Yitong Zhou

Stable cyclic actuation of twisted-and-coiled polymer (TCP) artificial muscles requires appropriate initial pretension and effective recovery. Reliable feedback is also essential for state regulation. Existing TCP self-sensing approaches often depend on complex modeling or multistep fabrication, while flexible sensing schemes are frequently constrained by insufficient adaptability to large deformation and difficulties in system integration. Inspired by the antagonistic action of abductor–adductor muscle groups, an active–passive asymmetric antagonistic actuation–sensing module is proposed. In this module, a fabrication-optimized second-order helical TCP achieves a favorable balance between large actuation stroke and high load-bearing capability and serves as the active actuator. Meanwhile, the developed stretchable polyurethane optical waveguide sensor features a simple fabrication process and straightforward signal acquisition, and functions as the passive antagonistic element to provide initial pretension, elastic recovery, and joint-angle sensing. Building on this mechanism, two antagonistic joints are arranged bilaterally on a pectoral-fin-inspired underwater actuator, where pectoral-fin deflection is regulated through joint-angle feedback to enable multi-angle steering and multi-trajectory motion. Results demonstrate that the proposed architecture simultaneously achieves compliance, state sensing, and motion regulation, providing a viable solution for actuation–sensing-integrated robotic joints and highlighting its potential for robotic motion control.

Manta rays exhibit highly agile and complex swimming patterns through undulatory pectoral fin flapping, inspiring the development of efficient and controllable swimming robots. However, integrating high propulsion efficiency, maneuverability, and untethered operation into a single robotic platform remains a grand challenge. Here, we propose a bioinspired bistable flapping soft swimming robot that mimics manta ray motion to address this issue. The flapping wings employ pre-stretched elastomeric matrix composites to achieve bistable shapes, enabling reconfigurable mono/bistable transitions and multimodal swimming behaviors through simple frequency modulation of fluidic actuation. An analytical model is employed to conduct a sensitivity analysis, identifying key parameters that influence the bistability and shapes of the actuators. computational fluid dynamics simulations show a peak instantaneous thrust of up to 17.2 N. Experimental parametric studies are performed with dynamic tests to assess the impact of critical parameters on swimmer performance and to optimize the robot’s design. An untethered swimming robot is integrated with a microfluidic pressure modulation control system for remote operation and multi-modal maneuverability. By allowing real-time modulation of swimming modes, the robot demonstrates the ability to navigate complex trajectories and avoid obstacles in unstructured aquatic environments.

Fully coupled fluid–structure interaction (FSI) modeling of the left heart (LH) remains computationally challenging, especially when the ventricle and its two valves are modeled together. Previous computational efforts have largely resorted to heavily simplified LH configurations, and a systematic quantification of the global energy budget has remained absent. To address these gaps, we present a fully coupled three-dimensional FSI model of the LH that incorporates both mitral and aortic valve geometries with variable tissue stiffness and prescribed wall kinematics under different ejection fractions (EFLV). Four conditions were compared: baseline (EFLV=40%, E=10 MPa), isolated aortic or mitral stiffening (E=20 MPa, EFLV=40%), and reduced EFLV (24%, E=10 MPa). The cases with EFLV=40% showed higher peak aortic flow rates (527 vs 404 ml/s) and larger geometric mitral orifice areas (0.50 vs 0.42 cm2). Aortic stiffening reduced the effective orifice area (0.81–0.69 cm2) and increased the maximum transvalvular pressure gradient (15.6–17.7 kPa), while mitral stiffening increased the diastolic leaflet forces (0.23–0.40 N). All cases exhibited competent valve closure with negligible regurgitation. Vortex analysis revealed that EF = 40% sustained high-helicity vortices in the left ventricle and atrium, which can reduce blood stasis, while EF = 24% led to markedly reduced vorticity. Energy analysis demonstrated that EF = 40% required substantially higher left ventricular work (0.84 vs 0.41 W), aortic kinetic energy flux (peak 4.3 vs 1.8 W), and energy dissipation (peak 1.08 vs 0.47 W) than EFLV=24%. Together, these findings quantify how EF and valve stiffness independently and interactively shape valvular dynamics, flow organization, and energetic efficiency in the failing LH, providing a biophysical framework for understanding LH failure. Our FSI platform offers a foundation for future parametric studies and holds translational potential for surgical planning and prosthetic valve design.

