Dual-arm robots are gaining prominence in modern industrial automation, particularly in smart manufacturing, driven by their exceptional flexibility, collaborative potential, and anthropomorphic design. Modern applications increasingly demand capabilities in complex assembly, precision manipulation, and close human-robot interaction. Consequently, integrating dexterous wrist joints into dual-arm systems has emerged as a critical research frontier to enhance their adaptability and collaborative performance. This study presents a lightweight, modular, and dexterous robotic wrist inspired by human wrist anatomy. The physical prototype is highly compact, weighing 496 g with a volume of 436 cm³. Experimental results demonstrate a payload capacity of 2 kg and spatial rotations comparable to human wrist flexion and extension. The robotic wrist is driven by an encoder-equipped servo motor and incorporates a high-precision Inertial Measurement Unit (IMU) for spatial orientation tracking. Real-time IMU feedback of three-axis angular variations enables dynamic adjustment of the motor torque, thereby ensuring stable payload performance and spatial adaptability. To validate its practical utility, two prototype wrists are integrated into a dual-arm robot, demonstrating enhanced flexibility and bimanual grasping capabilities. Extensive experimental results confirm the effectiveness and real-world applicability of the proposed design.
Bioinspired robotics is progressively moving beyond the imitation of biological forms toward systems that exploit biological functions, integrate living components, and interact with natural environments. This Special Issue captures this evolution through contributions spanning functional biomimetics, biohybrid robotics, environmentally powered systems, collective behaviors, and the ethical implications of integrating living organisms into engineered platforms. These works highlight an emerging transition from nature as a source of design principles toward a deeper integration of biological and environmental processes within robotic systems, outlining new directions for adaptive, sustainable, and responsible robotics.
Natural organisms are a rich source of inspiration for designing bioinspired microstructures that can be integrated into composites to achieve tunable mechanical performance. However, the inclusion of such structural motifs has been limited to a few structures only due to the processing limitations, but the current advancements in composite manufacturing processing such as magnetically assisted slip casting (MASC) in conjunction with pressureless sintering have enabled the precise creation of complex microstructures in ceramic-metal (CM) composites. Here, we produced bioinspired Al 2 O 3 -Cu composites with five distinct microstructures, inspired from molluscs, conch shells, mantis shrimp's dactyl club and a combination of crab and molluscs, and systemically investigated the responses under different loading conditions. The nacre-like brick-and-mortar microstructured and herringbone microstructured CM composites exhibited the highest flexural and compressive strengths, whereas the Bouligand microstructured composites demonstrated the greatest crack growth toughness. The zigzag arrangement in the herringbone microstructured CM composites achieved the highest energy dissipation by damping, while the Bouligand and the crosslamellar microstructured composites exhibited the lowest damping response but the highest energy absorption during impact due to their twisted microstructures. These findings provide valuable insights into the structure-property correlations in bioinspired CM composites and establish a framework for tailoring mechanical performance through controlled microstructural design.
A bionic eye system driven by shape memory alloy (SMA) springs is designed for humanoid facial expression.• An antagonistic SMA spherical joint model enables precise multi-directional eyeball rotation with ±20° range and <1° error.• An SMA-PVC bias actuation mechanism with closed-loop PID control achieves eyelid motion with step tracking error <3.7%.
