Soft Somatosensitive Actuators via Embedded 3D Printing.

Soft actuators present promising properties regarding applications in soft robotics and human-machine interfaces. Especially when directly interfacing with human skin, soft thin actuators can match the mechanical coupling with human tissue. The exploration of improving the performance and robustness of soft actuators is crucial for the development of flexible devices. The demand for robust, flexible devices poses challenges to the performance and manufacturing methods of the actuators. The article illustrates techniques for the design and fabrication of soft thin-film actuators. These soft actuators are robust, and demonstrate potential in versatile scenarios. This protocol shows the potential of the thin-film actuators in three different applications. First, a crawling robot driven by soft thin-film actuators was fabricated. The robot is extremely robust. It can survive continuous hammering and remain functional even with three metal needles punctured through its body. Second, a soft robotic gripper, which can perform fine manipulation such as grasping a piece of paper without damaging it, was fabricated. Third, a haptic feedback device with a thin-film actuator was fabricated, which can provide touching feedback when interacting with human skin. This protocol demonstrates efficient fabrication processes for robust soft thin-film actuators, with various application potential for driving robust soft robotics.

Fused Deposition Modeling (FDM) 3D printing with Thermoplastic Polyurethane (TPU) has recently been used to fabricate soft robotic actuators and grippers, offering an alternative to traditional silicone casting, which is time-consuming and involves complex manufacturing steps. However, 3D printing soft robotic actuators and grippers using highly-flexible TPU (Shore hardness of 60A and 70A) remains unexplored. Although 60A and 70A TPUs are expected to provide excellent features for soft robots, designing and simulating soft robots using these TPU grades requires information about their best-fitting hyperelastic model, parameters, and material properties, which are hitherto unknown. Therefore, we characterize the 60A and 70A TPU behavior using uniaxial tensile tests and identify the best-fitting hyperelastic model with its appropriate parameters. We then demonstrated the feasibility of using these materials by 3D printing high-fidelity soft grippers using 60A and 70A TPU. Compared to a traditional silicone-based soft gripper of a similar size and shape, the proposed 3D printed TPU soft gripper can grasp objects over five times heavier and achieve more than twice the bending angle, while significantly reducing fabrication time and complexity. We also compared the bending angles of 60A and 70A TPU with 85A TPU soft fingers to demonstrate the importance of low-Shore-hardness materials. Furthermore, we compared the experimentally measured bending behavior of the TPU soft fingers with simulation results using the obtained hyperelastic parameters and found that they closely match the experimental results.

A fluidic relaxation oscillator for reprogrammable sequential actuation in soft robots

The advent of variable stiffness soft robotic grippers furnishes a conduit for exploration and manipulation within uncharted, non-structured environments. The paper provides a comprehensive review of the necessary technologies for the configuration design of soft robotic grippers with variable stiffness, serving as a reference for innovative gripper design. The design of variable stiffness soft robotic grippers typically encompasses the design of soft robotic grippers and variable stiffness modules. To adapt to unfamiliar environments and grasp unknown objects, a categorization and discussion have been undertaken based on the contact and motion manifestations between the gripper and the things across various dimensions: points contact, lines contact, surfaces contact, and full-bodies contact, elucidating the advantages and characteristics of each gripping type. Furthermore, when designing soft robotic grippers, we must consider the effectiveness of object grasping methods but also the applicability of the actuation in the target environment. The actuation is the propelling force behind the gripping motion, holding utmost significance in shaping the structure of the gripper. Given the challenge of matching the actuation of robotic grippers with the target scenario, we reviewed the actuation of soft robotic grippers. We analyzed the strengths and limitations of various soft actuation, providing insights into the actuation design for soft robotic grippers. As a crucial technique for variable stiffness soft robotic grippers, variable stiffness technology can effectively address issues such as poor load-bearing capacity and instability caused by the softness of materials. Through a retrospective analysis of variable stiffness theory, we comprehensively introduce the development of variable stiffness theory in soft robotic grippers and showcase the application of variable stiffness grasping technology through specific case studies. Finally, we discuss the future prospects of variable stiffness grasping robots from several perspectives of applications and technologies.

