Search Results (377)

Yaw regulation of biomimetic underwater robots is complicated by flexible body motion, nonlinear hydrodynamics, and coupled actuation. This study examines whether a policy trained in simulation can be deployed on an existing robotic sea lion (RSL) without changing its hardware or low-level controllers. A deep deterministic policy gradient (DDPG) controller was formulated from measurable states and available actuator commands and trained in Webots using a model calibrated from previous tank tests. Four manually selected reward-weight settings and command update rates of 1, 2, 5, and 10 Hz were examined as deployment-oriented sensitivity comparisons, after which a 5 Hz policy was evaluated in six tank trials. Performance was reanalyzed using the circular-angle mean absolute error (MAE) and root mean square error (RMSE). In the two straight-swimming trials, the per-trial MAE was 1.01–1.12°, and the RMSE was 1.10–1.46°. In the four turning trials, evaluated from the first target crossing to the end of each record, the MAE was 1.71–3.63°, the RMSE was 2.10–4.20°, and the maximum overshoot was 2.99–7.70°. Despite the transient differences between simulations and experiments, the controller regulated the robot toward the target headings in all six tank trials. These results demonstrate the successful sim-to-real deployment of reinforcement-learning-based yaw control under low-frequency communication constraints and provide experimental evidence for its application to biomimetic underwater robots. Full article

To address contact force estimation and compliant control for biomimetic robotic arms interacting with uncertain environments, an adaptive variable-damping impedance control method based on a fuzzy-controlled forgetting-factor strong tracking Kalman filter (FSKF) is proposed. The proposed method improves the conventional strong tracking Kalman filter (SKF) by introducing a fuzzy control strategy to adaptively adjust the forgetting factor, thereby enhancing the filtering performance and improving the accuracy of contact force estimation. The estimated contact force is subsequently incorporated into an adaptive variable-damping impedance controller to achieve simultaneous contact force estimation and compliant control of the biomimetic robotic arm. During biomimetic robotic arm motion, the proposed controller utilizes the estimated contact force to adaptively regulate the damping coefficient, compensating for force-tracking errors caused by environmental uncertainties and thereby improving both force and position tracking performance. The simulation and experimental results demonstrate that the proposed adaptive variable-damping impedance controller has better force and position tracking accuracy compared with the conventional impedance controller. Compared with traditional methods, the estimation accuracy based on FSKF has improved by about 7.3%. These results demonstrate the potential of the proposed method for prosthetic systems and other applications involving compliant robot–environment interaction. Full article

Fish-like biomimetic robots increasingly combine compliant structures, soft and variable-stiffness actuation, distributed sensing, and autonomous control, but cross-study comparison remains difficult because biological inspiration, robotic embodiment, test boundaries, and mission definitions are heterogeneous. We synthesize the field through a mechanism-to-evidence framework that links biological mechanisms to measurable descriptors, robotic embodiment, controlled interventions, task-oriented evidence, and conditional design principles. Across the literature, the transferable unit is not external resemblance but a functional mechanism whose advantage remains measurable after robotic integration. Three conclusions recur: dynamic performance depends on matching stiffness, actuation frequency, damping, and fluid loading within the intended operating range; morphology, sensing, control, power, and payload must be co-designed; and component, free-swimming, controlled-task, and field studies support different scopes of inference. We translate these findings into nine evidence-informed conditional design principles with explicit applicability limits and discriminating validation tests. Major gaps remain in wet-state dynamic characterization, complete reporting of power boundaries and kinematics, uncertainty and failures, matched task-level comparisons, and long-duration field validation. The resulting framework shifts evaluation from peak metrics and taxonomic labels toward task-conditioned, evidence-bounded design decisions. Full article

Compliant muscle–tendon mechanics can improve terrain adaptation in musculoskeletal robots, but heterogeneous terrains impose competing requirements on compliance, propulsion, foot clearance, and support transfer. This paper proposes Value-Gradient Generalist Design (VGGD), a framework for selecting one fixed physiological muscle–tendon parameterization for cross-terrain locomotion while preserving skeletal topology and muscle routing. VGGD searches a compact PCA-based manifold that coordinates bounded scale factors for muscle strength, contraction-velocity capacity, and passive elastic response. A design- and terrain-conditioned value proxy is learned from sampled latent designs and then optimized by proximity-regularized projected value-gradient ascent under a soft-worst objective. Independent proxy validation uses 50 random designs solely for calibration and 100 separately sampled test designs excluded from fitting and Stage-B optimization. On the 100-design test set, the proxy shows positive agreement with mean cross-terrain return (Pearson $r=0.580$, Spearman $\rho =0.565$) and worst-terrain return ($r=0.583$, $\rho =0.551$), with all bootstrap intervals above zero and Holm-adjusted permutation $p=0.0006$. A separate paired local-direction test uses 60 previously unused evaluation seeds and equal feasible-space perturbation radii; at the nominal, midpoint, and selected designs, the proxy-gradient direction agrees with improvements in mean and seed-wise worst-terrain rollout return. After design selection, the muscle–tendon parameters are fixed, and a terrain-aware controller is trained with variational information-bottleneck regularization and auxiliary expert distillation. Checkpoint-resolved evaluation records identify 216/300 successes and an overall mean distance of 12.14 m for the complete pipeline, compared with 57/300 and 6.20 m for nominal-body PPO. The three checkpoint success rates are 84%, 78%, and 54% for Proposed and 49%, 0%, and 8% for PPO; exact two-sided policy-level permutation tests yield $p=0.10$ for success rate and $p=0.20$ for mean distance. All methods receive the same nominal 100-million-step final-controller budget per training run, while the 10 M Stage-A budget and expert-pretraining costs are reported separately. Full article

