Search Results (193)

Logarithmic-spiral soft grippers couple tendon actuation, variable-curvature morphology, distributed contact, and frictional load support. This study evaluates a finite-candidate predictive force-shape (PFS) controller within a control-oriented reduced-order surrogate of a two-tendon gripper. PFS is compared with open-loop, fixed-tension, position-only, and hybrid force-shape controllers across multiple object geometries, simultaneous uncertainty, payload-friction conditions, transient loads, ablations, and parameter variations. In the nominal study, PFS produced a mean force RMSE of 7.26 N and a mean peak local force of 8.07 N, while the comparison implementations produced force RMSE values from $57.9$ N to $99.3$ N and peak forces near $30.6$ N. This behavior involved a geometric tradeoff: PFS position RMSE was $0.088$ m, compared with $0.073$ m for PO and $0.074$ m for HFS. The remaining numerical studies characterize how this tradeoff changes inside the surrogate. A matched higher-resolution verification at $(N,N_c)=(60,48)$ preserved the principal force–position tradeoff: PFS yielded a mean force RMSE of $10.25$ N and peak local force of $8.84$ N, while PO and HFS retained lower position RMSE. Because the morphology and contact relations are phenomenological, the results are interpreted as reproducible numerical evidence rather than experimental validation or proof of physical superiority. Full article

Soft pneumatic actuators are widely used in robotic manipulation due to their compliance and adaptability; however, their performance is typically fixed at the fabrication stage, limiting their suitability for applications requiring task-specific tuning. This paper presents a reconfigurable self-bending contraction actuator (SBCA) that enables post-fabrication adjustment of mechanical behaviour through interchangeable internal reinforcing elements. The proposed design introduces novel end fittings that allow rapid, non-destructive insertion and replacement of reinforcing rods, transforming the actuator from a fixed-function component into a tunable system. Four reinforcing rod geometries are designed and experimentally evaluated to investigate the influence of stiffness distribution on actuator performance. Results show that reinforcement geometry significantly affects both bending curvature and force transmission, with the proposed configurations achieving up to 77° bending at 2 bar and a maximum fingertip force of 4.73 N. A 25.42% increase in bending angle and a 10% increase in force are observed relative to a baseline configuration. Beyond performance improvements, the study establishes a direct relationship between internal structural variation and actuator output, highlighting a controllable trade-off between bending curvature and force generation. This provides a practical framework for tuning actuator behaviour without redesign or reconstruction. A three-finger soft gripper integrating the proposed SBCA is developed and validated through grasping experiments on objects with varying geometries and mechanical properties, demonstrating robust and adaptive manipulation. The proposed approach advances SBCA design from fixed-performance actuators toward reconfigurable and application-adaptable soft robotic systems. Full article

This work presents a low-cost experimental methodology to estimate the circumferential variation in resultant contact force and equivalent mean pressure generated by a cable-driven SpiRob soft gripper during grasping. A cylindrical object instrumented with internal force sensing resistors (FSRs‘) was used as an angular scanning probe. Under a fixed actuation condition, the object was manually rotated inside the closed gripper in $5°$ increments, allowing the transmitted contact force to be mapped as a function of angular position. The measured forces were converted into equivalent mean pressure values using a reference contact area. Four repeated mapping tests were performed to evaluate repeatability. The results showed a non-uniform circumferential contact-force signature, together with moderate between-test variability. The proposed method does not spatially resolve interface loading; instead, it provides a practical experimental approach for identifying regions of higher contact intensity and supporting future studies on actuation, deformation, and pressure-related behaviour in SpiRob-type soft grippers. Full article