Soft pneumatic actuators possess attributes of large deformation, high driving force and light weight in the application of soft robots and smart devices. However, most reported soft pneumatic actuators are with rigid hydraulic source such as motor driven pump, piston and pressurized reservoir. These rigid and heavy hydraulic sources limit the actuation and compliance of the soft robots. Inspired by the bladders and hydrostatic skeleton of natural creatures, we propose a soft hydraulic robot consisting of dielectric elastomer (DE) and hydrogel, exhibiting an excellent actuating performance. An inflated DE balloon functions as the soft hydraulic source, in which the pressure of the containing water can be tuned by voltage. Hydrogel chambers are connected to the DE balloon as the hydraulic actuator, deforming as a soft robotic gripper. A new analytical approach is proposed to describe the system’s behaviors, which couples the electromechanical actuation of DE and the hydraulic deformation of hydrogel chamber. The proposed model is validated by good agreement between the numerical and experimental data. The proposed model could serve as a new tool for modeling and characterizing soft robots with hydraulic actuation. The working principles can guide the design and control of soft robots and smart structures.

Dual Users. Another way to make use of haptic devices for enhancing hands-on training is illustrated in Zhang et al. In this study, the haptic devices are not used to interact with the objects in a virtual world as in González-Mena and Neri et al., but to reproduce the expert gestures on the hands of the trainees. More precisely, the surgical tools handled by the expert are connected to individual haptic devices, each one recording in real time its connected tool trajectory. These trajectories are sent to the trainees' devices, which, in turn, guide the tools of the trainees. Thus, trainees can follow in their hands the expert tool trajectories, instead of only watching them and reproducing them on their own as usual. This experimental study suggests that haptic feedback superimposed on the trainee's motions can facilitate the performance of novice operators experiencing moments of difficulty, which was something that was already observed in other works (see the discussion of Zhang et al. for references). Even if the small sample size and use of a simple task limit the generalizability of their findings, this study illustrates that haptic training can be realized without any 3D virtual world, which requires accurate modeling for realistic haptic rendering of a complex task. Tactile Feedback. In Ratschat et al., the authors designed a shape exploration experiment to evaluate the effectiveness of multimodal tactile and kinesthetic feedback on shape perception. Sixteen participants were involved to reproduce different two-dimensional shapes with diverse characteristics in free space after exploring the shapes with two haptic feedback conditions: 1) kinesthetic feedback only and 2) kinesthetic plus tactile feedback. The kinesthetic feedback mechanism was implemented through an adapted single-degree-of-freedom SenseGlove Nova mechanism with an integrated electromagnetic brake. And tactile feedback was provided with a cable-driven platform mounted on the fingertip. To measure the participants' ability to perceive and reproduce the rendered shapes, the authors recorded the time participants spent exploring and reproducing the shapes and the error between the rendered and reproduced shapes after exploration and assessed the workload and motivation with questionnaires. Experimental results show that in a virtual shape exploration task without visual feedback, providing tactile and kinesthetic feedback is associated with more accurate and careful shape reproduction compared to exploring shapes with only kinesthetic feedback. Besides, the addition of tactile feedback does not seem to reduce the time spent during exploration, nor does it have an effect on motivation or workload. Thus, combining haptic and kinesthetic feedback could create more realistic virtual environments that may lead to better training results and easier transfer to real-world tasks, having implications across a variety of applications and training scenarios.Vibrotactile. Similarly, in Boutin et al . , the authors combined haptic (vibrotactile) feedback through the use of a haptic glove with a VR simulator for mixed-reality surgical training. They specifically focused on the potential for enhanced sensory feedback within VR. The authors chose to investigate External Ventricular Drain Placement (EVD), a common neurosurgery procedure, as a starting point. Experimental results demonstrated the simulator's accuracy, even though one major limitation was a lack of kinesthetic feedback. Like Ratschat et al., this work shows the potential to create more realistic mixed-reality environments that could extend beyond surgical applications.Kinesthetic. Force feedback plays a vital role in developing surgical skills, yet many virtual reality simulators lack this feature, creating a significant disparity between physical trainers and their digital counterparts, potentially limiting their effectiveness. In Abinaya and Manivannan, the authors take a different approach and use haptic feedback as an assessment metric for surgical training, focussing on laparoscopic surgery using a virtual reality simulator. By incorporating haptic feedback, they replicate the forces between the tool and the tissue, which directly correlate to tissue trauma. A virtual laparoscopic force model is incorporated into the simulator and used to determine the just noticeable differences of the laparoscopic grasping force. The results suggest that a simple linear model is sufficient for gripper force feedback, and a non-linear model does not affect the force perception. Expert laparoscopic surgeons agree that haptic feedback improves learning performance, and the force model improves the accuracy of object interaction during the gripping task.Innovative approaches to enhance surgical training must foster motor and sensory skills while reducing cognitive burden, lowering costs, and being conducive to faster design processes. This collection, the third on the topic of Haptic Training Simulation, underscores the potential of hapticenabled virtual reality tools in shaping the future of surgical education and improving patient outcomes.

