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.
Soft fluidic actuators consisting of elastomeric matrices with embedded flexible materials are of particular interest to the robotics community because they are affordable and can be easily customized to a given application. However, the significant potential of such actuators is currently limited as their design has typically been based on intuition. In this paper, the principle of operation of these actuators is comprehensively analyzed and described through experimentally validated quasi-static analytical and finite-element method models for bending in free space and force generation when in contact with an object. This study provides a set of systematic design rules to help the robotics community create soft actuators by understanding how these vary their outputs as a function of input pressure for a number of geometrical parameters. Additionally, the proposed analytical model is implemented in a controller demonstrating its ability to convert pressure information to bending angle in real time. Such an understanding of soft multimaterial actuators will allow future design concepts to be rapidly iterated and their performance predicted, thus enabling new and innovative applications that produce more complex motions to be explored.
This paper presents a portable, assistive, soft robotic glove designed to augment hand rehabilitation for individuals with functional grasp pathologies. The robotic glove utilizes soft actuators consisting of molded elastomeric chambers with fiber reinforcements that induce specific bending, twisting and extending trajectories under fluid pressurization. These soft actuators were mechanically programmed to match and support the range of motion of individual fingers. They demonstrated the ability to generate significant force when pressurized and exhibited low impedance when un-actuated. To operate the soft robotic glove, a control hardware system was designed and included fluidic pressure sensors in line with the hydraulic actuators and a closed-loop controller to regulate the pressure. Demonstrations with the complete system were performed to evaluate the ability of the soft robotic glove to carry out gross and precise functional grasping. Compared to existing devices, the soft robotic glove has the potential to increase user freedom and independence through its portable waist belt pack and open palm design.
Soft sensors comprising a flexible matrix with embedded circuit elements can undergo large deformations while maintaining adequate performance. These devices have attracted considerable interest for their ability to be integrated with the human body and have enabled the design of skin-like health monitoring devices, sensing suits, and soft active orthotics. Numerical tools are needed to facilitate the development and optimization of these systems. In this letter, we introduce a 3D finite element-based numerical tool to simultaneously characterize the mechanical and electrical response of fluid-embedded soft sensors of arbitrary shape, subjected to any loading. First, we quantitatively verified the numerical approach by comparing simulation and experimental results of a dog-bone shaped sensor subjected to uniaxial stretch and local compression. Then, we demonstrate the power of the numerical tool by examining a number of different loading conditions. We expect this work will open the door for further design of complex and optimal soft sensors.
This article describes the development of the Soft Robotics Toolkit, a set of open access resources to support the design, fabrication, modeling, characterization, and control of soft robotic devices. The ultimate aim of the toolkit is to support researchers in building upon each other's work, and thereby advance the field of soft robotics. An additional aim is to support educators and encourage students to pursue careers in engineering and science by making the resources as accessible as possible. The toolkit was developed and refined through a series of pilot studies and user tests. Specifically, the resources were used by students in a project-based medical device design course; volunteers from a variety of backgrounds tested the toolkit and provided feedback, and soft robotics researchers used the collection of resources and contributed to its development. Throughout all user studies, qualitative data were collected and used to guide improvements to the toolkit. This process of testing and refinement has resulted in a website containing design documentation describing general hardware control platforms and specific soft robotic component designs. The online documentation includes downloadable computer-aided design (CAD) files, detailed multimedia protocols for the fabrication of soft devices, tutorials and scripts for modeling and analyzing soft actuators and sensors, and source code for controlling soft devices. Successive iterations of qualitative data gathering and redesign have confirmed that the toolkit documentation is sufficiently detailed to be useful for researchers from a wide range of backgrounds. To date, the focus of the toolkit has primarily been fluid-actuated robotic systems, but the plan is to expand it to support a wider range of soft robotic-enabling technologies. The toolkit is intended as a community resource, and all researchers working in this field are invited to guide its future development by providing feedback and contributing new content.
Wearable robots based on soft materials will augment mobility and performance of the host without restricting natural kinematics. Such wearable robots will need soft sensors to monitor the movement of the wearer and robot outside the lab. Until now wearable soft sensors have not demonstrated significant mechanical robustness nor been systematically characterized for human motion studies of walking and running. Here, we present the design and systematic characterization of a soft sensing suit for monitoring hip, knee, and ankle sagittal plane joint angles. We used hyper-elastic strain sensors based on microchannels of liquid metal embedded within elastomer, but refined their design with the use of discretized stiffness gradients to improve mechanical durability. We found that these robust sensors could stretch up to 396% of their original lengths, would restrict the wearer by less than 0.17% of any given joint’s torque, had gauge factor sensitivities of greater than 2.2, and exhibited less than 2% change in electromechanical specifications through 1500 cycles of loading–unloading. We also evaluated the accuracy and variability of the soft sensing suit by comparing it with joint angle data obtained through optical motion capture. The sensing suit had root mean square (RMS) errors of less than 5° for a walking speed of 0.89 m/s and reached a maximum RMS error of 15° for a running speed of 2.7 m/s. Despite the deviation of absolute measure, the relative repeatability of the sensing suit’s joint angle measurements were statistically equivalent to that of optical motion capture at all speeds. We anticipate that wearable soft sensing will also have applications beyond wearable robotics, such as in medical diagnostics and in human–computer interaction.
A class of soft actuated materials that can achieve lifelike motion is presented. By embedding pneumatic actuators in a soft material inspired by a biological muscle fibril architecture, and developing a simple finite element simulation of the same, tunable biomimetic motion can be achieved with fully soft structures, exemplified here by an active left ventricle simulator.
Soft robots actuated by inflation of a pneumatic network (a “pneu-net”) of small channels in elastomeric materials are appealing for producing sophisticated motions with simple controls. Although current designs of pneu-nets achieve motion with large amplitudes, they do so relatively slowly (over seconds). This paper describes a new design for pneu-nets that reduces the amount of gas needed for inflation of the pneu-net, and thus increases its speed of actuation. A simple actuator can bend from a linear to a quasi-circular shape in 50 ms when pressurized at ΔP = 345 kPa. At high rates of pressurization, the path along which the actuator bends depends on this rate. When inflated fully, the chambers of this new design experience only one-tenth the change in volume of that required for the previous design. This small change in volume requires comparably low levels of strain in the material at maximum amplitudes of actuation, and commensurately low rates of fatigue and failure. This actuator can operate over a million cycles without significant degradation of performance. This design for soft robotic actuators combines high rates of actuation with high reliability of the actuator, and opens new areas of application for them.
Established design and fabrication guidelines exist for achieving a variety of motions with soft actuators such as bending, contraction, extension, and twisting. These guidelines typically involve multi-step molding of composite materials (elastomers, paper, fiber, etc.) along with specially designed geometry. In this paper we present the design and fabrication of a robust, fiber-reinforced soft bending actuator where its bend radius and bending axis can be mechanically-programed with a flexible, selectively-placed conformal covering that acts to mechanically constrain motion. Several soft actuators were fabricated and their displacement and force capabilities were measured experimentally and compared to demonstrate the utility of this approach. Finally, a prototype two-digit end-effector was designed and programmed with the conformal covering to shape match a rectangular object. We demonstrated improved gripping force compared to a pure bending actuator. We envision this approach enabling rapid customization of soft actuator function for grasping applications where the geometry of the task is known a priori.