Detecting and tracking swimming animals without disturbing them is a central need in fisheries protection and aquatic biological monitoring, yet optical and acoustic methods remain limited underwater. Passive hydrodynamic sensing offers an alternative: harbour seals can follow hydrodynamic wakes over long distances, and biomimetic whiskers respond measurably to the wakes of upstream bodies. Here we quantify how well four independently varied properties of a propulsive source can be discriminated simultaneously from a single force-instrumented whisker, using towing-tank measurements of ascaled biomimetic seal whisker instrumented with a six-axis force/torque transducer. First, we separate the sensor's intrinsic response from flow-induced forcing in quiescent flow over Reynolds numbers-. The quiescent-flow spectra show that the whisker's self-shedding response is weak and separated from the wake-relevant band. We then expose the sensor to wakes from a flapping NACA 0012 airfoil acrossconditions in which the source frequency, pitching amplitude, angle of attack, and downstream distance are prescribed independently at the source. The measured force response locks to the source frequency, scales with pitching amplitude, varies systematically in the drag-to-lift fluctuation ratio with angle of attack, and decays approximately exponentially with distance, giving four distinct force signatures of the prescribed source state. A one-dimensional convolutional neural network trained on the raw six-channel time series recovers all four attributes simultaneously withaverage test accuracy (mean over five random-seed runs; per-task-) and millisecond-scale CPU inference latency. Frequency and source angle of attack are recovered essentially perfectly, whereas the remaining errors are concentrated in adjacent pitching-amplitude and downstream-distance classes, indicating that the model's failures reflect physically weak separability rather than missing spectral cues. Within the experimentally investigated parameter space, these results establish the force signature of a biomimetic whisker as a compact basis for reading the state of a propulsive wake source.
Hoofed animals such as mountain goats, camels, horses, cows, and pigs exhibit exceptional capability in managing complex contact dynamics within their ecological niches, ranging from steep rocky slopes to loose sand and muddy ground. Recent numerical modelling and experimental work have demonstrated that the passive dynamics of mountain goat hooves can significantly reduce slippage without the need for active closed-loop control, provided that joint compliance lies within an appropriate range. In this paper, we review the biomechanics of biological hooves in relation to their environmental specialisations and examine the corresponding design principles, advantages, and limitations of robotic feet. By integrating evidence from biological morphology, robotic prototypes, and contact mechanics, we identify the critical morphological and material features required for robotic feet to perform effectively across diverse terrains. The paper highlights that: (a) layered and anisotropic material organisation in biological hooves enables passive, terrain-adaptive contact dynamics that provide stability and traction without active control; (b) anticipatory and morphology-driven contact modulation can replace high-bandwidth control in legged robots. This involves tunability of mechanical parameters, such as stiffness, damping, and contact geometry; (c) future robotic feet should combine bio-informed minimalism with adaptive compliance to achieve terrain-general locomotion.
One of the current research hotspots in lower limb exoskeletons (LLEs) is balance assistance. However, there is no systematic review to integrate the solutions and to highlight the challenges for balance and stabilization of LLEs that have been provided in previous studies. Therefore, this paper aims to integrate the approaches and identify the balance assistance/recovery strategy in various movement situations. We found that the balance strategies of LLEs are mainly focused on walking on level ground, with low coverage of most basic movement situations. Based on the available balance assistance methods, some possible future trends are presented, such as rethinking the role of humans in human-exoskeleton systems. This paper also provides a corresponding overview of the application of the stability criterion, which researchers can use as a reference to develop methods for further maintaining the balance and stability of LLEs.
Many migratory animals sense Earth's magnetic field and use it
for navigation, alongside stimuli in other modalities. Engineered systems could
benefit from similar approaches, especially where satellite signals are unavailable.
However, it is unknown how animals allocate attention between magnetic and non-
magnetic stimuli. One theory is that attention arises from competition between
stimuli, bottom-up biases towards salient (noticeable) stimuli, and top-down
biases towards goal-relevant stimuli. We develop an attention model based on
biased competition for a simulated agent that navigates between known waypoints
using magnetic, olfactory, and visual cues. We characterize how attentional biases
influence the agent's success rate, speed, and path efficiency during migrations
in a diverse set of abstract magnetic environments, with and without fluid
currents. We also explore how attention biases influence obstacle avoidance. Our
work suggests that biased competition is a plausible framework for multimodal
navigation in magnetoreceptive animals or engineered systems. Bottom-up biases
are crucial to obstacle detection, and support navigation near waypoints. While
top-down biases lead to more active navigation and improve speed, they also
hinder obstacle detection. Because we did not optimize parameters, combining
top-down and bottom-up biases did not lead to both efficient navigation and
obstacle avoidance.