Flexible electromagnetic actuators have attracted considerable attention for applications in soft robotics, adaptive manipulation, and human–machine interaction due to their fast response, large deformation capability, and inherent compliance. However, the concurrent application of high actuation performance and long-term cyclic durability remains a major challenge, particularly for liquid metal (LM)-based soft systems, where interfacial instability between LM conductors and polymer substrates often leads to performance degradation. In this work, we report a fabrication strategy in which patterned eutectic gallium–indium (EGaIn) liquid metal circuits are directly written onto electrospun graphene oxide/thermoplastic polyurethane (GO/TPU) nanofiber membranes. The incorporation of graphene oxide significantly enhances interfacial adhesion through hydrogen bonding interactions between oxygen-containing functional groups in GO and the native Ga₂O₃ layer on the LM surface, while the electrospun fibrous architecture further improves mechanical interlocking and structural stability. As a result, the fabricated actuator exhibits robust electromechanical performance, achieving a maximum bending deformation of 90° under a driving current of 0.8 A and maintaining stable operation over 2000 actuation cycles with negligible performance degradation. To further demonstrate its practical functionality, a soft robotic gripper was constructed based on the optimized actuator configuration. The gripper enables the stable grasping and lifting of objects with a weight up to seven times its own mass, while maintaining safe and compliant interaction with fragile objects. This work provides a simple yet effective strategy to simultaneously enhance actuation efficiency, interfacial stability, and mechanical reliability in LM-based GO/TPU flexible electromagnetic actuator systems, offering promising potential for next-generation soft robotic applications. 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

Selective harvesting of perilla (Perilla frutescens) leaves requires the repeated removal of mature outer leaves while preserving the central growing region, including the apical meristem and immature inner leaves, on the same plant. Conventional harvesting end-effectors developed for fruits or whole-head leafy vegetables are not directly applicable to this task because of the dense leaf arrangement, thin and flexible leaf blades, and the need to protect the central growing region. This study proposes and evaluates a dual-module end-effector that integrates a central growing region protection and stem-support (CPS) module with a petiole grasping (PG) module using pneumatic soft pads and a scissor-lift mechanism for petiole tensile separation. FSR-based pneumatic-pressure calibration and photoelectric-sensor-based position-adaptive stopping control were implemented to reduce grasping damage and accommodate plant-to-plant variation in petiole height. The developed end-effector was evaluated using mock perilla plants under aligned, rotated, and overlapped leaf conditions and cultivated perilla plants over two harvesting sessions separated by two weeks. In the mock-plant experiment, the system achieved an attempt success rate of 96.7% and a leaf harvest rate of 98.3%. In the real perilla experiment, it achieved an attempt success rate of 88.5% and a leaf harvest rate of 90.4%. The target-leaf damage rate was 2.1%, and no damage was observed on the main stem. In the second harvesting session, the system maintained an attempt success rate of 91.7% for newly developed leaves on the same plants. These results indicate that the developed end-effector can selectively harvest mature perilla leaves with low damage while preserving plant structures required for continued growth. Full article

Driven by orchard labor shortages and rising demand for intelligent harvesting, automated apple picking requires a balance between conformal enveloping and slip-resistant stability. To reduce damage and slippage caused by fragile skins, variable morphologies, and motion disturbances, this study proposes a multi-joint pneumatic flexible apple-picking hand with adjustable circumferential configuration. Based on structural configuration determining grasping stability, six apple-morphology-based finger-base supports were designed. Parametric analysis of soft gripper cavities identified an isosceles trapezoidal profile as the best configuration. Using the Yeoh constitutive model, an equivalent joint model for conformal gripping was developed, and genetic algorithm (GA) optimization selected the four-joint design as the preferred configuration. Static finite element simulations determined an operating pressure of 20.32 kPa. Grasping stability was quantified by relative slip displacement in rigid–flexible coupled dynamic simulations. Among the tested support configurations within 60–110°, the 90° bracket produced the most stable slip response under vertical and horizontal disturbances. Thin-film pressure tests showed an asymmetric but stable three-finger load-sharing pattern. Field trials in a high-density dwarf spindle orchard achieved an 83.98% harvesting success rate. After 72 h of cold storage, no obvious surface browning, epidermal abrasion, or compression marks were observed during visual inspection. This assessment was limited to visible external damage and did not include quantitative evaluation of internal bruising, firmness degradation, flesh browning, or long-term storage quality. These results demonstrate stable grasping performance and low visible external damage under the tested conditions. Full article

Inspired by the human hand, this work presents a hybrid rigid–soft gripper that achieves passive adaptability through a self-resetting granular jamming pouch integrated onto a 3-DOF cable-driven rigid skeleton. Seven fingertip configurations (rigid tip, different jamming particles, and TPU-only) were evaluated across five object geometries. The jamming pouch configurations showed a clear advantage over rigid fingertips and a modest improvement over TPU-only fingertips when grasping flat or smoothly curved surfaces, while demonstrating substantially superior performance for objects with sharp protrusions, lips, undercuts, or deformable edges, where enhanced conformability and geometric interlocking markedly improved payload capacity and lateral offset tolerance. The passive self-reset mechanism remained reliable over 1000 cycles. These results demonstrate that the hybrid design effectively combines the advantages of rigid and soft grippers, achieving superior overall grasping performance while balancing adaptability and payload without pneumatic actuation, with strong potential for applications in logistics, food handling, and mobile robotics. Full article

