There is much interest in form-fitting, low-modulus, implantable devices or soft robots that can mimic or assist in complex biological functions such as the contraction of heart muscle. We present a soft robotic sleeve that is implanted around the heart and actively compresses and twists to act as a cardiac ventricular assist device. The sleeve does not contact blood, obviating the need for anticoagulation therapy or blood thinners, and reduces complications with current ventricular assist devices, such as clotting and infection. Our approach used a biologically inspired design to orient individual contracting elements or actuators in a layered helical and circumferential fashion, mimicking the orientation of the outer two muscle layers of the mammalian heart. The resulting implantable soft robot mimicked the form and function of the native heart, with a stiffness value of the same order of magnitude as that of the heart tissue. We demonstrated feasibility of this soft sleeve device for supporting heart function in a porcine model of acute heart failure. The soft robotic sleeve can be customized to patient-specific needs and may have the potential to act as a bridge to transplant for patients with heart failure.
Soft actuators are the components responsible for producing motion in soft robots. Although soft actuators have allowed for a variety of innovative applications, there is a need for design tools that can help to efficiently and systematically design actuators for particular functions. Mathematical modeling of soft actuators is an area that is still in its infancy but has the potential to provide quantitative insights into the response of the actuators. These insights can be used to guide actuator design, thus accelerating the design process. Here, we study fluid-powered fiber-reinforced actuators, because these have previously been shown to be capable of producing a wide range of motions. We present a design strategy that takes a kinematic trajectory as its input and uses analytical modeling based on nonlinear elasticity and optimization to identify the optimal design parameters for an actuator that will follow this trajectory upon pressurization. We experimentally verify our modeling approach, and finally we demonstrate how the strategy works, by designing actuators that replicate the motion of the index finger and thumb.
Soft bending actuators are inherently compliant, compact, and lightweight. They are preferable candidates over rigid actuators for robotic applications ranging from physical human interaction to delicate object manipulation. However, characterizing and predicting their behaviors are challenging due to the material nonlinearities and the complex motions they can produce. This paper investigates a soft bending actuator design that uses a single air chamber and fiber reinforcements. Additionally, the actuator design incorporates a sensing layer to enable real-time bending angle measurement for analysis and control. In order to study the bending and force exertion characteristics when interacting with the environment, a quasistatic analytical model is developed based on the bending moments generated from the applied internal pressure and stretches of the soft materials. Comparatively, a finite-element method model is created for the same actuator design. Both the analytical model and the finite-element model are used in the fiber reinforcement analysis and the validation experiments with fabricated actuators. The experimental results demonstrate that the analytical model captures the relationships of supplied air pressure, actuator bending angle, and interaction force at the actuator tip. Moreover, it is shown that an off-the-shelf bend angle sensor integrated to the actuator in this study could provide real-time force estimation, thus eliminating the need for a force sensor.
This paper presents further developments, characterization and initial evaluation of a recently developed assistive soft robotic glove for individuals with hand pathologies. The glove technology utilizes a combination of elastomeric and inextensible materials to create soft actuators that conform to the user's hand and can generate sufficient hand closing force to assist with activities of daily living. User intent (i.e. desire to close or open hand) is detected by monitoring gross muscle activation signals with surface electromyography electrodes mounted on the user's forearm. In particular, we present an open-loop sEMG logic that distinguishes muscle contractions and feeds the information to a low-level fluidic pressure controller that regulates pressure in pre-selected groups of the glove's actuators. Experiments are conducted to determine the level of assistance provided by the glove by monitoring muscle effort and mapping the pressure distribution during a simple grasping task when the glove is worn. Lastly, quantitative and qualitative results are presented using the sEMG-controlled glove on a healthy participant and on a patient with muscular dystrophy.
In this work we investigate the influence of fiber angle on the deformation of fiber-reinforced soft fluidic actuators and examine the manner in which these actuators extend axially, expand radially and twist about their axis as a function of input pressure. We study the quantitative relationship between fiber angle and actuator deformation by performing finite element simulations for actuators with a range of different fiber angles, and we verify the simulation results by experimentally characterizing the actuators. By combining actuator segments in series, we can achieve combinations of motions tailored to specific tasks. We demonstrate this by using the results of simulations of separate actuators to design a segmented wormlike soft robot capable of propelling itself through a tube and performing an orientation-specific peg insertion task at the end of the tube. Understanding the relationship between fiber angle and pressurization response of these soft fluidic actuators enables rapid exploration of the design space, opening the door to the iteration of exciting soft robot concepts such as flexible and compliant endoscopes, pipe inspection devices, and assembly line robots.
This paper presents advancements in the design of a portable, soft robotic glove for individuals with functional grasp pathologies. The robotic glove leverages soft material actuator technology to safely distribute forces along the length of the finger and provide active flexion and passive extension. These actuators consist of molded elastomeric bladders with anisotropic fiber reinforcements that produce specific bending, twisting, and extending trajectories upon fluid pressurization. In particular, we present a method for customizing a soft actuator to a wearer's biomechanics and demonstrate in a motion capture system that the ranges of motion (ROM) of the two are nearly equivalent. The active ROM of the glove is further evaluated using the Kapandji test. Lastly, in a case study, we present preliminary results of a patient with very weak hand strength performing a timed Box-and-Block test with and without the soft robotic glove.
We report a new method for fabricating textile integrable capacitive soft strain sensors based on multicore–shell fiber printing. The fiber sensors consist of four concentric, alternating layers of conductor and dielectric, respectively. These wearable sensors provide accurate and hysteresis-free strain measurements under both static and dynamic conditions.