Grasp strategy-driven design of soft robotic grippers for food industry applications

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 robotic grippers are widely used in different mechatronic systems since they show great advantages in the adaptable grasping of objects with irregular shapes. However, as many soft grippers have a monolithic structure and gain their motion from the elastic deformation, it is difficult to use the conventional rigid-body mechanism theory to synthesize the shape of the soft grippers. To cope with this problem, topology optimization is frequently employed as the synthesis method since it can achieve automatic design of continuum-structure mechanisms. In this paper, we propose a 3D topology optimization framework in MATLAB to achieve automatic design of soft robotic grippers. Two design examples are also presented to illustrate the automatic synthesis process. Experimental tests have shown that the 3D topology optimized grippers in the example can successfully grasp objects with different shapes. In future work, the proposed framework can be further developed to synthesize soft robotic grippers with different actuation mechanisms and task-specific grasping behaviors.

A novel multi objective constraints based industrial gripper design with optimized stiffness for object grasping

Soft robotic grippers with compliance have great superiority in grabbing objects with irregular shape or fragility compared with traditional rigid grippers. The main limitations of such systems are small grasping force resulted from properties of soft actuators and lacking variable stiffness of soft robotic grippers, which prevent them from a larger wide range of applications. This article proposes a shape-memory alloy (SMA)-based soft gripper with variable stiffness composed of three robotic fingers for grasping compliantly at low stiffness and holding robustly at high stiffness. Each robotic finger mainly consisted of stiff parts and two variable stiffness joints is installed on the base with a specific angle. The paraffin as a variable stiffness material in the joint can be heated or cooled to change the stiffness of the robotic fingers. Results of experiments have shown that a single robotic finger can approximately achieve 18-fold stiffness enhancement. Each finger with two joints can actively achieve multiple postures by both changing the corresponding stiffness of joints and actuating the SMA wire. Based on these principles, the gripper can be applied to grasp objects with different shapes and a large range of weights, and the maximum grasping force of the gripper is increased to about 10 times using the variable stiffness joints. The final experiment is conducted to validate variable stiffness of the proposed soft grippers grasping an object.

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.

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.

The improvement of the load capacity of soft robotic grippers has always been a challenge. The load improvement methods of existing soft robotic grippers mainly include the development of soft actuators with high output force and the creation of closed gripping structures. Inspired by winding behaviors of animals and plants, we propose a high-load soft robotic gripper driven by pneumatic artificial muscles (PAMs) that combines the advantages of a high force soft actuator and a closed gripping structure. Most existing model formulations focus on characterizing the end force generated to the length contraction and applied pressure of PAMs. However, the focus of this work is to build the force model of PAMs in winding shape to analyze the tightening force of the high-load soft gripper, and the model is validated by a tightening force test. An experimental work is carried out to characterize the load capacity and multi-object gripping capacity of the high-load soft gripper. We experimentally prove that it can lift heavy objects that weigh up to 35.5 kg, which is more than 47 times its weight. This work contributes to the load improvement of soft robotic grippers, and the mathematical modeling of engineering systems with winding structures. The developed high-load soft gripper is expected to enter the practical application field from the laboratory.

This paper presents a proposed design of soft gripper fingers with adjustable stiffness that could be employed in the applications requiring adaptable and stable grasping. The main idea is to combine the under-actuated cable driven mechanism of a soft gripper finger with particle and layer jamming mechanisms to create a new grasping function with variable stiffness for different manipulation requirements. The movement of the soft gripper finger is produced by a cable-driven mechanism. However, particle and layer jamming chambers were embodied as a variable stiffness mechanism for the variable stiffness function. A single soft gripper finger module was developed and tested with particle and layer jamming chamber attached to it. The stiffness and response time of the soft gripper finger were measured in three distinct configurations: single finger module, particle jamming chamber attached to the finger, and layer jamming chamber attached to the finger. The comparison reveals that combining a soft finger with particle jamming increased performance by 20% compared to using the soft finger alone, while combining it with layer jamming led to an 80% increase. Additionally, layer jamming combined with a soft finger showed a 28% increase compared to particle jamming combined with a soft finger. Furthermore, simulation of the soft finger was conducted to estimate the deflection of the soft gripper finger under various applied forces. Moreover, proposed closed loop smart stiffness mechanism for the soft gripper was modeled and simulated by evaluating both soft and hard objects and simulation results were obtained for different cases. The findings indicated that the stiffness of the soft gripper finger can be adjusted for different grasping requirements.

Performing a successful robotic grasping to uncertain objects in unstructured environments is challenging. This study presents a new compliant soft robotic gripper for objects handling and cap manipulation through the coordination of three soft fingers and in-hand manipulation. The experiments are conducted to validate that the soft robotic gripper can successfully realize simultaneous grasping and capping manipulations with only one flexible shaft actuation for every single soft finger. Note to Practitioners —Uncertain object manipulation tasks pose significant challenges to a robotic gripper while grasping and capping unknown objects without damaging them. The existing rigid grippers have experienced flexible manipulation through multiple degrees of freedom (DoFs) by complex mechanical structures, and the soft gripper can realize stiffness-compliant manipulation differently. The proposed novel robotic in-hand manipulation can execute grasping and cap manipulation by a single flexible shaft to simultaneously achieve bending and rotational movements. The relationship between stretching force and finger’s curvature can enable a custom design for user-specific applications.