Conventional industrial manipulators are often costly and come with steep learning curves, which limits their scalability in hands-on robotics education. This paper presents a compact and modular vision-guided sorting platform based on a 4-DOF SCARA robot, designed for rapid assembly, reconfiguration, and beginner-friendly deployment in laboratory courses. A collaborative visual perception strategy is proposed, which introduces a lightweight YOLOv8 algorithm for robust material category recognition, while HSV-based color segmentation and Hough circle localization are utilized to extract sub-pixel centroid features. The pixel measurements are mapped to the robot base frame through an integrated nine-point hand–eye calibration model, and joint commands are generated via a joint-space quintic polynomial interpolation algorithm to ensure continuity and avoid kinematic singularities. The overall system adopts a hierarchical architecture in which the vision host communicates target commands to a motion controller via TCP/IP, while joint actuators are driven through a CAN bus. Feasibility is first verified in a Webots digital prototype with synchronized conveyor and manipulator control, and is then validated on a physical platform equipped with a compliant TPU-based soft gripper to improve grasp tolerance under localization noise. Experiments demonstrate that the system achieves an average recognition accuracy of 98.1% and a mean positioning error of 0.189 mm. The proposed platform provides an extensible testbed for teaching kinematics, perception-to-control integration, and modular robotic system development. Full article

Soft pneumatic grippers are well-suited for grasping irregular objects owing to their inherent compliance and ability to adapt to a wide range of shapes and sizes. However, their ability to quantitatively estimate object size during the grasping process remains limited. To address this limitation, this study proposes a soft pneumatic gripper integrated with a piezoresistive CNT/PDMS composite sensor and investigates the feasibility of object size estimation using only sensor signals. The pressure-sensing characteristics of the CNT/PDMS sensor were evaluated over a pressure range of 0–500 kPa, and the 1 wt% CNT/PDMS sensor exhibited the highest sensitivity of approximately 0.016 kPa⁻¹ in the initial linear pressure region. To this end, the normalized resistance response under applied pneumatic pressure was analyzed independent of external visual information, and a size estimation method was established based on the relationship between initial contact pressure and object diameter. Grasping experiments using spherical objects of varying diameters revealed that the resistance response patterns were clearly distinguishable according to object size, with larger objects exhibiting significant resistance changes at lower applied pressures. These findings demonstrate the feasibility of estimating the size of a grasped object based on the grasp onset pressure derived from the sensor response. The results of this study provide a foundation for future soft robotic systems capable of recognizing contact conditions and object size through sensor-based feedback. Furthermore, these findings may be extended to adaptive manipulation technologies involving real-time pneumatic pressure control. Full article

Soft robotics is a rapidly evolving field that has attracted significant attention within the scientific community. This review analyzes the main advantages of pneumatic technology in service robots across the different application domains defined by the International Federation of Robotics (IFR). By organizing the literature according to application domains, this work aims to clarify the specific benefits of pneumatic and soft pneumatic solutions in each context. The proposed approach distinguishes between traditional pneumatic solutions and the subsequent emergence of soft robotics, in order to highlight how and to what extent soft technologies have reshaped the design and application scenarios. Particular attention is devoted to the role of materials and recent manufacturing techniques used by researchers to fabricate soft pneumatic robots. Based on 163 selected papers, the analysis reveals that medical and agricultural applications dominate soft pneumatic research, accounting for 41% and 27% of the soft sample, respectively. Compared to traditional pneumatics, the medical sector has expanded into cardiac assistive devices, wearable monitoring sensors, and minimally invasive surgery; agriculture has grown from 17% to 27% of the soft literature due to precision harvesting grippers. Soft inspection robots have increased thanks to continuum manipulators and bio-inspired locomotion, while search and rescue remains a niche (9%) but promising sector. Unlike previous reviews that focus on single domains or technologies, this work quantifies the uneven transition from rigid to soft pneumatics across IFR sectors and highlights emerging application-specific design paradigms that were not feasible with traditional systems. Full article

