Soft robots, compared to rigid robots, possess inherent advantages, including higher degrees of freedom, compliance, and enhanced safety, which have contributed to their increasing application across various fields. Among these benefits, adaptability is particularly noteworthy. In this article, adaptability in soft robots is categorized into external and internal adaptability. External adaptability refers to the robot's ability to adjust, either passively or actively, to variations in environments, object properties, geometries, and task dynamics. Internal adaptability refers to the robot's ability to cope with internal variations, such as manufacturing tolerances or material aging, and to generalize control strategies across different robots. As the field of soft robotics continues to evolve, the significance of adaptability has become increasingly pronounced. In this review article, we summarize various approaches to enhancing the adaptability of soft robots, including design, sensing, and control strategies. Additionally, we assess the impact of adaptability on applications such as surgery, wearable devices, locomotion, and manipulation. We also discuss the limitations of soft robotics adaptability and prospective directions for future research. By analyzing adaptability through the lenses of implementation, application, and challenges, this article aims to provide a comprehensive understanding of this essential characteristic in soft robotics and its implications for diverse applications.

Biomimetics seeks to translate principles from living systems into innovative engineering solutions by drawing on the remarkable efficiency, adaptability, and multifunctionality found in nature [...]

Bioinspiration offers a powerful approach for designing robotic systems capable of interacting with complex environments by emulating biological strategies. This is particularly relevant in the context of ocean exploration for the conservation of marine ecosystems. A significant portion of marine biodiversity resides near the seabed, an area difficult to explore without disturbing its delicate balance. This work presents a computational fluid dynamics analysis of the lateral fin of cuttlefish, known for its ability to swim with remarkable stability and maneuverability near the seabed. Using an overset mesh approach, a prescribed rigid-body undulatory deformation is imposed on an isolated fin model, without the body mass, resulting in self-propelled forward motion. The resulting wake exhibits complex ring-like vortex structures, shaped by the three-dimensional redistribution of flow around the fin. The impact of wave parameters on swimming performance is assessed, providing an understanding of the mechanisms underlying efficient and environmentally respectful locomotion. Parametric analysis shows that frequency influences swimming speed, while amplitude and wavelength impact on efficiency. Low cost of transport for the isolated fin is achieved at low amplitude and intermediate wavelength. Longer wavelengths increase environmental disturbance, whereas shorter ones help confine the flow, making this propulsion strategy promising for seabed exploration.

Biological adaptive locomotion has long inspired robotic solutions for navigating unstructured environments. However, animal‐inspired systems—and, more recently, plant‐inspired ones—are typically considered separately. This study merges strategies from both kingdoms through a design inspired by the Mexican jumping bean. Specifically, the moth larva Cydia saltitans , which hatches inside the seed of Sebastiania pavoniana , generates temperature‐induced multimodal locomotion enabled by the seed's peculiar curved–flat geometry. Translating this principle into robotics, Bean‐Bot is a frugal, 1.3 cm thermo‐responsive jumping module enclosed within a bean‐shaped shell. Upon temperature increase, it achieves terrain‐sensitive locomotion—including jumping (up to 30 cm), flipping, rolling, sliding, climbing, and self‐reorientation—with 81.5% of jump events transitioning into one or more additional locomotion modes after landing, capabilities absent in conventional jumping robots. Unlike control‐centric or tethered multimodal systems, the electronics‐free, untethered Bean‐Bot achieves multimodality through a dual‐kingdom‐inspired embodied design that couples material properties, morphology, and the environment. Its bean‐inspired geometry passively modulates jump trajectories and enables terrain‐dependent mode switching. This bioinspired strategy demonstrates an aspect of physical intelligence by achieving multimodal behavior through the tight coupling of temperature‐responsive materials, shell morphology, and environmental interactions, with minimal computation. Through temperature variations, Bean‐Bots move stochastically and may offer new strategies for navigating unstructured environments.

The elephant trunk is a highly dexterous muscular hydrostat whose continuous, distributed deformations pose significant challenges for mathematical modeling. We introduce linear “stereotypical” laws that map desired trunk configurations, parameterized by curvature and length, directly to the internal muscle-analogue forces required in our rod-based dynamic model. The trunk is represented as a simplified multi-segment structure of point masses linked through longitudinal and radial muscle analogues and connective tissue, all modeled using rods. Using these laws, the model predicts biological reaching trajectories with tip-position errors below 8% while maintaining hydrostatic volume across trials. The resulting force-shape mappings reveal consistent, repeatable internal force patterns underlying trunk postures, providing a compact representation of actuation strategies that generate specific planar shapes. By reducing high-dimensional continuum dynamics to simple linear relationships, this framework preliminarily enables the inference of muscle-force distributions from shape configurations, laying the groundwork for deeper exploration of the elephant trunk motion strategies and their translation into advanced robotic systems control.

