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Soft grippers have safer and more adaptable human–machine and environment–machine interactions than rigid grippers. However, most soft grippers with single gripping postures have a limited gripping range. Therefore, this paper aims to design a soft gripper with variable gripping posture to enhance the gripping adaptability.

This paper proposes a novel soft gripper consisting of a conversion mechanism and four spring-reinforced soft pneumatic actuators (SSPAs) as soft fingers. By adjusting the conversion mechanism, four gripping postures can be achieved to grip objects of different shapes, sizes and weights. Furthermore, a quasi-static model is established to predict the bending deformation of the finger. Finally, the bending angle of the finger is measured to validate the accuracy of the quasi-static model. The gripping force and gripping adaptability are tested to explore the gripping performance of the gripper.

Through experiments, the results have shown that the quasi-static model can accurately predict the deformation of the finger; the gripper has the most significant gripping force under the parallel posture, and the gripping adaptability of the gripper is highly enhanced by converting the four gripping postures.

By increasing the gripping posture, a novel soft gripper with enhanced gripping adaptability is proposed to enlarge the gripping range of the soft gripper with a single posture. Furthermore, a quasi-static model is established to analyze the deformation of SSPA.

The purpose of this paper is to gain an in-depth understanding into the research progress, hot spots and future trends in smart gripping technology in the field of apparel smart manufacturing.

This work scrutinised the current research status of the five automatic grasping methods for garment fabrics including the pneumatic suction grasping, the electrostatic grasping, the intrusive grasping and the dexterous grasping. Specifically, the principles, characteristics, main devices and the impact on garment production were discussed.

In particular, soft finger of the dexterous grasping method has good flexibility and adaptability in the process of fabric grasping, which provides a new solution for garment production automation. Up to now, the reviewed method in general exhibit good grasping speed, high grasping stability and flat grasping process. However, in the face of complex fabric materials which are thin and flexible and do not return their original shapes when deformed in practical applications, the gripper for automatic fabric grasping need new technological breakthroughs in the positioning accuracy, grab efficiency and flexible grasping.

The outcomes offered an overview of the research status and future trends of the automatic grasping methods for garment fabrics in the field of apparel intelligent manufacturing. It could not only provide scholars with convenience in identifying research hot spots and building potential cooperation in the follow-up research but also assist beginners in searching core scholars and literature of great significance.

This study aims to introduce a novel bidirectional soft actuator as an enhancement to conventional pneumatic network actuators. This improvement involves integrating air chambers positioned at specific angles to improve stability, adaptability and grasping efficiency in various environments.

The design approach incorporates air chambers positioned at a 45° angle relative to the horizontal direction at the actuator's terminus, along with additional chambers at a 90° angle. Mathematical models are developed for longitudinal and transverse bending, as well as for obliquely connected cavities, based on the assumption of piecewise constant curvature. Analyses are conducted on output forces, bending characteristics and end contact areas for both transverse and longitudinal ends.

The proposed soft actuator surpasses traditional pneumatic network actuators in gripping area due to the inclusion of a diagonal air cavity and a transverse pneumatic network structure at the terminus. As a result, it provides torsion and gripping force in both directions. Testing on a dedicated platform with two variants of grippers demonstrates superior gripping force capability and performance in complex environments.

Through the design of multiangle chambers, the soft actuator exhibits diverse driving angles and morphological variations, offering innovative design perspectives for industrial grasping.

The design of multiangle chambers facilitates personalized configurations of soft actuators by researchers, enabling tailored angles for specific interaction environments to achieve desired functionalities. This approach offers novel insights into soft actuator design, addressing more prevalent industrial grasping challenges.

This study introduces a novel soft actuator design that significantly enhances gripping capabilities in comparison to conventional pneumatic network actuators. The incorporation of specific air chamber configurations and mathematical modeling provides valuable insights for the development of adaptable and efficient robotic grippers for industrial and household applications.