This review summarizes the research on the end effectors of agricultural harvesting robots (2010–2025) and extracts two core design principles. First of all, the selection of end effectors must follow the biological characteristics of fruits: rigid grippers are suitable for hard skinned and regular fruits; soft grippers can reduce the damage of fragile crops to a certain extent; suction cups are suitable for smooth, barrier free surfaces; the envelope type is suitable for soft and lossless picking scenes; the combined suction and grip design is more suitable for unstructured environments. Secondly, the separation mode should match the characteristics of the stem: motion separation (torsion/pull) is suitable for weak stems, while cutting is mainly used for hard stems. Unlike previous literature, this review provides a field deployability checklist (including dust/water proofing, cleanliness, maintenance, aging prevention, and aspiration prevention) to narrow the results of the laboratory and the real field environment. The three future directions of multimodal perception, variable stiffness driving and reinforcement learning are logically related to the analysis in this paper: multimodal perception optimizes the perception limit, variable stiffness solves the rigid–flexible trade-off, and reinforcement learning provides adaptive strategies for different crops. This framework can match the end effector design with the crop-specific field conditions. Full article

Accurately estimating the internal structure of deformable objects from sparse measurements remains a significant challenge in robotics. This work proposes a three-stage identification framework for this problem. First, a classification strategy determines a minimal informative set of indentation locations using a generalized error computed from pre-simulated FEM force reactions of baseline cavity models and flat-punch indentation estimation. Using this set, the estimation stage detects the cavity type and provides a preliminary estimate of its geometric parameters based solely on measured indentation responses. The correction stage then refines these parameters by replaying measured indentation depths in FEM simulations and deriving geometry corrections from the discrepancy between simulated and homogeneous force responses. Robust loss functions at both stages limit the influence of measurements where local contact conditions deviate from the assumed model, improving reliability across all tested cases. Indentation depth was obtained through gripper proprioception, with an RGB-D camera limited to global pose alignment. Experiments on soft cubes with spherical, cuboid, and pyramidal cavities demonstrate that, within known cavity families and fixed material parameters, the minimal indentation set reliably distinguishes cavity types and the pipeline reconstructs dimensions within error bounds. Extending the framework to non-centered structures and unknown materials remains future work. Full article

Soft robotic hands are well suited for handling fragile and geometrically diverse objects, yet many existing designs still rely on fixed finger layouts, which limits grasping adaptability when object size varies substantially. To address this issue, this study proposes a four-finger pneumatic soft robotic hand with a synchronous variable-stroke base mechanism. The design combines a rigid reconfigurable base with compliant soft fingers, allowing the radial positions of the fingers to be adjusted before grasping. A system-level kinematic model is established to describe the relationship between base stroke, finger bending, and the reachable workspace of the hand. A prototype is fabricated, and comparative grasping experiments are conducted under fixed-stroke and variable-stroke configurations using objects with different grasping cross-sections. The results show that the proposed mechanism achieves stable geometric reconfiguration and improves grasping performance when the initial finger spacing is matched to the object size. In particular, the variable-stroke configuration provides better grasp stability and a wider usable grasping range than the fixed-stroke configuration. These findings indicate that geometric reconfiguration at the hand level is an effective way to enhance the adaptability of multi-finger soft robotic hands. Full article

Underwater soft robots offer many potential applications, including exploration, search, and rescue missions. Notably, these recently developed underwater soft robots present a safer and more adaptable alternative to rigid robots currently in use. Their flexible and deformable bodies enable them to easily adapt to challenging underwater environments and interact with diverse aquatic creatures and structures. In this paper, we present a soft buoyancy gripper that can manage buoyancy and adjust its position in the water without relying on external mechanisms. Modulating the volume of internal fluid can function both as a gripper and adjust buoyancy as needed. When buoyancy is reduced and fluid volume is minimized, the gripper can securely grasp objects, while increased fluid volume and buoyancy allow for delicate object placement. During experiments, the gripper successfully grasped and released multiple objects. When an extra channel was added, the crawling motion was achieved. The buoyancy control system demonstrates versatility and adaptability, offering the possibility of safe underwater exploration and research. Its ability to operate without harming marine environments or organisms makes it suitable for underwater research. Full article