Search Results (45)

This study presents the design, fabrication, and experimental validation of a two-finger robotic gripper featuring a 135° V-shaped fingertip profile tailored for lightweight waste collection in laboratory-scale environmental robotics. The gripper was developed with a strong emphasis on cost-effectiveness and manufacturability, utilizing a desktop 3D printer and off-the-shelf servomotors. A four-bar linkage mechanism enables parallel jaw motion and ensures stable surface contact during grasping, achieving a maximum opening range of 71.5 mm to accommodate common cylindrical objects. To validate structural integrity, finite element analysis (FEA) was conducted under a 0.6 kg load, yielding a safety factor of 3.5 and a peak von Mises stress of 12.75 MPa—well below the material yield limit of PLA. Experimental testing demonstrated grasp success rates of up to 80 percent for typical waste items, including bottles, disposable cups, and plastic bags. While the gripper performs reliably with rigid and semi-rigid objects, further improvements are needed for handling highly deformable materials such as thin films or soft bags. The proposed design offers significant advantages in terms of rapid prototyping (a print time of approximately 10 h), modularity, and low manufacturing cost (with an estimated in-house material cost of USD 20 to 40). It provides a practical and accessible solution for small-scale robotic waste-collection tasks and serves as a foundation for future developments in affordable, application-specific grippers. Full article

Pneumatic soft manipulators are one of the current development trends in the field of manipulators. The soft manipulator that has been developed at present still has problems with single function and poor load-bearing capacity. This paper designs a composite soft finger inspired by the human middle finger, featuring a dual-chamber pneumatic drive and embedded steel sheet structure. Utilizing the principles of moment equilibrium and virtual work, a theoretical model for the bending behavior of the soft finger is developed, and the correlation between the bending angle and driving air pressure is derived. The determination process of key parameters and their influence on bending deformation are explained in detail through simulation. The bending experiment confirmed the reliability of the theoretical model. The fingertip force test indicates that the composite finger exerts a greater force than the ordinary one, with the extra force equivalent to 42.57% of the composite finger’s own fingertip force. Subsequent tests on the soft robotic hand measured the hooking quality, gripping diameter, and gripping force. The hooking experiment confirmed that composite fingers have a stronger load-bearing capacity than ordinary fingers, with an extra capacity equivalent to 31.25% of the composite finger’s own load-bearing capacity. Finally, the grasping experiment demonstrates that the soft manipulator can grasp objects of varying shapes and weights, indicating its strong adaptability and promising applications. Full article

The growing population of hand dysfunction patients necessitates advanced rehabilitation technologies. Current robotic solutions face limitations in motion compatibility and systematic design frameworks. This study develops a rigid–soft coupling rehabilitation robot integrating linkage mechanisms with soft components. A machine vision system captures natural grasping trajectories, analyzed through polynomial regression. Hierarchical constraint modeling and an improved artificial bee colony algorithm optimize linkage dimensions and control strategies, achieving enhanced human–robot kinematic matching. Finite element simulations using a Yeoh hyperelastic model refine soft component geometry for balance compliance and coordination. Prototype validation demonstrates high-precision trajectory tracking, grasping across 20–70 mm objects, and steady fingertip forces during training. Experimental results confirm the system’s ability to replicate physiological motion patterns and adapt to multiple rehabilitation scenarios. Full article

To address the limitations of single-chamber soft grippers, such as constant curvature, insufficient motion flexibility, and restricted fingertip movement, this study proposes a soft gripper inspired by the structure of the human hand. The designed soft gripper consists of three fingers, each comprising three soft joints and four phalanges. The air chambers in each joint are independently actuated, enabling flexible grasping by adjusting the joint air pressure. The constraint layer is composed of a composite material with a mass ratio of 5:1:0.75 of PDMS base, PDMS curing agent, and PTFE, which enhances the overall finger stiffness and fingertip load capacity. A nonlinear mathematical model is established to describe the relationship between the joint bending angle and actuation pressure based on the constant curvature assumption. Additionally, the kinematic model of the finger is developed using the D–H parameter method. Finite element simulations using ABAQUS analyze the effects of different joint pressures and phalange lengths on the grasping range, as well as the fingertip force under varying actuation pressures. Bending performance and fingertip force tests were conducted on the soft finger actuator, with the maximum fingertip force reaching 2.21 N. The experimental results show good agreement with theoretical and simulation results. Grasping experiments with variously sized fruits and everyday objects demonstrate that, compared to traditional single-chamber soft grippers, the proposed humanoid joint-inspired soft gripper significantly expands the grasping range and improves grasping force by four times, achieving a maximum grasp weight of 0.92 kg. These findings validate its superior grasping performance and potential for practical applications. Full article