Animal diaphragm-lung systems are soft organs that generate a controllable vacuum. Elephants, as rare land animals, can manipulate all three states of matter using their lung-generated vacuum. In soft robotics, however, current vacuum generation relies on rigid components, and no single soft device effectively handles all states of matter. Traditional soft pumps and grippers are limited in scope: soft pumps provide continuous liquid flow but cannot directly manipulate solids, while grippers manage solids but are ineffective with liquids and gases. Inspired by lung functionality, we present a soft pressure-to-vacuum converter that provides precise control over the suction, holding, and release of solids, liquids, and gases through a single entry and exit point based on negative pressure. Through the selection of appropriate material properties and design variations, our soft device achieves vacuum levels up to -18 kPa, enabling intermittent control and sequential handling of various media without the need for additional components. We demonstrate diverse applications of our soft device, including artificial lungs, liquid blending, vacuum gripping, coffee preparation, and liquid-gas vaporization. This bioinspired device not only provides a safe and adaptable solution for vacuum generation but also addresses a critical gap in soft robotics, offering a multifunctional system capable of manipulating all states of matter.

This study investigates the aerodynamics of a bio-inspired samara seed through high-fidelity numerical simulations, employing an overset mesh method to fully resolve its six-degree-of-freedom (6-DOF) motion. Coupled fluid and rigid body dynamics was solved using OpenFOAM v2406. A rigid 3D-printed seed prototype reproducing the samara ofAcer campestreand its geometrically scaled versions (0.5x and 2x) were analyzed to explore the effects of scaling on passive flight dynamics. The simulations captured the full 6-DOF behavior, including the transition from uniformly accelerated vertical free-fall to steady autorotation. Key aerodynamic quantities such as descent velocity, angular velocity, coning and pitch angles, and the surrounding flow field structure were evaluated and compared. Simulation results are found to agree with scaling laws derived from the literature. Autorotation was found to be robust across scales, but strongly dependent on drop height and aerodynamic efficiency. The larger prototype (2x) exhibited the highest aerodynamic performance, while the small seed (0.5x) showed a reduced lift and, consequently, a comparatively higher descent velocity. Moreover, the 2x prototype, provided a greater surface area, thus offering potential functional benefits for applications to environmental sensing. Flow visualizations confirmed the formation of coherent leading-edge vortices, which contribute to lift generation and flight stability. The drop height necessary to establish steady autorotation increases with the size of the seed. These results suggest the existence of practical and biological limits for effective autorotational flight and offer design insights for passive bio-inspired flying systems that balance scalability, deployment constraints, and aerodynamic performance.

This paper presents the design, development, and testing of a soft 3D-printed endoskeleton for arbitrary cable routing in tendon-driven soft actuators. The endoskeleton is embedded in a silicone body, and it is fixed to the mold prior to the casting process. It enables tendons to be placed through predefined eyelets, ensuring accurate positioning within the soft body. To minimize its impact on the overall stiffness of the soft body, the endoskeleton was designed with a slim profile, flexible connections, and fabricated using a 3D-printable elastic material (Shore A hardness 50), selected to roughly match the mechanical properties of the surrounding silicone matrix (typically with Shore 00 hardness 20–30). Although the reference geometry in this study is a cylindrical body, the design can be extended to a wide range of soft body shapes and sizes. Key features of the proposed solution include a 3D-printable guide for tendon routing that is (1) fully soft,(2) easy to place, (3) rapidly reconfigurable for arbitrary tendon paths, (4) adaptable to variable soft body geometries, and (5) easy to fabricate with single-step casting. The current work describes the design, manufacturing, simulation, and testing of a case study in which the endoskeleton is employed to reproduce a target pose predicted by FE analysis. The matching is satisfactory and demonstrates the effectiveness of the approach.

