Effect of Segment Types on Characterization of Soft Sensing Textile Actuators for Soft Wearable Robots

The use of textiles in soft robotics is gaining popularity because of the advantages textiles offer over other materials in terms of weight, conformability, and ease of manufacture. The purpose of this research is to examine the stitching process used to construct fabric-based pneumatic bending actuators as well as the effect of segment types on the actuators' properties when used in soft robotic glove applications. To impart bending motion to actuators, two techniques have been used: asymmetry between weave and weft knit fabric layers and mechanical anisotropy between these two textiles. The impacts of various segment types on the actuators' grip force and bending angle were investigated further. According to experiments, segmenting the actuator with a sewing technique increases the bending angle. It was discovered that actuators with high anisotropy differences in their fabric combinations have high gripping forces. Textile-based capacitive strain sensors are also added to selected segmented actuator types, which possess desirable properties such as increased grip force, increased bending angle, and reduced radial expansion. The sensors were used to demonstrate the controllability of a soft robotic glove using a closed-loop system. Finally, we demonstrated that actuators integrated into a soft wearable glove are capable of grasping a variety of items and performing various grasp types.

Automated summary

The use of textiles in soft robotics offers advantages in weight, conformability, and manufacturing. This research examines the stitching process and segment types for fabric-based pneumatic bending actuators in soft robotic glove applications. Experiments show that segmenting the actuator increases bending angle and high anisotropy differences result in higher gripping forces. The addition of textile-based capacitive strain sensors enhances grip force, bending angle, and controllability.