This paper introduces the TacFR-Gripper, a novel reconfigurable soft robotic gripper inspired by the Fin-Ray effect and equipped with tactile skin. The gripper incorporates a four-bar mechanism for accurate finger bending and a reconfigurable design to change the relative positions between the fingers and palm, enabling precise and adaptable object grasping. This 5-Degree-of-Freedom (DOF) soft gripper can facilitate dexterous manipulation of objects with diverse shapes and stiffness and is beneficial to the safe and efficient grasping of delicate objects. An array of Force Sensitive Resistor (FSR) sensors is embedded within each robotic fingertip to serve as the tactile skin, enabling the robot to perceive contact information during manipulation. Moreover, we implemented a threshold-based tactile perception approach to enable reliable grasping without accidental slip or excessive force. To verify the effectiveness of the TacFR-Gripper, we provide detailed workspace analysis to evaluate its grasping performance and conducted three experiments, including (i) assessing the grasp success rate across various everyday objects through different finger configurations, (ii) verifying the effectiveness of tactile skin with different control strategies in grasping, and (iii) evaluating the in-hand manipulation capabilities through object pose control. The experimental results indicate that the TacFR-Gripper can grasp a wide range of complex-shaped objects with a high success rate and deliver dexterous in-hand manipulation. Additionally, the integration of tactile skin is demonstrated to enhance grasp stability by incorporating tactile feedback during manipulations. Full article

Virtual reality systems may benefit from wearable (fingertip-mounted) haptic displays capable of rendering the softness of virtual objects. According to neurophysiological evidence, the easiest reliable way to render a virtual softness is to generate purely tactile (as opposed to kinaesthetic) feedback to be delivered via a finger-pulp-interfaced deformable surface. Moreover, it is necessary to control not only the skin indentation depth by applying quasi-static (non-vibratory) contact pressures, but also the skin contact area. This is typically impossible with available devices, even with those that can vary the contact area, because the latter cannot be controlled due to the complexity of sensing it at high resolutions. This causes indetermination on an important tactile cue to render softness. Here, we present a technology that allows the contact area to be open-loop controlled via personalised optical calibrations. We demonstrate the solution on a modified, pneumatic wearable tactile display of softness previously described by us, consisting of a small chamber containing a transparent membrane inflated against the finger pulp. A window on the device allowed for monitoring the skin contact area with a camera from an external unit to generate a calibration curve by processing photos of the skin membrane interface at different pressures. The solution was validated by comparisons with an ink-stain-based method. Moreover, to avoid manual calibrations, a preliminary automated procedure was developed. This calibration strategy may be applied also to other kinds of displays where finger pulps are in contact with transparent deformable structures. Full article

Button mushrooms (Agaricus bisporus) grow in multilayered Dutch shelves with limited space between two shelves. As an alternative to conventional hand-picking, automated harvesting in recent times has gained widespread popularity. However, automated harvesting of mushrooms faces critical challenges in the form of growing environment, limited spaces, picking forces, and efficiency. End effectors for picking button mushrooms are an integral part of the automated harvesting process. The end effectors developed so far are oversized, bulky, and slow and thus are unsuitable for commercial mushroom harvesting applications. This paper introduces a novel three-finger hybrid gripper with rigid and soft parts, specifically designed for harvesting button mushrooms in automated systems even on narrow shelves. It discusses the design, fabrication, force analysis, and picking performance of the gripper in detail for both individual and clustered mushrooms. The results indicate that the gripping force depends on mushroom density and size. The inclusion of textured soft pads on gripper fingertips performs better compared with plain soft pads by reducing force by up to 20% and improving picking time. The gripper achieved a 100% picking success rate for single-grown mushrooms and 64% for clusters, with reduced picking times compared with existing end effectors. However, harvesting clustered mushrooms led to increased damage, suggesting the need for future improvements. Full article

Currently, intelligent robotics is supplanting traditional industrial applications. It extends to business, service and care industries, and other fields. Stable robot grasping is a necessary prerequisite for all kinds of complex application scenarios. Herein, we propose a method for preparing an elastic porous material with adjustable conductivity, hardness, and elastic modulus. Based on this, we design a soft robot tactile fingertip that is gentle, highly sensitive, and has an adjustable range. It has excellent sensitivity (~1.089 kpa⁻¹), fast response time (~35 ms), and measures minimum pressures up to 0.02 N and stability over 500 cycles. The baseline capacitance of a sensor of the same size can be increased by a factor of 5–6, and graphene adheres better to polyurethane sponge and has good shock absorption. In addition, we demonstrated the application of the tactile fingertip to a two-finger manipulator to achieve stable grasping. In this paper, we demonstrate the great potential of the soft robot tactile finger in the field of adaptive grasping for intelligent robots. Full article