Twisted and coiled actuators (TCAs) with different helical levels exhibit markedly distinct actuation behaviors; however, the coupled relationships among fabrication parameters, hierarchical structures, and thermo-mechanical performance remain insufficiently understood, hindering performance optimization. Here, a unified process-structure-performance analysis framework is established to systematically analyze how fabrication parameters regulate geometric configuration, mechanical properties, and thermal actuation across first-and second-order TCAs. A multi-factor orthogonal experimental design is employed to quantify the coupled effects of twisting density, training load, and annealing conditions on pitch formation, modulus, stroke, and load capacity at different helical levels. Through optimized fabrication parameters, the maximum stroke of the first-order TCA (spring index 1.8) reaches 62.5%, while the load capacity of the second-order TCA (spring index 1.8) increases to 8.26 N, corresponding to improvements of 12.8% and 66.5%, respectively. Microstructural characterization and thermo-mechanical analysis reveal that performance differentiation arises from the competition between entropy-driven thermal softening of amorphous chain segments and rigidity provided by hydrogen-bonded crystalline networks, with enhanced segmental mobility near the α-relaxation regime governing large-stroke actuation, whereas stabilized crystalline constraints enable high load output. Finally, a soft robotic finger prototype is developed to validate application-level relevance, demonstrating task-dependent performance selection consistent with the proposed framework. This study establishes a generalizable process-guided design and fabrication strategy for hierarchical twisted artificial muscles, enabling application-oriented performance tailoring in soft robotic systems.

This study proposes a novel pneumatically driven mechanically prestressed rhombic bistable composite laminate with asymmetric cylindrical curvature, which exhibits two weakly-coupled cylindrical shapes where each shape is influenced by planform and geometry parameters. A reduced-order analytical model is developed to predict the laminate’s quasi-static equilibrium shapes and snap-through transitions of the laminate under pneumatic work loading, which is triggered by the internal pressure applied to the fluidic channels. A sensitivity study based on the model investigates the influence of key planform and geometric parameters (the internal angle α and aspect ratio E) on the laminate’s out-of-plane deflection and snap-through pressure. The results show that increasing α reduces the critical prestrain required to achieve bistability and amplifies the out-of-plane deflection, while excessive α may lead to monostable curvature. Variations in aspect ratio modify the coupling stiffness between orthogonal PEMC layers, thereby influencing the bistable domain and critical snap-through pressure. These findings provide methods for the design of bistable composite structures.

Twisted and coiled polymer (TCP) artificial muscles offer high energy density and large deformation, but achieving reliable closed-loop control remains difficult due to time-temperature-dependent parameter drift, structural variability, and labor-intensive control parameter tuning, which accelerate actuator wear through repeated adjustments. This work proposes an automated two-stage IGAPSO (improved genetic particle swarm optimization)-based framework that integrates neural-network-assisted offline optimization with rapid online fine-tuning on physical actuators, minimizing manual calibration while ensuring robust performance. Experiments demonstrate rapid and precise tuning of TCP control parameters: in step force control, convergence occurs within eight iterations with a 0.14 s settling time and 0.02% steady-state error; in step displacement control, tuning completes in three iterations with a 0.55 s settling time and 0.14% error. Zero-overshoot responses are realized by adjusting the optimization objective. The method further achieves robust waveform tracking (mean RMSEs of 1.90 mN force and 0.47 mm displacement), enables secondary retuning after long-term placement within seven iterations, and transfers effectively to TCPs with different spring indices. This work provides an efficient and generalizable strategy for accurate, robust, and adaptive TCP control, paving the way for broader integration in robotic systems.

Pectoral-fin-based (labriform) swimming combines high-speed propulsion with agile maneuverability through rigid–flexible fin partitioning. Inspired by this principle, we present a multi-stable soft robotic swimmer composed of two wedge-shaped bistable actuators integrated with fin-like rigid–flexible morphologies. The bistable actuators generate large, rapid deformations for thrust production, while the compliant fin membranes enable drag-reducing feathering during recovery. An analytical model is developed to predict the shape of bistable actuators and is validated experimentally with a minimum prediction accuracy of 97.74%. Computational fluid dynamics (CFD) analysis reveals that bistable switching induces vortex dipole ejection, contributing to thrust generation. The proposed robot attains a maximum speed of 17.53 $\text{cm}\cdot \text{s}^{-1}$ (1.10 $\text{BL}\cdot \text{s}^{-1}$), a turning radius of 0.58 per body length, and a turning speed of 31.51$^\circ$/s, highlighting our design in shaping both swimming speed and maneuverability. By integrating bistable actuation with bio-inspired fin morphologies, this work offers a principled design strategy for achieving fast and maneuverable swimming in robotic systems.