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Soft robotics is currently a rapidly growing new field of robotics whereby the robots are fundamentally soft and elastically deformable. Fabrication of soft robots is currently challenging and highly time- and labor-intensive. Recent advancements in three-dimensional (3D) printing of soft materials and multi-materials have become the key to enable direct manufacturing of soft robots with sophisticated designs and functions. Hence, this paper aims to review the current 3D printing processes and materials for soft robotics applications, as well as the potentials of 3D printing technologies on 3D printed soft robotics.

The paper reviews the polymer 3D printing techniques and materials that have been used for the development of soft robotics. Current challenges to adopting 3D printing for soft robotics are also discussed. Next, the potentials of 3D printing technologies and the future outlooks of 3D printed soft robotics are presented.

This paper reviews five different 3D printing techniques and commonly used materials. The advantages and disadvantages of each technique for the soft robotic application are evaluated. The typical designs and geometries used by each technique are also summarized. There is an increasing trend of printing shape memory polymers, as well as multiple materials simultaneously using direct ink writing and material jetting techniques to produce robotics with varying stiffness values that range from intrinsically soft and highly compliant to rigid polymers. Although the recent work is done is still limited to experimentation and prototyping of 3D printed soft robotics, additive manufacturing could ultimately be used for the end-use and production of soft robotics.

The paper provides the current trend of how 3D printing techniques and materials are used particularly in the soft robotics application. The potentials of 3D printing technology on the soft robotic applications and the future outlooks of 3D printed soft robotics are also presented.

Soft robotics is a burgeoning field owing to its high adaptability and safety in human–machine interaction and unstructured environments. However, the feedback control of soft actuators with flexible sensors is still a challenge.

To address this issue, this study proposes an optical fibre-based sensing membrane for the posture measurement of soft pneumatic bending actuators. The major contribution is the development of a flexible sensing membrane with a high sensitivity and repeatability for the feedback control of soft actuators. The characteristics of sensing membrane were analysed. The relationship between wavelength shift and bending curvature was derived. The curvatures of soft actuator were measured at four bending status, and the postures were reconstructed.

The results indicate that the measurement error is less than 2.1% of the actual bending curvature. The sensitivity is up to 212.8 pm/m⁻¹, and the signal fluctuation in repeated measurements is negligible. This approach has broad application prospects in soft robotics, because it makes the optical fibre achieve more strength and compatible with soft actuators, thus improving the sensing accuracy, sensitivity and reliability of fibre sensors.

Different from previous approaches, an optical fibre with FBGs is embedded into a multilayered polyimide film to form a flexible sensing membrane, and the membrane is embedded into a soft pneumatic bending actuator as the smart strain limited layer which is able to measure the posture in real time. This approach makes the optical fibre stronger and compatible with the soft pneumatic bending actuator, and the sensing accuracy, sensitivity and reliability are improved. The proposed sensing configuration is effective for the feedback control of the soft pneumatic bending actuators.

The purpose of this study is to analyze the robot trends of the next generation.

This paper is divided into two sections: the key modern technology on which Europe's robotics industry has built its foundation is described. Then, the next key megatrends were analyzed.

Artificial intelligence (AI) and robotics are technologies of major importance for the development of humanity. This time is mature for the evolution of industrial and service robots. The perception of robot use has changed from threading to aiding. The cost of mass production of technological devices is decreasing, while a rich set of enabling technologies is under development. Soft mechanisms, 5G and AI have enabled us to address a wide range of new problems. Ethics should guide human behavior in addressing this newly available powerful technology in the right direction.

The paper describes the impact of new technology, such as AI and soft robotics. The world of work must react quickly to these epochal changes to enjoy their full benefits.

Soft actuators using pneumatic-chamber (PneuNet)-based designs have been of interest in the area of soft robotics with scope of application in the area of biomedical assistance and smart agriculture. Researchers have attempted to investigate multiple chambers in parallel to examine their deformation characteristics. However, there is a lacuna for investigation of the deformation characteristics of four parallel chambered soft actuators. The purpose of this study is to comprehensively investigate the different possible actuation scenarios and the resulting bending/deformation behaviours.

Therefore, in this study, a four-chambered PneuNet actuator is numerically investigated to evaluate the effects of pressurization scenarios and pressure levels on its performance, operating reaching and working volume.

