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.

Wearable robotics is undergoing a transformative shift from rigid exoskeletons to lightweight soft robotic exosuits, which have shown impressive advances in motor assistance and augmentation. Yet, these systems still lack intuitive control strategies, often imposing additional cognitive effort on the user. To overcome this limitation, the development of innovative sensing technologies is essential, as it enables the design of smarter and more robust controllers. Here, we propose a geometry-informed magnetic tracking method that estimates the kinematics of a constrained wrist-assistive mechanism from the field of a passive permanent-magnet marker measured by a compact magnetometer array. We designed and validated a low-footprint sensing solution for pronation–supination tracking in a soft robotic device. Benchtop validation comprised a 3-hour recording with vision ground truth (30 fps) and synchronized magnetic and inertial data (60 Hz), a 5-minute latency benchmark, robustness tests under seven external disturbance sources, and a 5-minute free-space test to assess geomagnetic-field effects. We also integrated our sensing method into the device controller and demonstrated operation with one healthy participant. Against the vision reference, magnetic tracking achieved R2 = 0.99 with RMSE 1.59°. The approach showed no measurable drift relative to the vision reference during multi-hour benchtop recording, and limited sensitivity to disturbances, yielding mean absolute errors ≤ 0.59°. In the qualitative controller demonstration, the estimated device angle was successfully used to trigger an assistas- needed strategy from small user-initiated motions. Overall, these results indicate that magnetic tracking can provide a robust alternative to low-footprint, kinematic sensing for wearable robots and related human–machine interfaces.

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.

Delicate object manipulation remains a major challenge in robotics, particularly in agri-food applications where fruits and vegetables require gentle yet secure handling. This paper presents a novel three-fingered hybrid soft-rigid gripper designed for safe manipulation of delicate objects, with focus on raspberry harvesting (typical size of 1.5 cm). The gripper features a hybrid soft-rigid structure combining soft fingers with rigid actuators, enabling both fast response and gentle contact. A key contribution of this work lies in the sensing architecture: each finger integrates resistive and pressure sensors, allowing force estimation along the entire finger span with an RMSE of 0.12 N with respect to a nominal gripping force of 1 N, despite the sensors being positioned away from the contact surface. The force estimation was experimentally validated using sensorized berries, and the proposed gripper was demonstrated in a scenario related to raspberry harvesting.

Equipping robotic systems with the capacity to generate ex novo hardware during operation extends physical adaptability. Unlike modular systems that rely on discrete component integration pre- or post-deployment, we envision physical adaptation through continuous in-body development via hardware synthesis. Drawing inspiration from circulatory systems that redistribute mass and function in biological organisms, we utilize fluidics to restructure the material interface, a capability currently unmatched in robotics. Here, we realize this proof-of-concept hardware generation through a vascularized robotic composite designed for programmable material synthesis, demonstrated via receptogenesis - the on-demand construction of sensors. By coordinating the fluidic transport of precursors with external localized UV irradiation, we drove an in situ photopolymerization that chemically reconstructed the vasculature from the inside out. This reaction converted precursors with photolatent initiator into a solid dispersion of UV-sensitive polypyrrole in PETG, establishing a sensing modality validated by a characteristic decrease in electrical impedance. The newly synthesized sensor closed a local control loop in real time to regulate wing flapping in a moth-inspired robotic demonstrator. Our work is a proof-of-concept materials basis for ex novo hardware generation in a vascularized composite - a step towards situated robots adapting to environmental cues.

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.

Tracking permanent magnets represents a low-footprint and passive approach to monitoring objects or human motion by attaching or embedding magnets therein. Recent tracking techniques achieved high-bandwidth detection considering a simplified model for the magnetic sources, i.e., the dipole model. Nonetheless, such a model can lead to inaccurate results any time a non-spherical magnet approaches the sensor array. Here, we present a novel tracking algorithm based on an analytical model for permanent magnet cylinders with uniform arbitrary magnetization. By means of a physical system mounting 20 magnetometers, we compared the tracking accuracy obtained with our algorithm vs. results obtained by using the dipole model and with respect to a ground-truth reference. With a single magnetic target, our algorithm can significantly lower position (up to 0.68 mm) and orientation errors (up to 2.5 degrees) while enabling online tracking (computation time below 19 ms). We also accurately tracked two magnets, by obtaining a reduction in position error (up to 0.92 mm) vs. the dipole-based algorithm. These findings broaden the applicability of accurate magnetic tracking to real-time applications, facilitating the tracking of multiple magnetic targets in proximity of the magnetic sensors. This advancement opens avenues for applications in wearable devices, advancing the field of motion detection beyond traditional inertial measurement units.

