Many diseases, such as stroke, arthritis, and spinal cord injury, can cause severe hand impairment. Treatment options for these patients are limited by expensive hand rehabilitation devices and dull treatment procedures. In this study, we present an inexpensive soft robotic glove for hand rehabilitation in virtual reality (VR). Fifteen inertial measurement units are placed on the glove for finger motion tracking, and a motor—tendon actuation system is mounted onto the arm and exerts forces on fingertips via finger-anchoring points, providing force feedback to fingers so that the users can feel the force of a virtual object. A static threshold correction and complementary filter are used to calculate the finger attitude angles, hence computing the postures of five fingers simultaneously. Both static and dynamic tests are performed to validate the accuracy of the finger-motion-tracking algorithm. A field-oriented-control-based angular closed-loop torque control algorithm is adopted to control the force applied to the fingers. It is found that each motor can provide a maximum force of 3.14 N within the tested current limit. Finally, we present an application of the haptic glove in a Unity-based VR interface to provide the operator with haptic feedback while squeezing a soft virtual ball.

Soft and continuously controllable grippers can be assembled from fluidic prestressed composite (FPC) actuators. Due to their highly deformable features, it is difficult to model such actuators for large deflections. This article proposes a new method for modeling large deflections of FPC actuators called the chained composite model (CCM) to characterize the quasi-static response to an applied fluid pressure and load. The CCM divides an FPC actuator into discrete elements and models each element by a small rotation model. The strain energy of each element and the work done by pressure and loads are computed using third-order displacement polynomials with unknown coefficients; then, the total energy is minimized to calculate stable shapes using the Rayleigh–Ritz method. This study provides a set of systematic design rules to help the robotics community create FPC actuators by understanding how their responses vary as a function of input forces and pressures for a number of modeling and design parameters. Composite actuators are fabricated and a soft gripper is developed to demonstrate the grasping ability of the FPC actuators. Pneumatic pressure and end loads are applied to the composite actuators, and their responses are measured. The modeled responses of the actuators are shown to be in agreement with the measured responses.

Soft robotic gloves have attracted significant interest in hand rehabilitation in the past decade. However, current solutions are still heavy and lack finger-state monitoring and versatile treatment options. To address this, we present a lightweight soft robotic glove actuated by twisted string actuators (TSA) that provides whole-hand finger motion tracking. We have developed a virtual reality environment for hand rehabilitation training, allowing users to interact with various virtual objects. Fifteen small inertial measurement units are placed on the glove to predict finger joint angles and track whole-hand finger motion. We performed TSA experiments to identify design and control rules, by understanding how their response varies with input load and voltages. Grasping experiments were conducted to determine the grasping force and range of motion. Finally, we showcase an application of the rehabilitation glove in a Unity-based VR interface, which can actuate the operator’s fingers to grasp different virtual objects.

Continuous layer jamming is an effective tunable stiffness mechanism that utilizes vacuum to vary friction between laminates enclosed in a membrane. In this paper, we present a discrete layer jamming mechanism that is composed of a multilayered beam and multiple variable pressure clamps placed discretely along the beam; system stiffness can be varied by changing the pressure applied by the clamps. In comparison to continuous layer jamming, discrete layer jamming is simpler as it can be implemented with dynamic variable pressure actuators for faster control, better portability, and no sealing issues due to no need for an air supply. Design and experiments show that discrete layer jamming can be used for a variable stiffness co-robot arm. The concept is validated by quasi-static cantilever bending experiments. The measurements show that clamping 10% of the beam area with two clamps increases the bending stiffness by around 17 times when increasing the clamping pressure from 0 to 3 MPa. Computational case studies using finite element analysis for the five key parameters are presented, including clamp location, clamp width, number of laminates, friction coefficient, and number of clamps. Clamp location, number of clamps, and number of laminates are found to be most useful for optimizing a discrete layer jamming design. Actuation requirements for a variable pressure clamp are presented based on results from laminate beam compression tests.

Within the last decade, soft robotics has attracted an increasing attention from both academia and industry. Although multiple literature reviews of the whole soft robotics field have been conducted, there still appears to be a lack of systematic investigation of the intellectual structure and evolution of this field considering the increasing amount of publications. This paper conducts a scientometric review of the progressively synthesized network derived from 10,504 bibliographic records using a topic search on soft robotics from 2010 to 2021 based on the Web of Science (WoS) core database. The results are presented from both the general data analysis of included papers (e.g., relevant journals, citation, h-index, year, institution, country, disciplines) and the specific data analysis corresponding to main disciplines and topics, and more importantly, emerging trends. CiteSpace, a data visualization software, which can construct the co-citation network maps and provide citation bursts, is used to explore the intellectual structures and emerging trends of the soft robotics field. In addition, this paper offers a demonstration of an effective analytical method for evaluating enormous publication citation and co-citation data. Findings of this review can be used as a reference for future research in soft robotics and relevant topics.