The intrinsic compliance of soft continuum robots makes them well‐suited for gentle and adaptable grasping in dynamic and unstructured conditions. However, common actuation mechanisms—such as cables or pneumatic pumps—often involve bulky powering components that do not scale well in number, practically hindering their applicability in real‐world applications. This work presents a computational framework for the optimal tendon routing in cable‐driven soft manipulators, so as to match a set of target grasps while reducing the number of actuators. The design of an octopus‐inspired soft robotic arm for underwater manipulation is taken as a case study. The framework employs a genetic algorithm combined with the finite element method to identify the optimal tendon number and routing to reach desired bio‐inspired grasping poses. Numerical results are validated by fabricating two optimal solutions and comparing them with simulations. Results show good reproducibility across multiple simulations and experimental results are in agreement with the macroscopic configurations obtained in simulation (average error of 15%, 9.63%, and 11.33% for fetching, reaching and twisting poses, respectively, relative to the arm's length). This work provides a pipeline for designing underactuated soft arms, thereby facilitating their application in a real‐world environments.

How water droplets move and slide on leaves influences plant ecophysiological and abiotic interactions, as well as the design of advanced bio-inspired wetting materials. Despite cross-disciplinary relevance, current descriptions of the in situ dynamics of droplets on living leaves focus almost exclusively on surface structure and chemistry, treating the leaf as a static, electrically neutral substrate. Here, three decades after the mechanistic discovery of the Lotus effect, we show that a yet 'hidden' force due to instantaneous electrical phenomena affect the dynamic droplet motion on living leaves. Using high-speed motion tracking and precision charge measurements, we show that droplets sliding on the pristine epicuticular wax layer on superhydrophobic Colocasia esculenta leaves strongly charge affecting its dynamics, previously observed only on synthetic (highly electronegative fluorinated) surfaces. Droplets accumulate charges of Qp,D1 = -0.02 to -0.15 nC per 30 uL droplet on pristine leaves. However, we specifically demonstrate the crucial role of the epicuticular wax layer plasticity: by a structural modification that decreases its roughness amplitude, the same leaves gain an impressive 30-40 fold enhancement in charge transfer (reaching Qt,D1 = -2.8 to -5.2 nC) slowing the droplet by half due to an estimated electrostatic force of 11 uN dominating the resistive forces. The charge accumulation is surface-history-dependent and charge quantities per droplet are surprisingly similar or even exceeding those recently reported from artificial surfaces. Our findings prove that electrostatic charging is a fundamental component of droplet-leaf interactions, opening new research directions from charge-affected leaf ecology to sustainable materials for droplet-based energy harvesting by tuning surface treatments and, moreover,...

Soft robots powered by sustainable energy abundantly available on Earth, such as heat, humidity, sunlight, osmotic potential, pH variation, triboelectricity, and wind, represent a promising shift toward eco-friendly and autonomous robotic systems. Efficiency depends on selecting and engineering responsive materials that directly transform environmental stimuli into mechanical actuation and motion, or harvest and store environmental energy to power actuators. Thermo-responsive materials undergo shape changes with temperature variations, while hygroscopic materials leverage moisture adsorption to induce actuation. Photothermal materials convert sunlight into heat and can combine thermal or hygroscopic actuators for controlled deformation. Osmotic processes drive movement through fluidic interactions, whereas pH-sensitive hydrogels respond to chemical gradients, facilitating controlled motion. Triboelectric materials generate electricity via contact-induced charge transfer, enabling self-powered sensing and actuation, while wind-dispersed structures exploit aerodynamic forces for unique movements. This review explores the critical roles of chemical, physical, mechanical, and environmental properties of materials in designing soft robots for sustainable and autonomous operation. Importantly, the review distinguishes between the broad concept of environmental energy and operation that is energetically sustainable. It systematically evaluates reported actuators and soft robotic systems based on whether their required energy sources and operating conditions are naturally occurring and regenerable, or instead depend on restricted environmental ranges, auxiliary inputs, or laboratory-controlled conditions. By examining material behavior, integration into multifunctional composites, and mechanism design for exploiting sustainable energy, this review identifies both established and emerging pathways toward environmentally realistic, autonomous, and long-lived soft robotic systems, with potential applications in environmental monitoring, reforestation, and other robotic domains.