Our society, in general, and health care, in particular, faces notable challenges due to the emergence of innovative digital technologies. The use of socially assistive robots in aged care is a particular digital application that provokes ethical reflection. The answers we give to the ethical questions associated with socially assistive robots are framed by ontological and anthropological considerations of what constitutes human beings and how the meaning of being human relates to how these robots are conceived. Religious beliefs and secular worldviews, each of which may participate fully in pluralist societies, have an important responsibility in this foundational debate, as anthropological theories can be inspired by religious and secular viewpoints. This article identifies seven anthropological considerations grounded in the synthesis of biblical scriptures, Roman Catholic documents, and recent research literature. We highlight the inspirational quality of these anthropological considerations when dealing with ethical issues regarding the development and use of socially assistive robots in aged care. With this contribution, we aim to foster a global and inclusive dialogue on digitalization in aged care that deeply challenges our basic understanding of what constitutes a human being and how this notion relates to machine artefacts.

Plant cells expand and elongate. Their cumulative actuation defines organ morphing. Inspired by this modular transformability, this study proposes a modular concept for growing robots that will be able to grow by adding at their tip Transformable Modules (TMs). We provide a two-module implementation to evaluate the concept viability. We designed and characterized Shape-Retention Bellows (SRBs) that constitute the TM and are used to maintain the shape once the extension force is relaxed. We demonstrate module radial expansion and axial elongation in a straight and bent configuration (up to ∼4◦). This is the first concept of growing robots to enact the robot’s modularity and Transferability for future deployment in distributed growing systems capable of acting in various scenarios.

Most in vitro studies regarding new anticancer treatments are performed on 2D cultures, despite this approach imposes several limitations in recapitulating the real tumor behavior and in predicting the effects of therapy on both cancer and healthy tissues. Herein, advanced in vitro models based on scaffolds that support the 3D growth of glioma cells, further allowing the cocultures with healthy brain cells, are presented. These scaffolds, doped with superparamagnetic iron oxide nanoparticles and obtained through 2‐photon polymerization, can be remotely manipulated thanks to an external magnet, thus obtaining biomimetic 3D organization recapitulating the brain cancer microenvironment. From a geometric point of view, the structure is functional to both cell culture on individual unit scaffolds and to tailored cocultures fostered by magnetic‐driven unit assembly, also allowing for cell migration thanks to passages/fenestrations on adjacent structures. Leveraging magnetic dragging, for which a mathematical model is introduced, multiple cocultures are achieved, highlighting the high versatility and the user‐friendly character of the proposed platform that can help overcome the current challenges in 3D cocultures handling, and open the way to the construction of increasingly biomimetic artificial systems.

In organisms, liquid as a continuum intertwines architected components (organs), including nervous, vascular, and musculoskeletal systems. In this regard, spiders exhibit remarkable embodiments where hemolymph, which infuses the animal, simultaneously enables muscle activation and exoskeleton compliance. Previous works on spider-inspired artificial systems have focused on disentangled aspects, such as pressurization and flexible structures, yet organism-like liquid-mediated physical intelligence integrating control, distribution of resources, actuation, and support is still to be demonstrated. Here a spider-leg-inspired soft exoskeleton integrating a muscular system is shown, enabled by the contained liquid through hydration for compliance conditioning and charge transport for muscle activation. A two-photon polymerized 0.8 mm-diameter exoskeleton is reported that contains an electrolyte solution and is actuated via contraction of an ionic electroactive polymer muscle operated at 0-1 V. The exoskeleton features reversible bending and compliant interaction with natural entities such as anthers, spider webs, and pollen grains. The reported technology demonstrator, which functionally intertwines muscularization, vascularization, and innervation via liquid, supports the development of liquid-enabled systems based on embodied energy and multi-material design, particularly for bioinspired soft robotics. Natural organisms feature an unrivaled intertwining between structure and function via the bodily integration of multiple phases, multifunctional materials and architected elements. Learning from this, this study unveils a spider-leg-inspired artificial embodiment where the internal electrolyte simultaneously enables compliance conditioning via hydration, and charge transport for muscle activation. The achieved results support the development of liquid-enabled bioinspired soft robotics systems. image

Advances in bioinspired and biohybrid robotics are enabling the creation of multifunctional systems able to explore complex unstructured environments. Inspired by Avena fruits, a biohybrid miniaturized autonomous machine (HybriBot) composed of a biomimetic biodegradable capsule as cargo delivery system and natural humidity-driven sister awns as biological motors is reported. Microcomputed tomography, molding via two-photon polymerization and casting of natural awns into biodegradable materials is employed to fabricate multiple HybriBots capable of exploring various soil and navigating soil irregularities, such as holes and cracks. These machines replicate the dispersal movements and biomechanical performances of natural fruits, achieving comparable capsule drag forces up to ≈0.38 N and awns torque up to ≈100 mN mm-1. They are functionalized with fertilizer and are successfully utilized to germinate selected diaspores. HybriBots function as self-dispersed systems with applications in reforestation and precision agriculture.

