changes in the probe projected areas and mobilized normal stresses due to differences in probe geometry and the effects ofωR/von the resultant force direction and soil disturbance. The results show that CI penetration within a specific range ofωR/vleads to small increases inWT(i.e.,⩽25%), yet mobilizesFzmagnitudes that are 50%-80% lower than that mobilized during non-rotational penetration (i.e., CPT). This indicates that CI penetration can be adopted forcharacterization or sensor placement with smaller vertical forces, allowing for use of lighter rigs.

Embedded, flexible, multi-sensor sensing networks have shown the potential to provide soft robots with reliable feedback while navigating unstructured environments. Time delay associated with extracting information from these sensing networks and the complexity of constructing them are significant obstacles to their development. This paper presents a novel enhancement to an existing class of embedded sensor network with the potential to overcome these challenges. In its original version, this sensor network extracts information from multiple reactive sensors on a two-wire electrical circuit simultaneously. This paper proposes to change the excitation signal applied to this sensor network to a binary signal. This change offers two key advantages: it provides the ability to employ small, inexpensive microcontrollers and results in a faster data extraction process. The potential of this enhanced system is demonstrated here with a proof of concept implementation. The self-inductance of all inductance-based sensors within this proof of concept sensor network can be measured at a rate of over 5000 times per second with an average measurement error of less than 2%.

Animals use active sensing movements to shape the spatiotemporal characteristics of sensory signals to better perceive their environment under varying conditions. However, the underlying mechanisms governing the generation of active sensing movements are not known. To address this, we investigated the role of active sensing movements in the refuge tracking behavior of, a species of weakly electric fish. These fish track the longitudinal movements of a refuge in which they hide by swimming back and forth in a single linear dimension. During refuge tracking,exhibits stereotyped whole-body oscillations when the quality of the sensory signals degrades. We developed a closed-loop feedback control model to examine the role of these ancillary movements on the task performance. Our modeling suggests that fish may use active sensing to minimize predictive uncertainty in state estimation during refuge tracking. The proposed model generates simulated fish trajectories that are statistically indistinguishable from that of the actual fish, unlike the open-loop noise generator and stochastic resonance generator models in the literature. These findings reveal the significance of closed-loop control in active sensing behavior, offering new insights into the underlying mechanisms of dynamic sensory modulation.