The results of this study revealed that two-adjacent chamber equal pressurization and three-chamber pressurizations result in increased bending. However, two-opposite chamber pressurization reduces the bending angle with pressure levels in the lower pressure chamber. The maximum bending angle of 97° was achieved for single-chamber pressurization of 300 kPa. The two-adjacent chamber unequal pressurization can achieve a sweeping motion in the actuator along with bending. The working volume and reaching capability analysis revealed that the actuator can reach around 71% of the dimensional operating space.

The results provide fundamental guidance on the output nature of motion which can be obtained under different pressurization scenarios using the four-chambered design soft actuator, thereby making it a practical guide for implementation for useful applications.

The comprehensive pressurization scenarios and pressure level variations reported in this study will serve as fundamental operating guidelines for any practical implementation of the four-chambered PneuNet actuator.

Mechanoreception is crucial for robotic planning and control applications, and for robotic fingers, mechanoreception is generally obtained through tactile sensors. As a new type of robotic finger, the soft finger also requires mechanoreception, like contact force and object stiffness. Unlike rigid fingers, soft fingers have elastic structures, meaning there is a connection between force and deformation of the soft fingers. It allows soft fingers to achieve mechanoreception without using tactile sensors. This study aims to provide a mechanoreception sensing scheme of the soft finger without any tactile sensors.

This research uses bending sensors to measure the actual bending state under force and calculates the virtual bending state under assumed no-load conditions using pressure sensors and statics model. The difference between the virtual and actual finger states is the finger deformation under load, and its product with the finger stiffness can be used to calculate the contact force. There are distinctions between the virtual and actual finger state change rates in the pressing process. The difference caused by the stiffness of different objects is different, which can be used to identify the object stiffness.

Contact force perception can achieve a detection accuracy of 0.117 N root mean square error within the range of 0–6 N contact force. The contact object stiffness perception has a detection average deviation of about 15%, and the detection standard deviation is 10% for low-stiffness objects and 20% for high-stiffness objects. It performs better at detecting the stiffness of low-stiffness objects, which is consistent with the sensory ability of human fingers.

This paper proposes a universal mechanoreception method for soft fingers that only uses indispensable bending and pressure sensors without tactile sensors. It helps to reduce the hardware complexity of soft robots. Meanwhile, the soft finger no longer needs to deploy the tactile sensor at the fingertip, which can benefit the optimization design of the fingertip structure without considering the complex sensor installation. On the other hand, this approach is no longer confined to adding components needed. It can fully use the soft robot body’s physical elasticity to convert sensor signals. Essentially, It treats the soft actuators as soft sensors.

Currently, rehabilitation medical care is expensive, requires a large number of rehabilitation therapist and which can only limit in the fixed location. In addition, there is a lack of research on the structure optimization and theoretical analysis of soft actuators for hand rehabilitation. In view of the problems above, this paper aims to propose a cheap, portable, wearable soft multiple joints rehabilitation glove.

First, this paper determined the hyperelastic constitutive model by material tensile test. Second, the soft actuator’s internal longitudinal section shape was optimized through the comparison of three diverse chamber structures. Meanwhile, the motion model of the soft actuator is established by the finite element model analysis method. Then, this paper established the constitutive model of the soft actuator according to the torque equilibrium equation and analyzed the relationship between the soft actuator’s bending angle and the input air pressure. This paper has verified that the theoretical model is correct through the soft actuator bending test. Finally, rehabilitation gloves were manufactured according to the model and the rehabilitation performance and grasping ability of gloves were verified through experiments.

The optimization results show that the internal semicircular cavity has better performance. Then, the actuator performance is better after adding the external arc structure and optimizing the physical dimension. The experimental results show that the trajectory of the actuator conforms to the mathematical model and rehabilitation gloves can meet the needs of rehabilitation treatment.

Rehabilitation gloves made of actuators can help patients with hand dysfunction in daily rehabilitation training. Then, it can also assist patients with some fine and complicated hand movements.

This paper proposes a new type of soft rehabilitation glove, which is composed of new soft actuators and adapting pieces. The new actuator is small enough to be fitted to the knuckle of the glove to move each joint of the finger.

The purpose of this study is to develop a novel approach to designing locally programmed multi-material distribution in a three-dimensional (3D) model, with the goal of producing a biomimetic robot that could mimic the locomotion of living organisms.