The actuation of soft robotics has relied predominantly on pneumatic or hydraulic transmissions. However, these transmissions require good sealing and complicated valve control systems. Robots based on such transmissions are also tethered to bulky pneumatic or hydraulic pumps. In many practical grasping applications, soft actuators are expected to show several-fold stiffness change, which is difficult to achieve in pneumatic or hydraulic soft actuators. In this paper, a novel particle transmission method is proposed for soft gripper design. In the proposed method, particles enclosed in an elastic membrane are driven by a piston, thus problems associated with sealing are resolved as long as particle diameter is greater than the clearance between the piston and the cylinder. By controlling the volume of particles injected into the elastic membrane, bending of the actuator is achieved and its stiffness is increased accordingly. In the experiments, when injected particle volume is changed from 1.0 to 1.8 times that of the actuator's initial volume, the actuator bends up to 60° and its stiffness is increased by nearly seven folds from its initial state. A sample soft robotic gripper made of three such soft actuators is developed to test the feasibility and capability of the proposed method. It is believed that the proposed method could provide an important alternative to soft robotic gripper design and development.

This study is focused on developing a new dexterous soft robotic gripper with three fingers and an active palm capable of performing in-hand manipulation purposes. This innovative design meets all the dexterous manipulation requirements without any increase in mechanical complexity. In each finger, the bending position can be modified and controlled by moving a stiff rod inserted inside the center hole of the finger. In this way, the effective length of the manipulation can be changed. As a result, these reconfigurable fingers provide a more accessible workspace than conventional soft grippers. Besides, a large diversity of the finger's shape configurations results in more dexterity and in-hand manipulation capability. Workspace analysis is accomplished to characterize the advantages of the proposed design. The effectiveness of this soft robotic gripper is validated by different in-hand manipulation experimental tests, including rotation, regrasping, and rolling. The results suggest a promising solution to bridge the design gap between hard and soft robots for dexterous manipulation tasks. The hybrid design carries advantages of these two classes, such as reconfigurability, position, and shape control from hard robots, with large degrees of freedom (DOFs), complex deformations, and lightweight from soft robots. Like human manipulation, the palm plays a major role in stable grasping, especially for enhancing the in-hand manipulation capability. Therefore, we also investigate two types of vacuum palms (suction cup and granular particles) to guarantee a wide range of object manipulation tasks that cannot be completely performed by previously suggested soft grippers.

A magneto-elastica reinforced elastomer makes soft robotic grippers

This paper presents a hybrid tele-manipulation system, comprising of a sensorized 3-D-printed soft robotic gripper and a soft fabric-based haptic glove that aim at improving grasping manipulation and providing sensing feedback to the operators. The flexible 3-D-printed soft robotic gripper broadens what a robotic gripper can do, especially for grasping tasks where delicate objects, such as glassware, are involved. It consists of four pneumatic finger actuators, casings with through hole for housing the actuators, and adjustable base. The grasping length and width can be configured easily to suit a variety of objects. The soft haptic glove is equipped with flex sensors and soft pneumatic haptic actuator, which enables the users to control the grasping, to determine whether the grasp is successful, and to identify the grasped object shape. The fabric-based soft pneumatic haptic actuator can simulate haptic perception by producing force feedback to the users. Both the soft pneumatic finger actuator and haptic actuator involve simple fabrication technique, namely 3-D-printed approach and fabric-based approach, respectively, which reduce fabrication complexity as compared to the steps involved in a traditional silicone-based approach. The sensorized soft robotic gripper is capable of picking up and holding a wide variety of objects in this study, ranging from lightweight delicate object weighing less than 50 g to objects weighing 1100 g. The soft haptic actuator can produce forces of up to 2.1 N, which is more than the minimum force of 1.5 N needed to stimulate haptic perception. The subjects are able to differentiate the two objects with significant shape differences in the pilot test. Compared to the existing soft grippers, this is the first soft sensorized 3-D-printed gripper, coupled with a soft fabric-based haptic glove that has the potential to improve the robotic grasping manipulation by introducing haptic feedback to the users.

Unlike traditional hard grippers, soft robotic grippers are commonly made of soft materials so that the soft grippers can produce motion via elastic deformations of their compliant components. The advantages of compliance allow soft grippers to effectively eliminate shocks caused by hard contact, which usually occurs when a hard robotic gripper manipulates a hard object. Until now, the soft robotic grippers are able to operate numerous objects with irregular geometries and different textures. Besides, with the help of embedded sensors, soft robotic grippers have facilitated the growing automation of many tasks, which are thought to be far too delicate for robotic manipulation. This paper reviews the advancement in soft robotic grippers. The paper first introduces the actuation technologies followed by the design and fabrication techniques. The use of 3D printing techniques in the fabrication of the soft gripper is also discussed. The Review then highlights the challenges and future outlook in the fabrication of soft grippers and sensors.