The industrial relevance of biomimetic design rests on whether a biological principle can be converted into an engineering solution that is manufacturable, verifiable, scalable, and traceable in operation. This critical integrative review considers that problem from a production-management perspective and examines the contribution of Industry 4.0 technologies to design, validation, manufacture, and industrial use. The evidence base consists of 50 purposively selected Gold Open Access full texts (n = 50) from the Web of Science Core Collection. Each study was coded for its biological model, design principle, digital technology, material and manufacturing route, manufacturability, scale, evidence level, and reported performance. CAD, modeling, simulation, machine learning, optimization, and digital manufacturing support different parts of the transformation process, whereas sensors, robotics, and IIoT supply functional and operational feedback. The direct studies report laboratory- or prototype-level improvements in strength, stiffness, material or support use, drag, thermal and energy performance, sensing, and actuator durability. None, however, demonstrates E4–E5 evidence across the complete chain. Evidence on serial production, process capability, stable quality, total cost, standardization, certification, and life-cycle performance is still limited. Drawing on these findings, the review proposes a technology–production–performance framework and a set of measurable Industry 5.0 indicators. Its main limitations are the Gold Open Access and English-language boundaries, purposive rather than exhaustive selection, unavailable exact search strings and record-level exclusion counts, single-researcher coding, and outcome heterogeneity that prevented meta-analysis. Full article

Robotic piano playing is a challenging benchmark for biomimetic dexterous manipulation, requiring precise timing, coordinated multi-finger motion, and stable key contact. This study proposes a robotic piano-playing framework based on a two-stage reinforcement learning curriculum. Musical Instrument Digital Interface (MIDI) data are converted into target-key and fingering grids to provide future musical goals for policy learning in a parallel MJLab simulation environment. A Soft Actor–Critic (SAC) agent takes a 2106-dimensional observation vector, including joint states, previous actions, musical phase, future key targets, fingering assignments, and piano-key states, and outputs a 21-dimensional continuous action vector for wrist, finger, and global hand-positioning control. Stage 1 weakens physical regularization to facilitate key-pressing acquisition, whereas Stage 2 strengthens power, velocity, acceleration, collision, posture, and finger-speed constraints to improve the regularity of policy outputs and readiness for real-world deployment. Simulation experiments on 30 s right-hand excerpts from Für Elise, Canon, and Beethoven’s Symphony No. 5 achieve frame-wise key-state F1 scores above 0.99 on the first two excerpts and approximately 0.945 on Beethoven. Real-world deployment uses open-loop playback of policy-generated high-level trajectories with low-level joint-position feedback and achieves F1 scores of 0.95, 0.91, and 0.83, respectively, while reproducing representative piano techniques such as chords, octaves, mixed black-and-white-key patterns, overlapping finger actions, and rapid sequential movements. These physical results demonstrate the feasibility of the proposed sim-to-real pipeline for complete 30 s executions; they are not intended as a statistical repeatability study. The results further show that biomimetic robotic hands can learn complex piano-playing skills from MIDI-based task objectives without relying on human motion demonstration trajectories. Full article

Biomimetic hydrogels have emerged as versatile bioelectronic interface materials for bioelectronics and human–machine interfaces (HMIs), enabling mechanically compliant and multifunctional interactions between electronic devices and biological tissues. Inspired by the structures and functions of biological systems, these hydrogels incorporate tissue-like mechanics, efficient ionic/electronic transport, robust wet adhesion, and environmental adaptability within hydrated polymer networks, enabling stable bioelectronic interfaces. This review first categorizes biomimetic hydrogels into polymer-based hydrogels, carbon–polymer composites, and metal–polymer composites, with emphasis on their structural features and functional properties. We then discuss biomimetic strategies for regulating charge transport, mechanical performance, and interfacial adhesion through structural and molecular engineering, highlighting how biomimetic principles are translated into material properties. Finally, representative applications in electrophysiological monitoring, biochemical sensing, gesture recognition, and robotic control are discussed to establish the link between biomimetic material design and device functionality. Overall, this review highlights the design principles that connect biological inspiration to material properties and bioelectronic functions, providing a framework for the development of hydrogel-based biointerfaces for advanced bioelectronics and HMIs. Full article