A voxelized representation is used to design the multi-material digital model and the material distribution in the model is optimized with the aims of mimicking the deflection dynamics of a real-life biological structure (i.e. inchworms) during its locomotion and achieving smooth deflection between adjacent regions. The design is validated post-fabrication by comparing the bending profiles of the printed robot with the deflection reference images of the real-life organism.

The proposed design framework in this study provides a foundation for multi-material multi-functional design for biomimicry and a wide range of applications in the manufacturing field and many other fields such as robotics and biomedical fields. The final optimized material design was 3D printed using a novel multi-material additive manufacturing method, magnetic field-assisted projection stereolithography. From the experimental tests, it was observed that the deflection curve and the deflection gradient of the printed robot within the adjacent regions of the body agreed well with the profiles taken from the real-life inchworm.

This paper presents a voxelized digital representation of the material distribution in printed parts, allowing spatially varied programming of material properties. The incorporation of reference images from living organisms into the design approach is a novel approach to transform image domain knowledge into the domain of engineering mechanical and material properties. Furthermore, the novel multi-material distribution design approach was validated through designing, 3D printing and prototyping an inchworm-inspired soft robot, which showed superior locomotion capability by mimicking the observed locomotion of the real inchworm.

The purpose of this paper is to introduce a variable distance pneumatic gripper with embedded flexible sensors, which can effectively grasp fragile and flexible objects.

Based on the motion principle of the three-jaw chuck and the pneumatic “fast pneumatic network” (FPN), a variable distance pneumatic holder embedded with a flexible sensor is designed. A structural design plan and preparation process of a soft driver is proposed, using carbon nanotubes as filler in a polyurethane (PU) sponge. A flexible bending sensor based on carbon nanotube materials was produced. A static model of the soft driver cavity was established, and a bending simulation was performed. Based on the designed variable distance soft pneumatic gripper, a real-time monitoring and control system was developed. Combined with the developed pneumatic control system, gripping experiments on objects of different shapes and easily deformable and fragile objects were conducted.

In this paper, a variable-distance pneumatic gripper embedded with a flexible sensor was designed, and a control system for real-time monitoring and multi-terminal input was developed. Combined with the developed pneumatic control system, a measure was carried out to measure the relationship between the bending angle, output force and air pressure of the soft driver. Flexible bending sensor performance test. The gripper diameter and gripping weight were tested, and the maximum gripping diameter was determined to be 182 mm, the maximum gripping weight was approximately 900 g and the average measurement error of the bending sensor was 5.91%. Objects of different shapes and easily deformable and fragile objects were tested.

Based on the motion principle of the three-jaw chuck and the pneumatic FPN, a variable distance pneumatic gripper with embedded flexible sensors is proposed by using the method of layered and step-by-step preparation. The authors studied the gripper structure design, simulation analysis, prototype preparation, control system construction and experimental testing. The results show that the designed flexible pneumatic gripper with variable distance can grasp common objects.

This paper aims to review the shape sensing techniques using large area flexible electronics (LAFE). Shape perception of humanoid robots using tactile data is mainly focused.

Research papers on different shape sensing methodologies of objects with large area, published in the past 15 years, are reviewed with emphasis on contact-based shape sensors. Fiber optics based shape sensing methodology is discussed for comparison purpose.

LAFE-based shape sensors of humanoid robots incorporating advanced computational data handling techniques such as neural networks and machine learning (ML) algorithms are observed to give results with best resolution in 3D shape reconstruction.

The literature review is limited to shape sensing application either two- or three-dimensional (3D) LAFE. Optical shape sensing is briefly discussed which is widely used for small area. Optical scanners provide the best 3D shape reconstruction in the noncontact-based shape sensing; here this paper focuses only on contact-based shape sensing.

Contact-based shape sensing using polymer nanocomposites is a very economical solution as compared to optical 3D scanners. Although optical 3D scanners can provide a high resolution and fast scan of the 3D shape of the object, they require line of sight and complex image reconstruction algorithms. Using LAFE larger objects can be scanned with ML and basic electronic circuitory, which reduces the price hugely.

LAFE can be used as a wearable sensor to monitor critical biological parameters. They can be used to detect shape of large body parts and aid in designing prosthetic devices. Tactile sensing in humanoid robots is accomplished by electronic skin of the robot which is a prime example of human–machine interface at workplace.

This paper reviews a unique feature of LAFE in shape sensing of large area objects. It provides insights from mechanical, electrical, hardware and software perspective in the sensor design. The most suitable approach for large object shape sensing using LAFE is also suggested.