In recent years, many researchers have aimed to construct robotic soft grippers that can handle fragile or unusually shaped objects without causing damage. This study proposes a smart textile-composite actuator and its application to a soft robotic gripper. An active fiber and an inactive fiber are combined together using knitting techniques to manufacture a textile actuator. The active fiber is a shape memory alloy (SMA) that is wire-wrapped with conventional fibers, and the inactive fiber is a knitting yarn. A knitted textile structure is flexible, with an excellent structure retention ability and high compliance, which is suitable for developing soft grippers. A driving source of the actuator is the SMA wire, which deforms under heating due to the shape memory effect. Through experiments, the course-to-wale ratio, the number of bundling SMA wires, and the driving current value needed to achieve the maximum deformation of the actuator were investigated. Three actuators were stitched together to make up each finger of the gripper, and layer placement research was completed to find the fingers’ suitable bending angle for object grasping. Finally, the gripping performance was evaluated through a test of grasping various object shapes, which demonstrated that the gripper could successfully lift flat/spherical/uniquely shaped objects.

Soft actuators that execute diverse motions have recently been proposed to improve the usability of soft robots. Nature-inspired actuators, in particular, are emerging as a means of accomplishing efficient motions based on the flexibility of natural creatures. In this research, we present an actuator capable of executing multi-degree-of-freedom motions that mimics the movement of an elephant’s trunk. Shape memory alloys (SMAs) that actively react to external stimuli were integrated into actuators constructed of soft polymers to imitate the flexible body and muscles of an elephant’s trunk. The amount of electrical current provided to each SMA was adjusted for each channel to achieve the curving motion of the elephant’s trunk, and the deformation characteristics were observed by varying the quantity of current supplied to each SMA. It was feasible to stably lift and lower a cup filled with water by using the operation of wrapping and lifting objects, as well as effectively performing the lifting task of surrounding household items of varying weights and forms. The designed actuator is a soft gripper that incorporates a flexible polymer and an SMA to imitate the flexible and efficient gripping action of an elephant trunk, and its fundamental technology is expected to be used as a safety-enhancing gripper that requires environmental adaptation.

As the use of drones grows, so too does the demand for physical protection against drone damage resulting from collisions and falls. In addition, as the flight environment becomes more complicated, a shock absorption system is required, in which the protective structure can be deformed based on the circumstances. Here, we present an origami- and kirigami-based structure that provides protection from various directions. This research adds a deformation capacity to existing fixed-shape guards; by using shape memory alloys, the diameter and height of the protective structure are controlled. We present three protective modes (1: large diameter/low height; 2: small diameter/large height; and 3: lotus shaped) that mitigate drone falls and side collisions. From the result of the drop impact test, mode 2 showed a 78.2% reduction in the maximum impact force at side impact. We incorporated kirigami patterns into the origami structures in order to investigate the aerodynamic effects of the hollow patterns. Airflow experiments yielded a macro understanding of flow-through behaviors on each kirigami pattern. In the wind speed experiment, the change in airflow velocity induced by the penetration of the kirigami pattern was measured, and in the force measurement experiment, the air force applied to the structure was determined.

Textiles composed of fibers can have their mechanical properties adjusted by changing the arrangement of the fibers, such as strength and flexibility. Particularly, in the case of smart textiles incorporating active materials, various deformations could be created based on fiber patterns that determine the directivity of active materials. In this study, we design a smart fiber-based textile actuator with a chain structure and evaluate its actuation characteristics. Smart fiber composed of shape memory alloy (SMA) generates deformation when the electric current is applied, causing the phase transformation of SMA. We fabricated the smart chain column and evaluated its actuating mechanism based on the size of the chain and the number of rows. In addition, a crochet textile actuator was designed using interlooping smart chains and developed into a soft gripper that can grab objects. With experimental verifications, this study provides an investigation of the relationship between the chain actuator’s deformation, actuating force, actuator temperature, and strain. The results of this study are expected to be relevant to textile applications, wearable devices, and other technical fields that require coordination with the human body. Additionally, it is expected that it can be utilized to configure a system capable of flexible operation by combining rigid elements such as batteries and sensors with textiles.

A Dielectric Elastomer Actuator (DEA) consists of electrodes with a dielectric layer between them. By controlling the design of the electrodes, voltage, and frequency, the operating range and speed of the DEA can be adjusted. These DEAs find applications in biomimetic robots, artificial muscles, and similar fields. When voltage is applied to the DEA, the dielectric layer undergoes compression and expansion due to electrostatic forces, which can lead to electrical breakdown. This phenomenon is closely related to the performance and lifespan of the DEA. To enhance stability and improve dielectric properties, a DEA Reservoir layer is introduced. Here, stability refers to the ability of the DEA to perform its functions even as the applied voltage increases. The Reservoir layer delays electrical breakdown and enhances stability due to its enhanced thickness. The proposed DEA in this paper is composed of a Reservoir layer and electrode layer. The Reservoir layer is placed between the electrode layers and is independently configured, not subjected to applied voltage like the electrode layers. The performance of the DEA was evaluated by varying the number of polymer layers in the Reservoir and electrode designs. Introducing the Reservoir layer improved the dielectric properties of the DEA and delayed electrical breakdown. Increasing the dielectric constant through the DEA Reservoir can enhance output characteristics in response to electrical signals. This approach can be utilized in various applications in wearable devices, artificial muscles, and other fields.

Knee osteoarthritis (OA), also known as degenerative arthritis, is a disease characterized by irreversible changes in the cartilage and bones comprising the joints, resulting in pain, impaired function, and deformity. Furthermore, independent of natural aging, the rate of change in joint cartilage has increased in recent years, which is mainly attributed to environmental factors. The rising incidence of knee-related disorders emphasizes the importance of analyzing the morphology and kinematics of knee structure. This study introduces a knee measurement system designed to replicate the motions of knee using 3D-printing technology, providing insights into knee mechanics with OA level. The research explores the stages of OA using the Kellgren–Lawrence (KL) grade scale, highlighting the variations in the force applied to the knee bone according to movement. The developed knee-simulation system, utilizing the four-bar-link theory, presents a novel approach to studying OA levels 0 to 4. As OA progresses, the cartilage deteriorates, affecting the movement of OA. The OA-based knee measurement system that incorporates soft tissues and skeletons can assist in developing a personalized diagnostic approach for knee disease. This will also help to enhance surgical effectiveness by facilitating the creation of personalized prosthetic joints for individual patients and offering a customized surgical simulation.