Background: Early-stage elderly-care robot design requires biological analogies to be translated without turning qualitative inspiration into unvalidated numerical evidence. Methods: We audited 15 initial variables and retained a four-dimensional exploratory space: nominal shell-edge radius (V06), pre-braking trigger distance (V09), translational speed (V11), and commanded deceleration (V12). Latin hypercube samples were filtered by V09 − V11²/(2V12) ≥ 0. A derived warning margin proxy, I5 = 1 − [V11²/(2V12)]/V09, was evaluated with fixed-seed feasibility, distribution, coverage, cluster, coordinate stability, and distance-sensitivity diagnostics. Results: The pooled pre-check acceptance rate was 0.8621. I5 descriptive and distributional stability passed at N = 768→1024, but four-dimensional coverage passed in only 10/30 seeds; no sufficient N was established up to 1024. Natural cluster structure was not detected, exact representative coordinates were seed-sensitive, and selection overlap under an alternative distance definition was 0.53. Two fixed-seed points were therefore retained only as illustrative boundaries. AI-assisted images and legacy Rhino studies were used for qualitative design communication, not as validated realizations of the computation. Conclusions: The evidence-tiered workflow supports traceable exclusion of infeasible combinations and transparent product design translation while preserving explicit limits: no physical safety, usability, manufacturing, or optimality claim is made. Full article

Soft robots are particularly suitable for in-pipe inspection, where locomotion must be achieved within confined, curved, and geometrically constrained environments without damaging the pipe wall. In this context, structural compliance is not only a safety feature but also a functional design principle, enabling the robot to adapt to the pipe geometry, maintain distributed contact, and generate locomotion through controlled anchoring and extension–contraction cycles. This study presents the design, fabrication, and experimental validation of an earthworm-inspired soft pneumatic robot for in-pipe inspection. The robot uses inflatable anchoring elements for alternating radial anchoring and pneumatic bellows actuators for extension–contraction cycles, enabling locomotion while maintaining stable contact with the pipe wall. A laboratory-scale prototype was fabricated using additive manufacturing and evaluated with a dedicated pneumatic and control system. Experiments were conducted to determine locomotion performance, operating pressures, actuation timing, friction characteristics, bend negotiation, and load capacity. The optimal anchoring pressure was only 0.1 bar, demonstrating that reliable contact with the pipe wall can be achieved at a very low pneumatic pressure. The robot achieved average locomotion speeds of 21.07 mm/s in horizontal and 20.59 mm/s in vertical PVC pipes, successfully traversed a 90° pipe bend, and demonstrated a maximum vertical load capacity of 1.2 kg. These results demonstrate the feasibility of the proposed biomimetic soft robotic concept for in-pipe inspection and provide a basis for future development toward autonomous operation and industrially relevant testing. Full article

Biomimetic structures are now a major topic of research, as natural systems achieve high performance through hierarchical organization, multifunctional interfaces, and scale-bridging design principles. Nanofabrication provides a powerful approach to recapitulate biological architectures from the nanoscale to the macroscale, allowing accurate control of the surface chemistry, geometry, transport, mechanics and function. Recent work demonstrates that this approach is especially critical for bionic devices and systems, including biosensors, drug delivery platforms, tissue-engineered constructs, organ-on-chip systems, soft robots, and biohybrid devices. The aim of this review is to provide a systematic overview on how nanofabrication allows the construction of biomimetic structures, with emphasis on bio-templating and replication of natural structures, applications of nanofabrication in bionic devices and systems, and cross-scale biomimetics. Full article

To address the challenges of lumped model uncertainties and tracking error constraints in biomimetic rehabilitation robot control, this paper proposes a novel high-order integral barrier function to construct an adaptive neural tracking control scheme. Radial basis function neural networks (NNs), inspired by the receptive field mechanism of motor neurons, feature local activation and can accurately approximate the nonlinear dynamics of such bionic rehabilitation devices. Distinct from traditional integral barrier Lyapunov functions, the presented high-order integral barrier function can accommodate both time-varying and time-invariant error constraints, while simplifying the controller derivation and ensuring full differentiability of virtual control laws throughout the backstepping framework. Supported by the derived barrier function theorems, the tracking error of the robot is theoretically proven to stay within predefined safe boundaries and converge exponentially to a compact neighborhood of the origin. Finally, comparative numerical simulations on a biomimetic rehabilitation robot validate the effectiveness of the proposed theorem and constrained adaptive neural control strategy. Full article

