Continued technological progress in robotic systems has led to more applications where robots and humans operate in close proximity and even physical contact in some cases. Soft robots, which are made of highly compliant and deformable materials, provide inherent safety features unlike conventional robots that are made of stiff and rigid components. Soft robotics is a rapidly developing field exploiting biomimetic design principles, novel sensor and actuation concepts, and advanced manufacturing techniques. In this study, we propose novel 3D printable soft vacuum actuators that are inspired by the sporangium of fern trees. These actuators that are directly manufactured using commercial and affordable fused deposition modeling 3D printers offer many advantages such as high actuation speed (5.54 Hz), long lifetime (123,000 cycles), large payload to weight ratio (∼26), and significant output forces (∼16 N). The behavior of these actuators is accurately predicted, and their performance is optimized using finite element modeling. Furthermore, diverse robotic applications such as locomotion robots (a walking robot moving with an average forward speed of v = 3.54 cm/s, and a hopping robot called Gongaroo hopping with an average speed of v = 3.75 cm/s), grippers, and artificial muscles have been established and activated using the new soft actuation concept. Finally, to demonstrate the modularity of the proposed actuation concept, soft actuators with multiple degrees of freedom and variable length are established using a series of 3D printable vacuum hinges.

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Numerous soft grippers have been developed based on smart materials, pneumatic soft actuators, and underactuated compliant structures. In this article, we present a three-dimensional (3-D) printed omnipurpose soft gripper (OPSOG) that can grasp a wide variety of objects with different weights, sizes, shapes, textures, and stiffnesses. The soft gripper has a unique design that incorporates soft fingers and a suction cup that operate either separately or simultaneously to grasp specific objects. A bundle of 3-Dprintable linear soft vacuum actuators (LSOVA) that generate a linear stroke upon activation is employed to drive the tendon-driven soft fingers. The support, fingers, suction cup, and actuation unit of the gripper were printed using a low-cost and open-source fused deposition modeling 3-D printer. A single LSOVA has a blocked force of 30.35 N, a rise time of 94 ms, a bandwidth of 2.81 Hz, and a lifetime of 26 120 cycles. The blocked force and stroke of the actuators are accurately predicted using finite element and analytical models. The OPSOG can grasp at least 20 different objects. The gripper has a maximum payload-toweight ratio of 7.06, a grip force of 31.31 N, and a tip blocked force of 3.72 N.

Soft robots are ideal to interact safely alongside humans when compared to rigid‐bodied robots. These robots require robust soft sensors that can sustain large deformations. Novel soft pneumatic sensing chambers (SPSCs) that can be directly 3D printed using a low‐cost 3D printer and an off‐the‐shelf thermoplastic poly(urethane) (TPU) are presented. The SPSCs are responsive to four main mechanical input modalities of compression, bending, torsion, and rectilinear displacement, and all of these cause a pressure change in the SPSCs. The SPSCs have several advantages including fast response, linearity, negligible hysteresis, repeatability and reliability, stability over time, long lifetime, and very low power consumption. The SPSCs are optimized using finite element modeling (FEM) simulations to obtain a linear relationship between the input mechanical modalities and the output pressure. With the hyperelastic material model developed for the TPU, the FEM simulations accurately predict the experimental behavior. These SPSCs are generic and can be tailored to diverse soft and interactive human–machine interfaces including soft wearable gloves for virtual reality applications and soft adaptive grippers control, soft push buttons for science, technology, engineering, and mathematics (STEM) education platforms, haptic feedback devices for rehabilitation, soft game controllers and soft throttle controllers for gaming, and soft bending sensors for soft prosthetic hands.

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Highly sensitive, flexible sensors that can be manufactured with minimum environmental footprint and be seamlessly integrated into wearable devices are required for realtime tracking of complex human movement, gestures, and health conditions. This study reports on how biodegradation can be used to enhance the sensitivity and electromechanical performance of piezoresistive sensors. Poly(glycerol sebacate) (PGS) elastomeric porous sensor was synthesized and blended with multiwall carbon nanotubes (MWCNTs) and sodium chloride (NaCl). Because of their unique porous characteristics, a single linear behavior over a large range of pressures (≤8 kPa) and an increase in their sensitivity from 0.12 ± 0.03 kPa −1 up to 8.00 ± 0.20 kPa −1 was achieved after 8 weeks in a simulated body fluid media. They can detect very low pressures (100 Pa), with negligible hysteresis, reliability, long lifetime (>200 000 cycles), short response time (≤20 ms), and high force sensitivity (≤4 mN). The characteristics of the developed foam sensors match the sensing characteristics of the human finger to pave the way toward low-footprint wearable devices for applications including human movement and condition monitoring, recreation, health and wellness, virtual reality, and tissue engineering.

The modeling of soft structures, actuators, and sensors is challenging, primarily due to the high nonlinearities involved in such soft robotic systems. Finite element modeling (FEM) is an effective technique to represent soft and deformable robotic systems containing geometric nonlinearities due to large mechanical deformations, material nonlinearities due to the inherent nonlinear behavior of the materials (i.e., stress-strain behavior) involved in such systems, and contact nonlinearities due to the surfaces that come into contact upon deformation. Prior to the fabrication of such soft robotic systems, FEM can be used to predict their behavior efficiently and accurately under various inputs and optimize their performance and topology to meet certain design and performance requirements. In this article, we present the implementation of FEM in the design process of directly three-dimensional (3D) printed pneumatic soft actuators and sensors to accurately predict their behavior and optimize their performance and topology. We present numerical and experimental results to show that this approach is very effective to rapidly and efficiently design the soft actuators and sensors to meet certain design requirements and to save time, modeling, design, and fabrication resources.

Soft robots require seamless integration with sensors and actuators that are simple to manufacture at scale with low cost and minimum footprint. The sensor materials must be highly reliable, sensitive, and stable, and their mechanical features should match the sensing requirements of soft robots such as minimal response time and nonlinearity of hysteresis and relaxation. A resistive-type sensor based on the synthesis of poly(glycerol secabate) (PGS) with a foam-like structure and outstanding mechanical, electrical, and electromechanical properties is developed. These foam sensors present high sensitivity (gauge factor ≈ −9), very fast response (≤3 ms), negligible hysteresis, reliability, long lifetime (>1 200 000 cycles), and a pressure differential sensitivity of 34 Pa. They can accurately detect low and high frequency vibrations (up to 300 Hz) and small forces (200 mN) that cover the very low detection range of metallic strain gauges and the very large detection range of elastomeric strain sensors. These characteristics closely match those of the human fingertip, and hence pave the way toward tactile and compliant sensing elements embedded in prosthetic hands. Prospective applications for unexplored resistive-type sensors to meet the sensory requirements of soft robotic systems are demonstrated.