Biomimetic underwater acoustic communication (BUAC) is a key technology for underwater data transmission, yet existing BUAC techniques are hindered by low data rates and inadequate degree of mimic (DoM). Inspired by the wideband click trains of dolphins, this paper proposes a high-speed BUAC scheme that employs dolphin clicks as information carriers. Information is embedded by jointly modulating the amplitude and phase of these clicks. The effects of Doppler shift and inter-symbol interference are effectively mitigated through the cascaded application of interleaving, Gray coding, resampling, and channel equalization. Furthermore, handshake-free adaptive modulation is implemented via the frame header, ultimately achieving high-speed and reliable BUAC. Shallow-water sea trial results demonstrate that the proposed method achieves a communication performance of 22.54 kbps*km with a bit error rate of only 0.0019, which is twice the upper bound of existing techniques. Moreover, the technique can flexibly switch its signal carrier according to local biological signals, further enhancing DoM and providing a feasible solution for high-speed BUAC among underwater equipment.
Bioinspired soft robots leverage the efficient deformation mechanisms of living organisms to navigate complex environments. Magnetic actuation is a particularly promising modality for these designs due to its wireless control, rapid response, and biocompatibility. However, achieving sophisticated and controllable deformation remains a significant challenge. Inspired by the versatile deformation and stiffness-tuning capabilities of octopus tentacles, this study proposes a programmable magnetic soft robot (PMSR). The PMSR incorporates a truncated cone profile and an axisymmetric V-shaped notch structure to regulate its axial stiffness distribution, with internal magnetization profiles defined via programmable magnetization technology. A magnetic-mechanical coupling finite element model was established, incorporating mesh independence verification and literature benchmarking to systematically investigate deformation behaviour of the PMSR under non-uniform magnetic fields derived by permanent magnet (PM). Simulation results demonstrate that adjusting the working distance and rotation angle of PM enables controllable bending. Extensive parametric studies elucidate the influence of notch geometry, magnetization patterns, material stiffness, and remanent magnetization on actuation performance. Furthermore, contact mechanics simulations in simplified vascular interventional scenarios show that the contact pressure between the PMSR tip and the vascular wall remains within a preliminary safe operational limit across various advancement distances and vessel curvatures. This work provides a robust analytical framework for the systematic design and performance prediction of bioinspired magnetically controlled soft robots.
This study numerically investigates the hydrodynamics of two self-propelled undulating foils in an initial anti-phase, side-by-side configuration. The effects of lateral spacing, undulatory amplitude, frequency, and kinematic mismatches by independently varying
amplitude or frequency, are systematically examined. When kinematics are identical, the foils maintain a symmetric formation, with forward speed varying non-monotonically with lateral spacing and power consumption always exceeding solitary swimming. A critical
spacing exists where speeds match while energy efficiency remains lower. Under frequency differences, four modes emerge, separating (Se), side-by-side (Ss), bouncing side-by-side (Bs), and staggered (Sg), with the kinematically disadvantaged individual gaining speed and efficiency at the advantaged individual's energetic expense. Under amplitude differences, formations become more stable. The kinematically disadvantaged individual consistently gains speed with increased power consumption, while energy efficiency gains appear only when disparity is sufficiently large. Further analysis shows that reduced-order models for inline formations fail to capture the observed non-monotonic speed variation and critical spacing. Instead, collective performance in side-by-side configurations is governed by the coupling of full-body lateral velocity fields, rather than wake-vortex or leader's trailing edge-follower's leading edge interactions. These findings highlight fundamental differences between anti-phase, side-by-side and inline schooling, demonstrating that kinematic heterogeneity reshapes the distribution of hydrodynamic advantages among individuals.