Soft-tethered colonoscopes were proposed for safe and effective colon navigation, yet the deployment of front-wheel actuated colonoscopes is hindered by contact interactions with the lumen along the entire soft tether. To mitigate this problem, this study introduces an over-the-tube flexible device aimed to assist colonoscope deployment. The device is composed of three pneumatically driven actuators devised to repeatedly perform a two-phase operation: (phase I) to advance along the tether up to a working position relatively close to the colonoscope's tip; (phase II) to clamp and drag the tether forward, upon anchoring to the colonic wall. This way, a distal tether portion is freed, thus reducing the aforementioned limitations and fostering effective front-wheel navigation. Considering anatomical/clinical constraints and a 2N resistive force, we designed and prototyped a system with an inner and outer diameter of 12 and 26 mm, respectively, a length of 91 mm, and operating pressures equal to 150, 50, and 15 kPa for clamping the tether, elongating the device and safely anchoring to the colonic wall, respectively. The device was successfully tested, achieving locomotion speeds up to 4.9 and 2.2 mm/s, and tether-freeing rates up to 2.9 and 1.8 mm/s, in tabletop conditions and in a colon phantom, respectively.

Magnetic systems based on permanent magnets are receiving growing attention, in particular for micro/millirobotics and biomedical applications. Their design landscape is expanded by the possibility to program magnetization, yet enabling analytical results, crucial for containing computational costs, are lacking. The dipole approximation is systematically used (and often strained), because exact and computationally robust solutions are to be unveiled even for common geometries such as cylindrical magnets, which are ubiquitously used in fundamental research and applications. In this study, exact solutions are disclosed for magnetic field and gradient of a cylindrical magnet with generic uniform magnetization, which can be robustly computed everywhere within and outside the magnet, and directly extend to magnets systems of arbitrary complexity. Based on them, exact and computationally robust solutions are unveiled for force and torque between coaxial magnets. The obtained analytical solutions overstep the dipole approximation, thus filling a long‐standing gap, and offer strong computational gains versus numerical simulations (up to 10 6 , for the considered test‐cases). Moreover, they bridge to a variety of applications, as illustrated through a compact magnets array that could be used to advance state‐of‐the‐art biomedical tools, by creating, based on programmable magnetization patterns, circumferential and helical force traps for magnetoresponsive diagnostic/therapeutic agents.

Combined photothermal‐hygroscopic effects enable novel materials actuation strategies based on renewable and sustainable energy sources such as sunlight. Plasmonic nanoparticles have gained considerable interest as photothermal agents, however, the employment in sunlight‐driven photothermal‐hygroscopic actuators is still bounded, mainly due to the limited absorbance once integrated into nanocomposite actuators and the restricted plasmonic peaks amplitude (compared to the solar spectrum). Herein, the design and fabrication of an AgNPs‐based plasmonic photothermal‐hygroscopic actuator integrated with printed cellulose tracks are reported (bioinspired to Geraniaceae seeds structures). The nanocomposite is actuated by sunlight power density (i.e., 1 Sun = 100 mW cm −2 ). The plasmonic AgNPs are in situ synthesized on the PDMS surface through a one‐step and efficient fluoride‐assisted synthesis (surface coverage ≈40%). The nanocomposite has a broadband absorbance in the VIS range (>1) and a Photothermal Conversion Efficiency ≈40%. The actuator is designed exploiting a mechanical model that predicted the curvature and forces, featuring a ≈6.8 ± 0.3 s response time, associated with a ≈43% change in curvature and a 0.76 ± 0.02 mN force under 1 Sun irradiation. The plasmonic nanocomposite actuator can be used for multiple tasks, as hinted through illustrative soft robotics demonstrators, thus fostering a bioinspired approach to developing embodied energy systems driven by sunlight.

Microrobots (MRs) have attracted growing interest for their potentialities in diagnosis and noninvasive intervention in hard-to-reach body areas. The safe operation of biomedical MRs requires fine control capabilities, which strongly depend on precise and robust feedback about their position over time. Ultrasound acoustic phase analysis (US-APA) may allow for a reliable feedback strategy for MR imaging and tracking in tissue. In this article, we combine task-specific magnetic actuation and related US-APA motion tracking to achieve closed-loop navigation of a magnetic MR, rolling on the boundary of a lumen in a tissue-mimicking phantom. A C-arm system attached to a robotic platform is used to precisely position the magnetic actuation source and US-APA detection unit within the workspace, thus enabling MR visual-servoing. In the first place, the proposed approach allows to perform supervised localization of the MR without any a-priori knowledge of its position. After localization, a robust real-time tracking enables closed-loop MR teleoperation in the phantom lumina over a travel distance of 80 mm (145 body lengths), both in static and counter flow, thus achieving an average position tracking error of 368 micron (0.67 body lengths). For the first time, our results validate US-APA as a reliable feedback strategy for visual-servoing control of MRs in simulated in-body environment.