The applicability of current upconverting lanthanide-doped luminescent thermometers is limited by signal discriminability and thermal sensitivity. We overcome these limitations by creating fluorescent nanocomposites in biodegradable polyhydroxyalkanoates (PHAs). Nanocomposites that combine different lanthanide-based upconverting nanoparticles were designed. We created mixed emitter composites with bright red (Mn2+ doped with Er3+ and Yb3+ in NaYF4), green (Er3+ and Yb3+ in BaYF5) and blue (Tm3+ and Yb3+ in CaF2) emitting particles to obtain clearly distinguishable and intense fluorescence signals. The resulting nanocomposites had maximum relative thermal sensitivities of 34% K-1, outperforming existing thermometers. Importantly, their readout requires detection only in visible wavelength ranges, making them particularly suitable for drone-based environmental monitoring purposes. To demonstrate their applicability in this field, we integrated the nanocomposites into plant-inspired artificial fliers, creating self-deployable and biocompatible units for wireless monitoring of environmental temperature. The surface temperature of topsoil was reconstructed based on the fluorescence intensity ratio among the RGB (red-green-blue) wavelengths of the upconverting nanocomposites integrated into the fliers.

Octopuses exhibit remarkable motor dexterity through distributed sensing and control in their flexible arms. Inspired by this biological model, we present a tendon-driven soft robotic arm featuring optoelectronic mechanosensors embedded in suction cups and a hierarchical behaviour-based control architecture. Each artificial sucker integrates light-emitting diodes and phototransistors to detect contact force and direction via light reflection, achieving high sensitivity (similar to 400 mV N-1 in the 0-2-N range) and directional accuracy (error, <18 degrees). The sensors operate reliably in dry and wet environments with minimal drift and hysteresis. Their compact, modular design facilitates system integration. The hierarchical control architecture enables local reflexes at the suction cup level and global coordination for autonomous grasping. The system reliably detects contact events, estimates force and direction and infers object position relative to the arm, enabling purposeful interaction. This work advances sensor-integrated soft robotics, demonstrating the potential of biologically inspired designs for adaptive grasping in unstructured environments.

This study introduces a minimally invasive robotic probe inspired by plant root growth, designed for subsoil exploration and future ecosystem monitoring and intervention. The bio‐inspired probe advances in soil by mimicking plant root apical growth, creating and consolidating a borehole through the injection of a bio‐based, biodegradable binder at its tip. This innovative process confines penetration resistance to the tip while generating a hollow tubular structure by harnessing in situ local soil. The probe's penetration is facilitated by a linear actuator, which can be retracted upon reaching a desired depth, thereby minimizing the environmental dispersion of mechatronic components. This approach not only enhances the efficiency of subsoil exploration (whether on‐Earth or in outer space) by reducing penetration force requirements and reliance on exogenous material but also ensures environmental sustainability by employing biodegradable materials and lowering mechanical footprints. The robotic probe's design and functionality highlight the potential of bio‐inspired technologies to address complex environmental challenges, paving the way for future innovations in ecological research and conservation efforts. This study underscores the importance of integrating biological principles into engineering solutions to develop tools that are both effective and environmentally responsible.

This paper investigates the penetration performance of soil-burrowing probes with different tip designs during shallow-depth penetration in various media, including terrestrial soils (Hostun sand) and well-characterized planetary soil simulants (LHS-1 Lunar regolith simulant and MGS-1 Martian regolith simulant). The analysis evaluates performance based on the pressure required to successfully penetrate the soil, comparing a conical tip design (i.e., the traditional tip design of penetrometers) with a plant root-inspired design. For each soil type, three different levels of soil compaction were considered to verify how initial soil porosity affects penetration performance. The study involves both experimental and numerical analyses. Experimentally, penetration tests were conducted in chambers filled with Hostun sand, LHS-1, and MGS-1. Numerically, a three-dimensional Discrete Element Model was developed to simulate probe penetration in soil packings with geomechanical properties of Hostun sand, LHS-1, and MGS-1, respectively. In accordance with the experimental findings, the modeling results show significant advantages of the plant root-inspired tip design over the conical tip. Indeed, the plant root-inspired design encountered lower soil resistance pressure during penetration across all soil types and compaction levels: the arithmetic mean values of the pressure reductions associated with the use of the bioinspired tip design resulted 25.5% experimentally and 25.4% numerically compared with the non-bioinspired tip.

The suckers on the octopus arm play a pivotal role in the execution of tasks in unstructured environments by providing a means to grip objects as well as perceive the environment through (chemo‐)tactile receptors in the suckers. This work presents an octopus‐inspired suction cup with high‐resolution tactile sensing capabilities using a camera that captures the displacement of markers that are integrated in the suction cup. The orientation of the suction cup with respect to an object surface could be predicted with an average error of 1.97° for latitude and 9.41° for longitude. In a closed‐loop control experiment, the orientation of the suction cup with respect to the object surface is estimated by an initial touch and the suction cup is consequently reoriented to approach the object surface in a perpendicular manner. The passive compliance of the suction cup is sufficient to compensate for the prediction error and a seal could be created on all of the objects. In combination with the automated design and manufacturing process, this is a major step toward the deployment of sensory innervated suction cups for motion planning and control of soft continuum robot arms.