Crawling soft robots have attracted widespread attention due to their high adaptability to unstructured environments. However, existing research often focuses on understanding the formation mechanism of their motion capabilities from the perspective of actuation methods or control strategies, resulting in fragmented design logic and a lack of a unified framework. Through comparative analysis across animal, plant, and microbial systems, this paper points out that crawling behavior in different biological systems largely depends on the synergistic effect of morphological deformation and interface friction. Many studies have shown that rectifying periodic, reversible deformation processes into directional net displacement plays a crucial role. Building on this, this paper further analyzes the roles of various actuation technologies in crawling systems, emphasizing that actuation primarily undertakes deformation triggering and modulation functions, and its impact on motion performance is highly dependent on the coupling method with morphological structure and interface conditions. Regarding control and learning methods, this paper discusses the key role of morphological and interface design in reducing control dimensionality and improving system robustness from the perspective of embodied intelligence, a design paradigm in which intelligent behavior emerges from the interaction among morphology, materials, actuation, and environmental constraints rather than solely from computational control. Pointing out that control strategies are more about compensating for and optimizing the structure-generated motion capabilities. Soft crawling robots gain locomotion from coordinated periodic deformation rectification among body morphology, driving timing and interfacial contact instead of single actuator performance. This review further summarizes prospective design rules and research paradigms to build a unified framework for relevant mechanism analysis and practical engineering design. This review provides a unique perspective by systematically examining the coupling among morphology, interfacial friction, and environmental interactions in crawling soft robots, which distinguishes it from previous general reviews on soft robotics and soft actuation systems.
This study applies dynamic mode decomposition to motion-capture-based kinematics of straight flight in the great roundleaf bat (Hipposideros armiger) to identify dominant frequency components and evaluate their aerodynamic effects using prescribed-kinematics computational fluid dynamics. Three dominant mode pairs capture the primary deformation content: a zero-frequency static mode representing mean posture, a fundamental flapping mode at 9.2 Hz, and a superharmonic twisting mode at 18.6 Hz. Spatial localization shows the flapping mode represents the global stroke motion, with amplitude increasing toward the wingtip, whereas twisting is concentrated on the outboard wing, strongest near the distal trailing edge. Two temporal descriptions are compared: eigenvalue-based predictive dynamics with nearly constant-amplitude sinusoidal evolution, and data-projected dynamics exhibiting stroke-phase-dependent amplitude modulation. Aerodynamic results show that reconstructions retaining the static and flapping modes reproduce the dominant downstroke lift trend but underpredict thrust, particularly near stroke transitions. Incorporating the twisting mode substantially improves thrust recovery and increases lift recovery by preserving distal wing reorientation and associated pressure-difference signatures. Predictive dynamics provide actuator-ready commands but can introduce phase offsets relative to the measured, phase-modulated kinematics. Overall, bat straight flight kinematics support a compact frequency basis, but realistic force production requires stroke-phase-dependent modulation rather than purely harmonic evolution.
Navigating in unsteady wake flows, such as Kármán vortex streets, presents a formidable challenge for biomimetic autonomous underwater vehicles. Biological fish achieve this by utilizing their lateral line sensory systems to perceive local flow gradients and adopting an energy-efficient swimming pattern known as the Kármán gait. To translate this biological phenomenon into a practical robotics engineering solution, this paper proposes a fully computational framework focusing on the modeling and simulation of a spatio-temporal sensory system to autonomously generate the Kármán gait. To overcome the unrealistic assumption of full-state observability common in existing reinforcement learning studies, we model a multi-point lateral line array coupled with a frame-stacking mechanism. This allows the simulated agent to reconstruct the spatio-temporal topology of the surrounding unsteady flow relying exclusively on local pressure and velocity gradients. The sensory model is integrated with a spatio-temporal perceptual twin delayed deep deterministic policy gradient (STP-TD3) algorithm, which drives a Hopf-oscillator-based central pattern generator. Through rigorous high-fidelity computational fluid dynamics simulations, we quantitatively evaluate the autonomous emergence of the Kármán gait by assessing the agent's kinematic energy proxy-mapped from joint actuation effort. Results reveal that the agent expends significantly less mechanical effort navigating through the turbulent vortex street compared to swimming in steady water, suggesting the active exploitation of the local wake dynamics. The results theoretically underscore the necessity of distributed STP for biomimetic robots, providing a robust algorithmic blueprint for future physical deployments in complex aquatic environments.