In robot-assisted microsurgery (RAMS), surgeons often face the challenge of operating with minimal feedback, particularly lacking in haptic feedback. However, most traditional desktop haptic devices have restricted operational areas and limited dexterity. This report describes a novel, lightweight, and low-budget wearable haptic controller for teleoperated microsurgical robotic systems. We designed a wearable haptic interface entirely made using off-the-shelf material-PolyJet Photopolymer, fabricated using liquid and solid hybrid 3D co-printing technology. This interface was designed to resemble human soft tissues and can be wrapped around the fingertips, offering direct contact feedback to the operator. We also demonstrated that the device can be easily integrated with our motion tracking system for remote microsurgery. Two motion tracking methods, marker-based and marker-less, were compared in trajectory-tracking experiments at different depths to find the most effective motion tracking method for our RAMS system. The results indicate that within the 4 to 8 cm tracking range, the marker-based method achieved exceptional detection rates. Furthermore, the performance of three fusion algorithms was compared to establish the unscented Kalman filter as the most accurate and reliable. The effectiveness of the wearable haptic controller was evaluated through user studies focusing on the usefulness of haptic feedback. The results revealed that haptic feedback significantly enhances depth perception for operators during teleoperated RAMS. Full article

The coconut crab, Birgus latro, has black protrusions on the tops of its walking legs and claw fingers. In addition, there are regularly aligned small black protrusions on parts of the exoskeleton surface of the claws and leg. In this study, the elemental composition, crystal structure, tissue structure, and mechanical properties of these protrusions were studied using a materials science approach, and the results were compared with those of mineralized cuticle. These leg tips were found to be a non-calcified fibrous tissue of α-chitin connected to the mineralized cuticle. The tip of the second walking leg was elongated and had a pointed shape with an oval cavity at its center that was more than 1000 times larger than the pore tubes (100–350 nm) of the mineralized cuticle. It was very soft, with a hardness of 0.4 GPa, corresponding to 11–12% of the hardness of the hard exocuticle and 55–57% of the hardness of the soft endocuticle. The elastic modulus of 8.0 GPa obtained by means of nanoindentation testing was consistent with that of α-chitin fibers of shrimp shells obtained by means of tensile testing. These soft protrusions provide a secure grip on the surfaces of trees or rocks and protect the claw fingertips. It was concluded that the black protrusions are related to a unique ecological (engaging in vertical movements, entering and exiting limestone caves, and escape behavior) aspect of the coconut crab, the largest terrestrial crustacean. Full article

Multisensory human–machine interfaces for virtual- or augmented-reality systems are lacking wearable actuated devices that can provide users with tactile feedback on the softness of virtual objects. They are needed for a variety of uses, such as medical simulators, tele-operation systems and tele-presence environments. Such interfaces require actuators that can generate proper tactile feedback, by stimulating the fingertips via quasi-static (non-vibratory) forces, delivered through a deformable surface, so as to control both the contact area and the indentation depth. The actuators should combine a compact and lightweight structure with ease and safety of use, as well as low costs. Among the few actuation technologies that can comply with such requirements, pneumatic driving appears to be one of the most promising. Here, we present an investigation on a new type of pneumatic wearable tactile displays of softness, recently described by our group, which consist of small inflatable chambers arranged at the fingertips. In order to objectively assess the perceptual response that they can elicit, a systematic electroencephalographic study was conducted on ten healthy subjects. Somatosensory evoked potentials (SEPs) were recorded from eight sites above the somatosensory cortex (Fc2, Fc4, C2 and C4, and Fc1, Fc3, C1 and C3), in response to nine conditions of tactile stimulation delivered by the displays: stimulation of either only the thumb, the thumb and index finger simultaneously, or the thumb, index and middle finger simultaneously, each repeated at tactile pressures of 10, 20 and 30 kPa. An analysis of the latency and amplitude of the six components of SEP signals that typically characterise tactile sensing (P50, N100, P200, N300, P300 and N450) showed that this wearable pneumatic device is able to elicit predictable perceptual responses, consistent with the stimulation conditions. This proved that the device is capable of adequate actuation performance, which enables adequate tactile perceptual performance. Moreover, this shows that SEPs may effectively be used with this technology in the future, to assess variable perceptual experiences (especially with combinations of visual and tactile stimuli), in objective terms, complementing subjective information gathered from psychophysical tests. Full article