The purpose of this paper is to describe a range of artificial muscle and soft gripping technologies for robotic applications.

Following a short introduction, this paper first discusses the role of air muscles and other pneumatic actuation technologies. It then considers electroactive polymer and shape‐memory alloys and finally discusses the prospects for various classes of electrohydrodynamic fluids.

This paper shows that a technologically diverse range of novel actuation techniques exist, or are under development, which can act as artificial muscles and soft grippers. They are based on pneumatics, shape changing materials and electrohydrodynamic fluids and have prospects to impart robots with improved or unique capabilities.

The paper provides an insight into developments in artificial muscle and soft gripping technologies. These are expected to play a vital role in future robot generations.

Flexible mechanical gripper has better safety and adaptability than a rigid mechanical hand. At present, there are few soft grippers for small objects on a millimeter scale. Therefore, the purpose of this paper is to design a soft pneumatic gripper for grasping millimeter-scale small and fragile objects such as jewelry and electronic components.

By simulating the clamping action of the bird’s mouth and combining the high flexibility of the soft material, the bird’s beak soft pneumatic gripper is designed. First, the internal cavity of the gripping end of the gripper is determined by bending deformation calculation, and the brief manufacturing process of the gripper is outlined. Then, the single finger of the soft gripper is modeled mechanically, and the relationship between air pressure and bending deformation of the single finger is obtained. Finally, the experimental platform of the soft mechanical gripper is built, and the gripping performance of silicone rubber material is tested by comparison test, bending deformation test, stability test, adaptability test and gripping accuracy test.

The designed gripper has the advantages of simple structure, convenient operation, easy grasping of different small objects of millimeter-scale and good adaptability. It can grasp the precise dispensing needle with a minimum diameter of 0.19 mm, and its accuracy meets daily use.

A new type of soft pneumatic, the mechanical gripper is proposed and manufactured. According to the shape of the bird’s beak and the calculation of bending performance, a hollow finger gripper with better bending performance is designed. Various test results show that the gripper has a significant clamping effect on millimeter small objects, which supplements the research field of millimeter small object gripper.

Varied shapes and sizes of different products with irregular rough surface and fragile properties give a challenge to traditional contact gripping. Single Bernoulli grippers are not suited to handle fragile objects as the impact of center negative pressure force could result in large deformation and stress which damage the materials, and they are also have some limitations for gripping objects with different large and small shapes. Thus, this paper aims to design a non-contact gripper for soft, rough-surfaced and fragile objects gripping with multi Bernoulli heads, which have optimal structures and parameters.

The compressed air is ejected into four Bernoulli heads through radial and long flow channels, then passes through four strip-shaped narrow gaps after fully developing in the annular cavity to provide negative pressure. Based on the mathematic model and the computational model, the key structural parameters affecting the gripping performance are selected, and parameters optimization of the gripper is performed by computational fluid dynamics simulation analysis and performance evaluation. The orthogonal method is used and L16 orthogonal array is selected for experimental design and optimization. The characteristics of the designed gripper are tested from the aspects of pressure distribution and lifting force.

From the applications in gripping different objects, the designed non-contact gripper can grip varied shapes and sizes of soft, rough-surfaced, fragile and sliced objects with little effect of torque.

In this paper, a non-contact gripper is designed for handling soft, rough-surfaced and fragile objects based on the Bernoulli principle. A systematic approach, which consists of modeling, simulation, optimization and measurement is provided for the non-contact gripper design and tests.

The garment industry will be one of the major beneficiaries of advances in smart manufacturing, as it is highly labor-intensive and heavily depends on labor force. Manipulating robots in human environments has made great strides in recent years. However, the main research has focused on rigid, solid objects and core capabilities such as grasping, placing remain a challenging problem when dealing with soft textiles. The experimental results indicate that adopting the proposed bionic soft finger will provide garment manufacturers with smart manufacturing capabilities. Then, the purpose of this paper is to utilize the flexibility of the soft finger to transfer fabric layer by layer without damage in garment automation.