While unmanned aerial vehicles (UAVs) are increasingly expected to perform active physical interactions, dynamic aerial docking remains fundamentally challenging. Conventional active grippers struggle to achieve rapid response and reliable locking simultaneously due to sensing delays, actuation latency, and impact vulnerability. To address this challenge, this paper presents an aerial docking system that integrates mechanical design and flight control, built around a Bistable Tension-Hinge Gripper (BTHG). By incorporating morphological intelligence, the BTHG utilizes the collision impact to cross an elastic energy barrier. This triggers a rapid snap-through instability that forces the mechanism into a securely locked state. This purely passive locking process eliminates the need for continuous power or active feedback during the transient contact phase. Furthermore, the outwardly flared geometry of the gripper enlarges the capture region. Its compliant structure also absorbs collision shocks to protect the UAV during rapid physical contact. Bench tests demonstrate that the prototype completes the locking transition in 0.16 s and provides a maximum holding force of 54.8 N. When integrated with onboard perception and a PX4/ROS2 flight control framework, the BTHG enables a fully autonomous docking pipeline at approach speeds up to 1.4 m s. This pipeline seamlessly covers visual target detection, agile approach, and passive locking. By shifting the highly dynamic contact response from active software control to physical hardware design, this work enables UAVs to perform reliable dynamic docking. Such capabilities pave the way for practical applications including aerial logistics relay and UAV recovery by a mothership.
This article presents the development of a wearable exoskeleton robotic device designed for the motor recovery of the upper limbs following stroke, in which the possibility of integrating soft actuators was explored. The device is designed for multi-joint assistance, with the ability to help patients in recovery training with sequential movements of the elbow, wrist, and fingers in flexion/extension and adduction/abduction. Based on the specific characteristics of each target area, the device integrates three different types of soft actuators, whose force and range of motion (ROM) characteristics were analyzed using numerical and experimental methods. The relatively low force/torque characteristics in the targeted areas of the limb have made it possible to develop a compact, lightweight system that offers comfort during long periods of use. The device is made entirely of soft materials and textiles, and the soft actuators have been designed based on average anthropometric characteristics. The force development and their ROM were the defining characteristics analyzed of the three different types of soft actuators (bellows-type textile actuator, McKibben-type artificial muscles, and PneuNets multi-segment actuators-MSA). The device integrates a closed-loop control, increasing performance as well as patients' adaptability. According to the results, the actuators develop sufficient force for recovery training, and preliminary analysis regarding ROM shows an error of 2.29% for finger flexion, 4% and 10.5% for adduction/abduction, for forearm flexion: 4.4%, and higher for hand flexion/extension. In accordance with these results, future directions concentrate on investigating the device on stroke patients and augmenting the portability of the mechanism.
This study presents a mechanism-driven analysis of spanwise folding kinematics in bird-inspired ornithopters, in which the folding motion is generated by a planar crank-rocker mechanism augmented with a folding loop. A closed-form position analysis of the linkage yields an analytical expression for the folding phase angleϕfas a function of the flapping-loop link lengths alone, and a two-stage genetic-algorithm optimization identifies the linkage geometry that minimizesϕffor prescribed inner-wing kinematic targets. An in-house integrated simulation framework, which couples a modified unsteady vortex-lattice method with a multi-flexible-body dynamics model, is then applied to a parametric study spanning the wing length ratio, the folding amplitude, and the mean folding angle within the resulting feasible design space. The framework is validated against wind-tunnel force measurements for flexible flapping wings and against forward-flight test data for a single-joint ornithopter. The minimum-phase configuration produces a marginally positive mean thrust at the baseline operating point, whereas the maximum-phase configuration produces negative mean thrust. Varying the wing length ratio from 1.0 to 2.2 produces an explicit lift-thrust trade-off, with the lift efficiency rising by 27% as the outer-wing fraction grows. The mean folding angle is identified as the primary lever for tuning the lift-thrust balance of the mechanism-driven folding wing, while the folding amplitude provides a secondary adjustment around each operating point. The proposed mechanism-driven framework connects linkage geometry, kinematic constraints, and aerodynamic performance within a single analytical-numerical pipeline, supporting the systematic design of bird-inspired ornithopters with spanwise folding wings.