Aiming at the issues of complex manufacturing processes and unstable bonding after individual manufacturing in current soft manipulator forming methods, this study investigated the mechanical characteristics of a pneumatically driven soft-picking manipulator formed by the stereolithography (SLA) process and evaluated its application in grasping fruits and vegetables. The soft-picking manipulator mainly consists of three soft actuators designed in an integrated folded structure to simplify the manufacturing process compared to a conventional one. A finite element model (FEM) of the actuator was created to analyze the bending deformation capability under different pressures, and the simulated results match well with the experimental ones. Under the 60 kPa pressure, the maximum grasping force for fingertip- and envelope-grasping is 3.94 N and 8.87 N, respectively. The grasping tests of several fruits and vegetables of different weights and sizes by the soft manipulator were examined, and the results showed that the manipulator has strong adaptability. For spherical and elongated fruits and vegetables, the completion time for grasping is approximately 8.59 ± 1.26 s and 10.99 ± 1.79 s, respectively, and for irregularly shaped ones, the pressure is increased accordingly to the increased grasping stability. This study may provide a basis for the development of a soft manipulator for sorting and picking fruits and vegetables. Full article

Soft fingertips have distinct intrinsic features that allow robotic hands to offer adjustable and manageable stiffness for grasping. The stability of the grasp is determined by the contact stiffness between the soft fingertip and the object. Within this work, we proposed a line vector representation method based on the Winkler Model and investigated the contact stiffness between soft fingertips and objects to achieve control over the gripping force and fingertip displacement of the gripper without the need for sensors integrated in the fingertip. First, we derived the stiffness matrix of the soft fingertip, analyzed the contact stiffness, and constructed the global stiffness matrix; then, we established the grasp stiffness matrix based on the contact stiffness model, allowing for the analysis and evaluation of the soft fingertip’s manipulating process. Finally, our experiment demonstrated that the variation in object orientation caused by external forces can indicate the contact force status between the fingertip and the object. This contact force status is determined by the contact stiffness. The position error between the theoretical work and tested data was less than 9%, and the angle error was less than 5.58%. The comparison between the theoretical contact stiffness and the experimental results at the interface indicate that the present model for the contact stiffness is appropriate and the theoretical contact stiffness is consistent with the experiment data. Full article

This paper presents a quasi-static model-based control algorithm for controlling the motion of a soft robotic exo-digit with three independent actuation joints physically interacting with the human finger. A quasi-static analytical model of physical interaction between the soft exo-digit and a human finger model was developed. Then, the model was presented as a nonlinear discrete-time multiple-input multiple-output (MIMO) state-space representation for the control system design. Input–output feedback linearization was utilized and a control input was designed to linearize the input–output, where the input is the actuation pressure of an individual soft actuator, and the output is the pose of the human fingertip. The asymptotic stability of the nonlinear discrete-time system for trajectory tracking control is discussed. A soft robotic exoskeleton digit (exo-digit) and a 3D-printed human-finger model integrated with IMU sensors were used for the experimental test setup. An Arduino-based electro-pneumatic control hardware was developed to control the actuation pressure of the soft exo-digit. The effectiveness of the controller was examined through simulation studies and experimental testing for following different pose trajectories corresponding to the human finger pose during the activities of daily living. The model-based controller was able to follow the desired trajectories with a very low average root-mean-square error of 2.27 mm in the x-direction, 2.75 mm in the y-direction, and 3.90 degrees in the orientation of the human finger distal link about the z-axis. Full article

Industries such as the manufacturing or logistics industry need algorithms that are flexible to handle novel or unknown objects. Many current solutions in the market are unsuitable for grasping these objects in high-mix and low-volume scenarios. Finally, there are still gaps in terms of grasping accuracy and speed that we would like to address in this research. This project aims to improve the robotic grasping capability for novel objects with varying shapes and textures through the use of soft grippers and data-driven learning in a hyper-personalization line. A literature review was conducted to understand the tradeoffs between the deep reinforcement learning (DRL) approach and the deep learning (DL) approach. The DRL approach was found to be data-intensive, complex, and collision-prone. As a result, we opted for a data-driven approach, which to be more specific, is PointNet GPD in this project. In addition, a comprehensive market survey was performed on tactile sensors and soft grippers with consideration of factors such as price, sensitivity, simplicity, and modularity. Based on our study, we chose the Rochu two-fingered soft gripper with our customized force-sensing resistor (FSR) force sensors mounted on the fingertips due to its modularity and compatibility with tactile sensors. A software architecture was proposed, including a perception module, picking module, transfer module, and packing module. Finally, we conducted model training using a soft gripper configuration and evaluated grasping with various objects, such as fast-moving consumer goods (FMCG) products, fruits, and vegetables, which are unknown to the robot prior to grasping. The grasping accuracy was improved from 75% based on push and grasp to 80% based on PointNetGPD. This versatile grasping platform is independent of gripper configurations and robot models. Future works are proposed to further enhance tactile sensing and grasping stability. Full article