Seahorses possess a unique tail muscle architecture that enables efficient grasping and anchoring onto objects. This prehensile ability is crucial for their survival, as it allows them to resist currents, cling to mates during reproduction and remain camouflaged to avoid predators. Unlike in any other fish, the muscles of the seahorse tail form long, parallel sheets that can span up to 11 vertebral segments. This study investigates how this distinctive muscle arrangement influences the mechanics of prehension. Through in silico simulations validated by a three-dimensional-printed prototype, we reveal the complementary roles of these elongated muscles alongside shorter, intersegmental muscles. Furthermore, we show that muscles spanning more segments allow greater contractile forces and provide more efficient force-to-torque transmissions. Our findings confirm that the elongated muscle-tendon organization in the seahorse tail provides a functional advantage for grasping, offering insights into the evolutionary adaptations of this unique tail structure.

Unlike living organisms, which evolved to adapt to dynamic conditions, robots often become less agile in complex scenarios, prompting roboticists to reduce environmental complexities to ease robot operations. However, the strategies implemented by animals and plants to achieve energy-saving movements in complex environments can inspire the design of more resilient autonomous robots with lower energy consumption. In nature, movement strategies evolved to balance energy expenditure and resource acquisition to survive in unpredictable environments. This is particularly relevant for robots operating over large distances or in resource-limited conditions. In this Review, we present a performance analysis of movement strategies in both natural and artificial systems and across different environments — terrain, soil, underwater and air — and emphasize how energy-saving design principles can be used to widen the operativity of robots. We discuss the importance of the cost of transport as a metric for assessing movement economy and propose its use, not only for animals, but also to benchmark movement by growth and seed dispersal in plants. Despite the profound differences in energy harvesting strategies, as plants produce organic matter using energy from light and animals obtain energy by consuming organic matter, studying both can lead to energy-saving designs in bioinspired robots. Living organisms surpass robots in durability and adaptability. This Review explores animal and plant energy-saving strategies to inspire resilient, low-energy robots and emphasizes the cost of transport as a key metric in relation to the durability of various movement modalities.

Tendrils coil their shape to anchor the plant to supporting structures, allowing vertical growth toward light. Although climbing plants have been studied for a long time, extracting information regarding the relationship between the temporal shape change, the event that triggers it, and the contact location is still challenging. To help build this relation, we propose an image-based method by which it is possible to analyze shape changes over time in tendrils when mechano-stimulated in different portions of their body. We employ a geometric approach using a 3D Piece-Wise Clothoid-based model to reconstruct the configuration taken by a tendril after mechanical rubbing. The reconstruction shows high robustness and reliability with an accuracy of R2 > 0.99. This method demonstrates distinct advantages over deep learning-based approaches, including reduced data requirements, lower computational costs, and interpretability. Our analysis reveals higher responsiveness in the apical segment of tendrils, which might correspond to higher sensitivity and tissue flexibility in that region of the organs. Our study provides a methodology for gaining new insights into plant biomechanics and offers a foundation for designing and developing novel intelligent robotic systems inspired by climbing plants.

The transition to smart agriculture is an ongoing process involving multiple aspects, one of which is the automation of crop harvesting. In this context, we present the so called Enveloped Vacuum Apple (EVA) Twisting, a soft gripper designed for apple harvesting. One of the main challenges in crop harvesting is handling delicate structures, such as fruits, while preserving the integrity of the tree. To address these issues, we propose that the gripper should incorporate soft structures, enabling safe interaction not only with the target fruit but also with neighboring fruits and branches. Additionally, the gripper must ensure a reliable grasp, even in the presence of minor positional inaccuracies. EVA Twisting presents three soft fingers, with integrated suction cups, made of materials with different shore hardness and driven by a rigid underactuated mechanism. Furthermore, the gripper integrates elements in the wrist to perform a harvesting motion of twisting and pulling without relying on the robotic arm. Preliminary test were conducted in a controlled laboratory greenhouse with young apple trees, along with other strength test with apples bought in supermarkets. Both tests showed very encouraging results for more in-depth field analysis during the next harvesting season.