The design of robotic graspers that can safely interact with deformable, damage-prone materials such as fruits, vegetables, and biological tissues remains an ongoing challenge in robotics. Conventional robotic graspers made of mostly rigid materials have limited compliance and tactile sensing, reducing their applicability to contact-rich manipulation of soft objects. In contrast, humans and animals can interact with their environments safely and intelligently through their bodies' structural properties and nervous systems' computational capabilities. In this article, we present the design and control of a soft grasper inspired by the sea slug,Aplysia californica, and compare its performance with rigid graspers. The soft jaws and actuators allow the grasper to mimicAplysia's force sensing capability and its ability to conform to complex food as it grasps. Combining synthetic nervous systems, an artificial neural network model inspired by computational neuroscience, and network architectures inspired byAplysia's feeding control circuitry, we designed distributed and interpretable pick-and-place controllers for the soft grasper and its rigid counterparts. During grasping, these controllers either command a fixed closure radius (feedforward position control) or cap the contact force at a predefined level (force feedback control). We first validated our approach in simulation, demonstrating that the controllers can perform pick-and-place behavior that is robust to sensor noise. We then extended the validation to the physical platform to quantitatively compare how much deformation these graspers induced on soft objects. Fruits such as strawberries, tomatoes, and avocados showed little deformation after they were handled by the soft grasper, suggesting that this approach might have significant agricultural uses. The experimental data suggest the value of the bioinspired soft grasper for soft object manipulation.
Some species of fly larvae and nematodes achieve rapid locomotion by forming loops with their bodies, latching their heads and tails, and storing elastic energy by pressurizing their soft bodies, until rapidly releasing the energy to power a jump, even without legs. Here, we model the mechanics of curved expanding bodies to understand the forces generated against a latch and the energetics that govern jumping. We then present a gall midge inspired soft-bodied jumper inspired by the incredible feats of these larvae and nematodes that emulates this jumping strategy through thermally induced volumetric expansion and mechanical latching. The robot is constructed from a silicone-alcohol composite that expands under Joule heating from an embedded nichrome wire, and is secured by a polyimide latch that enables elastic energy storage and sudden release. With a mass of 150 mg and length of 13 mm, the soft-bodied jumper reaches take-off velocities up to 1.82 m sand a jumping power density up to 1274 W kg, rivaling the performance of its biological counterparts, and demonstrating one of the highest-performing soft-bodied latch-mediated spring actuation (LaMSA) systems. Together, the model and physical system illustrate a simplified soft-bodied LaMSA mechanism, showing how the interplay of elastic energy storage and rapid release enables high-speed, impulsive motion in small-scale synthetic systems.
How skeletal architecture and landing posture shape the immediate post-impact viscoelastic response of the foot remains incompletely understood, in part because cadaveric specimens are ill-suited to repeated impact testing across postures. In this study, we developed an anthropomimetic foot joint structure aimed at replicating the skeletal geometry of the human foot. Using a vertical drop apparatus that simulates landing and a viscoelastic system-identification model, we investigated how skeletal structure and posture modulate the apparent post-impact viscoelastic response. The results show that the multi-jointed anthropomimetic structure exhibited a higher damping ratio than simplified flat and rigid feet. Moreover, ankle dorsiflexion and toe extension systematically shifted the identified parameters, reducing the damping ratio under the tested conditions. Taken together, these findings indicate that an arch-like, multi-jointed skeletal architecture can enhance impact attenuation in an anthropomimetic mechanical foot, and that morphology and passive posture alone can tune the trade-off between attenuation and rebound. The observed trends are qualitatively consistent with reported differences in human landing strategies, and highlight the engineering advantage of anatomically informed skeletal design for achieving tunable impact attenuation through postural adjustment.