Advances in material sciences, control algorithms, and manufacturing techniques have facilitated rapid progress in soft grippers, propelling their adoption in various fields. In this review article, a comprehensive overview of the design and control aspects of intelligent soft robotic grippers tailored specifically for agricultural product handling is provided. Soft grippers have emerged as a promising solution for handling delicate and fragile objects. In this article, the recent progress in various gripper design, including fluidic and mechanical grippers, is elucidated and the role of advanced control approaches in enabling intelligent functions, such as object classification and grasping condition evaluation, is explored. Moreover, the challenges and opportunities pertaining to implementation of soft grippers in the agricultural industry are thoroughly discussed. While most demonstrations of soft grippers and their control strategies remain at the experimental stage, in this article, it is aimed to provide insights into the potential applications of soft grippers in agricultural product handling, thereby inspiring future research in this field.

Soft compliant gripping is a promising way to protect soft tissues from the grip damage caused by the high stress points in delicate surgical manipulation. In this paper, a new soft robotic gripper is designed to minimize the risk of soft tissues damage due to the over-gripping force generated by the conventional forceps. This new soft robotic gripper consists of a 3D-printed hook retractor shell, a soft inflatable actuator and two small rods. The ability of compliant grip is achieved by the inflated soft pneumatic actuator. Two small rods are used to separate the inflatable actuator into three-fingers-like bloats which can firmly grip the soft tissues by multi-contacts between the tissues and the gripper when the air pressure is applied to the pneumatic channel. In addition, it can protect the tissues against the harmful contacts with the rigid shell. The hook structure allows scooping-up motion during delicate surgical manipulation. The gripping tests and pulling force sensing experiments are carried out to evaluate the performance of the proposed soft robotic gripper.

A gripper is a part of a system or single device which could hold certain objects as solid materials. Soft Robotics is a new way to achieve a certain robotic mechanism which cannot be performed by the rigid body, for example, soft robots do not break and have better flexibility. In this work, four different grippers are designed from various bioinspired gripping mechanisms. These soft robotic grippers are used for gripping different types of objects such as soft materials, food items, delicate items, etc., which cannot be gripped by the conventional rigid body robotic gripper. Fingers of these soft grippers are made with soft silicone material and their base is made with Acrylonitrile Butadiene Styrene (ABS). The four grippers are actuated by pneumatic pressure, shape memory alloy wire and electromagnets. We have done experiments with these grippers for testing their gripping mechanism and force generated by the fingers while gripping an object.

The use of soft robotic grippers is an alternative to conventional rigid body grippers in industrial applications specifically in the handling of carpets. This paper presents, a novel design of a 3D soft robotic gripper based on a simulation model and experimental prototype that can be used for carpet handling applications. In addition, the fabrication method of the pneumatic soft robotic gripper is introduced. The pneu-net actuator geometrical parameters are optimized such as the thickness of the chamber walls and the internal structure of the chambers resulting in significantly improved pressure handling capabilities. The simple pneu-net and the modified actuator are tested at two different pressure 55 and 110 kPa, to check the range of motion. A single actuator is calculated to lift a maximum of five kilograms, with several actuators included in the gripper the weight carrying capabilities reached ten kilograms. The geometry was optimized to maximize weight carrying capabilities by increasing the amount of pressure the actuator can withstand. A finite element analysis using ABAQUS software is carried out to evaluate the stresses acting upon the soft gripper.

Soft robotic grippers, a novel category of robotic arm end‐effectors, have garnered significant interest owing to their distinct characteristics: soft structure, flexibility, and robust adaptability. These features grant them immense potential for applications across various domains. This study delves into a range of driving mode, encompassing tendon‐driven, fluidic actuation, smart materials‐based actuation, chemical reactive actuation, and variable stiffness approaches, and thoroughly analyzes the characteristics of each. The design of soft robotic grippers frequently draws inspiration from natural and biological organisms, is bolstered by advancements in materials science, and leverages hyperelastic materials to enable versatile manipulation capabilities. In the fabrication of these grippers, materials such as hydrogels, liquid crystal elastomers, electroactive polymers, and shape‐memory alloys are routinely employed. Additionally, fabrication techniques, including mold casting and additive manufacturing, are comprehensively analyzed. The study discusses the expansive application prospects of soft robotic grippers in medical treatment, emergency rescue, agriculture, and industrial production, emphasizing their potential for cross‐domain utilization. Furthermore, the paper outlines potential avenues for advancing soft robotic grippers in grasping strategies, key fabrication processes, and expanding application scenarios, thereby offering valuable insights into the development of innovative soft robots tailored for multifield operations.

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.