In this paper, a new way to separate layer by layer pieces of fabric has been inspired by the rise of soft robotics and their applications in automation. Fabric gripping is accomplished by wiping deformation and pinching the fabric. A single fabric piece is separated from cutting pile by the soft finger in four steps: making an arch by pressing, wiping deformation, grasping and separating, and placing.

The case study demonstrated that the soft finger arrangement for automated grasping of fabric pieces of a garment can be successfully applied to delicate fabric. A combination of cloth shape and weight determines the number of soft fingers. In addition, the soft finger was tested on different types of fabrics to determine its performance and application capabilities. The technology may be used to produce clothing intelligently in the future, such as intelligent stacking, intelligent transportation and intelligent packaging, to increase clothing industry productivity.

An industrial bionic soft finger gripping system is proposed in this paper for application in the field of fabric automatic manipulation. A piece of fabric could be picked up and released layer by layer from a stack by the proposed gripper without creating any damage to it. Soft grippers have the right proportion of softness and rigidity like a human being. A soft finger has a potential affinity for soft materials such as fabrics without damaging either their surface or their properties.

This paper aims to provide details of recent commercial and academic developments in flexible and soft grippers and considers their impact on emerging robotic markets.

Following an introduction, this paper first considers commercially available anthropomorphic robotic hands and soft grippers. It then discusses a selection of recent research activities and concludes with a brief discussion of the potential of these developments.

Anthropomorphic robotic hands, which seek to mimic the structure and capabilities of the human hand, together with a technologically diverse family of soft grippers have recently have been commercialised. Most are produced by companies which spun-out from academic establishments. A strong body of innovative research continues and involves a wide range of principles and technologies. These gripping technologies are expected to catalyse several new and emerging applications; the most important being in agile manufacturing, particularly when used with collaborative robots (cobots).

This paper provides details of recent developments and research into anthropomorphic hands and soft grippers and an insight into their applications.

In an empirical study learning opportunities were identified. Learning opportunities are enablers or disablers for the achievement of shared understanding.

Actors were interviewed about their communication process. The learning history method was used to analyze and structure the data. From the learning histories learning opportunities were derived. Finally, the learning opportunities were categorized.

Learning opportunities were found on three levels: the actor, project and company level. They were also joined in six themes. Combining these two patterns showed that learning opportunities are interrelated.

The case study done was retrospective for the actors involved. Therefore, only conclusions could be drawn on the achievement of shared understanding. To be able to say more about the creation of shared understanding, following a NPD project real time would be desirable, in future research.

This study shows the importance for managers of looking across boundaries. Only solving problems integrally within the organization will help to solve problems successfully. Knowing the learning opportunities of a NPD project finished, will help them to improve future projects. The explicit use of storytelling during a NPD project may help to create a learning organization with shared understanding between the actors.

Previous research showed, shared understanding is important, to be able to manage the integration of different knowledge domains. However, these studies do not describe learning opportunities for the achievement of shared understanding, which was done in this study.

The purpose of this paper is to provide details of biomimetic and neuromorphic sensor research and developments and discuss their applications in robotics.

Following a short introduction, this first provides examples of recent biomimetic gripping and sensing skin research and developments. It then considers neuromorphic vision sensing technology and its potential robotic applications. Finally, brief conclusions are drawn.

Biomimetics aims to exploit mechanisms, structures and signal processing techniques which occur in the natural world. Biomimetic sensors and control techniques can impart robots with a range of enhanced capabilities such as learning, gripping and multidimensional tactile sensing. Neuromorphic vision sensors offer several key operation benefits over conventional frame-based imaging techniques. Robotic applications are still largely at the research stage but uses are anticipated in enhanced safety systems in autonomous vehicles and in robotic gripping.

This illustrates how tactile and imaging sensors based on biological principles can contribute to imparting robots with enhanced capabilities.