Performa of SCARA based intelligent 3 axis robotic soft gripper for enhanced material handling

Realizing high-performance soft robotic grippers is challenging because of the inherent limitations of the soft actuators and artificial muscles that drive them, including low force generation, small actuation range, and poor compactness to name a few. Despite advances in this area, realizing compact soft grippers, which exhibit high dexterity and force output, is still challenging. This article explores using twisted string actuators (TSAs) to drive a soft robotic gripper. TSAs have been widely used in numerous robotic applications, but their inclusion in soft robots has been limited. The proposed design of the gripper was inspired by the human hand, with four fingers and a thumb. Tunable stiffness was implemented in the fingers by using antagonistic TSAs. The fingers' bending angles, actuation speed, blocked force output, and stiffness tuning are experimentally characterized. The gripper achieves a score of 6 on the Kapandji test and recreate 31 of the 33 grasps of the Feix GRASP taxonomy. It exhibits a maximum grasping force of 72 N, which is almost 13 times its own weight. A comparison study reveals that the proposed gripper exhibits equivalent or superior performance compared to other similar soft grippers.

Soft robotic grippers possess high structural compliance and adaptability, allowing them to grasp objects with unknown and irregular shapes and sizes. To enable more dexterous manipulation, soft sensors that are similar in mechanical properties to common elastomer materials are desired to be integrated into soft grippers. In this paper, we develop ionic hydrogel-based strain and tactile sensors and integrate these sensors into a three-finger soft gripper for learning-based object recognition and force-controlled grasping. Such hydrogel-based sensors have excellent conductivity, high stretchability and toughness, good ambient stability, and unique antifreezing property; they can be readily attached to a soft gripper at desired locations for strain and tactile sensing. By using a deep-learning model, the sensory soft gripper is demonstrated to be capable of grasping and recognizing objects at both room and freezing temperatures, and achieving close to 100% recognition accuracy for ten typical objects. Moreover, the capacitive tactile feedback of the gripper is utilized to develop a closed-loop force controller and realize force-controlled grasping of fragile or highly deformable objects. A new slip detection and compensation strategy is also proposed and validated for the sensory gripper for adjusting the grasping force in real time upon detecting slippage. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —The multimodal sensation of a soft robotic gripper could enrich its grasping functionalities and improve its manipulation performance. This research integrates novel antifreezing ionic hydrogel-based strain and tactile sensors into a three-finger soft robotic gripper for learning-based object recognition and force-controlled grasping. Constructed from a highly stretchable, ambient-stable, and antifreezing ionic hydrogel, the strain and tactile sensors can be readily integrated at the desired locations on the soft gripper, and can reliably operate at both ambient and freezing temperatures with excellent mechanical and electrical properties. Based on the feedback of the strain and tactile sensors, a deep learning model is employed to enable high-accuracy object recognition while grasping, which can be useful for manipulation in vision-free environments. Closed-loop force control and slip compensation strategies are also demonstrated for reliably grasping fragile/deformable objects and handling slip events during the manipulation of heavy objects. The sensory soft gripper and the associated object recognition and force control methods could find practical applications in a variety of robotic manipulation tasks.

Soft robots have received much attention due to their impressive capabilities including high flexibility and inherent safety features for humans or unstructured environments compared with hard-bodied robots. Soft actuators are the crucial components of soft robotic systems. Soft robots require dexterous soft actuators to provide the desired deformation for different soft robotic applications. Most of the existing soft actuators have only one or two deformation modes. In this article, a new soft pneumatic actuator (SPA) is proposed taking inspiration from Kirigami. Kirigami-inspired cuts are applied to the actuator design, which enables the SPA to be equipped with multiple deformation modes. The proposed Kirigami-inspired soft pneumatic actuator (KiriSPA) is capable of producing bending motion, stretching motion, contraction motion, combined motion of bending and stretching, and combined motion of bending and contraction. The KiriSPA can be directly manufactured using 3D printers based on the fused deposition modeling technology. Finite element method is used to analyze and predict the deformation modes of the KiriSPA. We also investigated the step response, creep, hysteresis, actuation speed, stroke, workspace, stiffness, power density, and blocked force of the KiriSPA. Moreover, we demonstrated that KiriSPAs can be combined to expand the capabilities of various soft robotic systems including the soft robotic gripper for delicate object manipulation, the soft planar robotic manipulator for picking objects in the confined environment, the quadrupedal soft crawling robot, and the soft robot with the flipping locomotion.