In the past decades, bone tissue engineering developed and exploited many typologies of bioreactors, which, besides providing proper culture conditions, aimed at integrating those bio-physical stimulations that cells experience in vivo, to promote osteogenic differentiation. Nevertheless, the highly challenging combination and deployment of many stimulation systems into a single bioreactor led to the generation of several unimodal bioreactors, investigating one or at mostly two of the required biophysical stimuli. These systems miss the physiological mimicry of bone cells environment, and often produced contrasting results, thus making the knowledge of bone mechanotransduction fragmented and often inconsistent. To overcome this issue, in this study we developed a perfusion and electroactive-vibrational reconfigurable stimulation bioreactor to investigate the differentiation of SaOS-2 bone-derived cells, hosting a piezoelectric nanocomposite membrane as cell culture substrate. This multimodal perfusion bioreactor is designed based on a numerical (finite element) model aimed at assessing the possibility to induce membrane nano-scaled vibrations (with ~12 nm amplitude at a frequency of 939 kHz) during perfusion (featuring 1.46 dyn cm-2 wall shear stress), large enough for inducing a physiologically-relevant electric output (in the order of 10 mV on average) on the membrane surface. This study explored the effects of different stimuli individually, enabling to switch on one stimulation at a time, and then to combine them to induce a faster bone matrix deposition rate. Biological results demonstrate that the multimodal configuration is the most effective in inducing SaOS-2 cell differentiation, leading to 20-fold higher collagen deposition compared to static cultures, and to 1.6- and 1.2-fold higher deposition than the perfused- or vibrated-only cultures. These promising results can provide tissue engineering scientists with a comprehensive and biomimetic stimulation platform for a better understanding of mechanotransduction phenomena beyond cells differentiation.

Polydopamine (PDA) is a polymer that derives from the self-polymerization of the biomolecule dopamine. It can be easily synthesized to obtain spherical nanoparticles (PDNPs), tunable in terms of size, loaded cargo, and surface functionalization. PDNPs have been increasingly attracting the attention of the research community due to their elevated versatility in the biomedicine field, for their excellent ability to encapsulate drugs, to convert near-infrared (NIR) radiation into heat, and to act as an antioxidant agent. Size is an important aspect to be considered, especially concerning the specific intended field of application. This work aims at investigating how changes in the size of PDNPs affect the nanoparticle properties relevant for biomedical applications, especially focusing on cancer nanomedicine. A library of differently sized PDNPs (from 145 to 957 nm) has been obtained by varying the ammonia/dopamine molar ratio during the synthesis procedure, and detailed characterization in terms of biocompatibility, cell internalization, antioxidant capacity, and photothermal conversion has been carried out. Experiments showed that nanoparticles with a larger diameter display higher NIR absorbance, superior resistance to degradation, and higher photothermal conversion capacity (the latter confirmed by a mathematical model). On the other hand, a reduction in diameter size induces both improved antioxidant properties and enhanced cellular uptake. Herein, we provide a useful tool, allowing one to choose the proper size of PDNPs tailored for specific biomedical applications.

Collaborative robots are expected to physically interact with humans in daily living and workplace, including industrial and healthcare settings. A related key enabling technology is tactile sensing, which currently requires addressing the outstanding scientific challenge to simultaneously detect contact location and intensity by means of soft conformable artificial skins adapting over large areas to the complex curved geometries of robot embodiments. In this work, the development of a large-area sensitive soft skin with a curved geometry is presented, allowing for robot total-body coverage through modular patches. The biomimetic skin consists of a soft polymeric matrix, resembling a human forearm, embedded with photonic Fiber Bragg Grating (FBG) transducers, which partially mimics Ruffini mechanoreceptor functionality with diffuse, overlapping receptive fields. A Convolutional Neural Network deep learning algorithm and a multigrid Neuron Integration Process were implemented to decode the FBG sensor outputs for inferring contact force magnitude and localization through the skin surface. Results achieved 35 mN (IQR = 56 mN) and 3.2 mm (IQR = 2.3 mm) median errors, for force and localization predictions, respectively. Demonstrations with an anthropomorphic arm pave the way towards AI-based integrated skins enabling safe human-robot cooperation via machine intelligence.