The inherent trade-off between structural compactness and functional versatility poses a fundamental challenge in biomimetic robotic hand design. This paper presents a multi-objective optimization framework for determining the optimal phalanx length allocation of a biomimetic finger under a fixed total-length constraint. Three performance criteria are formulated: grasp capability, measured by the area of a novel shared workspace (Region II) between power grasping and precision manipulation; kinematic dexterity, evaluated as the global average of the reciprocal condition number of the Jacobian matrix; and key-press range, defined as the maximum static fingertip span under perpendicularity and slope constraints. A full grid search reveals distinct optimal configurations for each objective. Pareto analysis of 117 non-dominated solutions shows that the key-press range is most sensitive to dimensional variations, with a 24.7% performance spread. A hierarchical selection strategy that prioritizes the key-press range while balancing the other two objectives yields a recommended compromise design. Experimental validation of the key-press reachability for the recommended compromise design achieves a 98.8% keystroke success rate over 1000 cross-row strikes without wrist movement. These results confirm its practical feasibility for fine manipulation tasks, while experimental characterization of the grasp capability and kinematic dexterity objectives remains as future work. Full article

Soft actuators made from soft organic materials that can exhibit biomimetic motions, such as artificial muscles, have recently attracted substantial interest for applications in soft robotics, wearable electronics, and haptic interfaces, where flexible, adaptive, and biocompatible actuation is essential. In this context, piezoelectric and electroactive materials have emerged as important platforms for electromechanical transduction; however, conventional piezoelectric materials are predominantly ceramic-based, making them brittle, limiting achievable strain, and often requiring high operating voltages. Ionic liquids (ILs) have emerged as promising alternatives due to their high ionic conductivity, negligible volatility, and wide thermal and electrochemical stability windows. Notably, recent reports of piezoelectric behavior in ionic liquids, representing the first observation of such effects in liquid systems, have opened new opportunities for IL-based soft actuators. These advances highlight the potential of IL-based materials for developing next-generation soft robotic systems with enhanced functionality. Accordingly, there is a growing interest in designing sustainable actuators that integrate self-healing, self-powering, and self-actuating capabilities while maintaining efficient energy use, long-term stability, and user-specific adaptability. This review summarizes recent progress in IL-based soft actuators, including material design, actuation mechanisms, sensing integration, and control strategies, and also discusses current challenges and future research directions in this emerging field. Full article

Liquid metals, particularly gallium-based alloys, uniquely combine fluidic compliance with metallic conductivity, which makes them ideal candidates for biomimetic design. Rather than treating biomimicry as the mere imitation of biological forms, we argue that liquid metal biomimicry should be understood as the realization of biological strategies through the intrinsic physics of fluidity and interfacial dynamics. This review organizes existing research within a hierarchical framework that couples physical liquidity, interface biology analogy, and functional emergence to explain how adaptive behaviors naturally arise from dynamic liquid metal systems. We examine representative systems across morphological and functional dimensions and contend that their true significance lies not in replicating nature but in addressing problems that conventional rigid materials cannot solve. Looking forward, we identify several transformative directions that collectively chart a roadmap toward truly intelligent and autonomous bioinspired systems. By bridging the physics of fluidity with the principles of biological adaptability, liquid metal biomimicry holds transformative potential for soft robotics, wearable electronics, neuromorphic computing, and biomedical engineering. Full article

This study presents the innovative design and development of biomimetic origami-based soft robotic grippers capable of two-stage grasping. Inspired by the biological structure of the sea urchin mouth, which combines external rigid teeth with an internal soft membrane, the proposed grippers employ origami architectures to achieve coordinated two-stage grasping. Novel waterbomb and Miura-ori origami architectures were introduced, enabling the formation of external and internal teeth. The developed grippers integrate an elastomeric membrane with an internal origami structure that enables contraction-driven folding under negative-pressure actuation. Multiple gripper configurations with varying dimensions are fabricated using paper and polymer-laminated paper skeletons. An energy-based modeling framework is introduced to describe the pressure–force relationship while accounting for the effects of structural deformation. Experimental evaluations conducted at different negative-pressure values quantified grasping performance and holding force. Imprint-based analysis confirmed the two-stage grasping mechanism, while grasping capability investigations demonstrated compliant interaction with delicate objects. Holding forces were measured using cylindrical metal and spherical wooden test objects of varying sizes and orientations. The waterbomb-based gripper achieved the most consistent performance, particularly for cylindrical objects, reaching a maximum holding force of 70 N, whereas the Miura-ori provided improved adaptability and higher holding forces for spherical objects, reaching 74.8 N, and maximum force-to-weight ratios of 327.2 and 346.6 were achieved for the waterbomb- and Miura-ori-based grippers, respectively. Full article