Bioinspired soft robots for deep-sea exploration.

The deep ocean, Earth's untouched expanse, presents immense challenges for exploration due to its extreme pressure, temperature, and darkness. Unlike traditional marine robots that require specialized metallic vessels for protection, deep-sea species thrive without such cumbersome pressure-resistant designs. Their pressure-adaptive forms, unique propulsion methods, and advanced senses have inspired innovation in designing lightweight, compact soft machines. This perspective addresses challenges, recent strides, and design strategies for bioinspired deep-sea soft robots. Drawing from abyssal life, it explores the actuation, sensing, power, and pressure resilience of multifunctional deep-sea soft robots, offering game-changing solutions for profound exploration and operation in harsh conditions.

Desktop fabrication of monolithic soft robotic devices with embedded fluidic control circuits.

Most soft robots are pneumatically actuated and fabricated by molding and assembling processes that typically require many manual operations and limit complexity. Furthermore, complex control components (for example, electronic pumps and microcontrollers) must be added to achieve even simple functions. Desktop fused filament fabrication (FFF) three-dimensional printing provides an accessible alternative with less manual work and the capability of generating more complex structures. However, because of material and process limitations, FFF-printed soft robots often have a high effective stiffness and contain a large number of leaks, limiting their applications. We present an approach for the design and fabrication of soft, airtight pneumatic robotic devices using FFF to simultaneously print actuators with embedded fluidic control components. We demonstrated this approach by printing actuators an order of magnitude softer than those previously fabricated using FFF and capable of bending to form a complete circle. Similarly, we printed pneumatic valves that control a high-pressure airflow with low control pressure. Combining the actuators and valves, we demonstrated a monolithically printed electronics-free autonomous gripper. When connected to a constant supply of air pressure, the gripper autonomously detected and gripped an object and released the object when it detected a force due to the weight of the object acting perpendicular to the gripper. The entire fabrication process of the gripper required no posttreatment, postassembly, or repair of manufacturing defects, making this approach highly repeatable and accessible. Our proposed approach represents a step toward complex, customized robotic systems and components created at distributed fabricating facilities.

Variable Stiffness Devices Using Fiber Jamming for Application in Soft Robotics and Wearable Haptics.

Variable stiffness actuation has applications in a wide range of fields, including wearable haptics, soft robots, and minimally invasive surgical devices. There have been numerous design approaches to control and tune stiffness and rigidity; however, most have relatively low specific load-carrying capacities (especially for flexural loads) in the most rigid state that restricts their use in small or slender devices. In this article, we present an approach to the design of slender, high flexural stiffness modules based on the principle of fiber jamming. The proposed fiber jamming modules (FJMs) consist of axially packed fibers in an airtight envelope that transition from a flexible to a rigid beam when a vacuum is created inside the envelope. This FJM can provide the flexural stiffness of up to eight times that of a particle jamming module in the rigid state. Unlike layer jamming modules, the design of FJMs further allows them to control stiffness while bending in space. We present an analytical model to guide the parameter choices for the design of fiber jamming devices. Finally, we demonstrate applications of FJMs, including as a versatile tool, as part of a kinesthetic force feedback haptic glove and as a programmable structure.

Effect of post-curing light exposure time on the physico-mechanical properties and cytotoxicity of 3D-printed denture base material.

OBJECTIVE: This study investigated the effect of post curing light exposure time on the physico-mechanical properties and cytotoxicity of a 3D-printed PMMA-based denture material in comparison to a conventional heat-cured alternative as a control. METHODS: 3D-printed specimens were fabricated followed by post-curing for 0, 5, 10 or 20 min at 200 W and light wavelength range of 390-540 nm. Heat-cured specimens were fabricated using a standard protocol. Specimens were placed in artificial saliva at 37 â„ƒ for 48 h (immediate groups) and 6 months (aged group), then evaluated flexural strength/modulus, fracture toughness, microhardness, and degree of conversion. Water sorption and solubility was assessed after 28 days. Flexural strength, flexural modulus, and fracture toughness were tested through three-point bending tests, while the surface hardness was tested using Vickers's test. Fractured specimens were viewed by scanning electron microscope (SEM). Cytotoxicity in term of cell viability was evaluated using human oral fibroblasts. RESULTS: Flexural strength/modulus, fracture toughness and surface hardness significantly improved with the increase in light curing time up to 20 min. The same pattern of improvement was found with degree of conversion, water sorption, solubility, and cell viability. There was no significant difference (p < 0.01) between heat-cured material and 3D specimens post-cured for 20 min in term of flexural strength/modulus, surface hardness, and degree of conversion at the two-storage time points. SIGNIFICANCE: Generally, the physico-mechanical properties of the 3D-printed denture base material improve as post curing time increases up to 20 min which exhibited comparable performance as the conventional heat-cured control.

Electronic skins and machine learning for intelligent soft robots.

Soft robots have garnered interest for real-world applications because of their intrinsic safety embedded at the material level. These robots use deformable materials capable of shape and behavioral changes and allow conformable physical contact for manipulation. Yet, with the introduction of soft and stretchable materials to robotic systems comes a myriad of challenges for sensor integration, including multimodal sensing capable of stretching, embedment of high-resolution but large-area sensor arrays, and sensor fusion with an increasing volume of data. This Review explores the emerging confluence of e-skins and machine learning, with a focus on how roboticists can combine recent developments from the two fields to build autonomous, deployable soft robots, integrated with capabilities for informative touch and proprioception to stand up to the challenges of real-world environments.

Design Considerations for 3D Printed, Soft, Multimaterial Resistive Sensors for Soft Robotics.

Sensor design for soft robots is a challenging problem because of the wide range of design parameters (e.g., geometry, material, actuation type, etc.) critical to their function. While conventional rigid sensors work effectively for soft robotics in specific situations, sensors that are directly integrated into the bodies of soft robots could help improve both their exteroceptive and interoceptive capabilities. To address this challenge, we designed sensors that can be co-fabricated with soft robot bodies using commercial 3D printers, without additional modification. We describe an approach to the design and fabrication of compliant, resistive soft sensors using a Connex3 Objet350 multimaterial printer and investigated an analytical comparison to sensors of similar geometries. The sensors consist of layers of commercial photopolymers with varying conductivities. We characterized the conductivity of TangoPlus, TangoBlackPlus, VeroClear, and Support705 materials under various conditions and demonstrate applications in which we can take advantage of these embedded sensors.

Soft robot perception using embedded soft sensors and recurrent neural networks.

Recent work has begun to explore the design of biologically inspired soft robots composed of soft, stretchable materials for applications including the handling of delicate materials and safe interaction with humans. However, the solid-state sensors traditionally used in robotics are unable to capture the high-dimensional deformations of soft systems. Embedded soft resistive sensors have the potential to address this challenge. However, both the soft sensors-and the encasing dynamical system-often exhibit nonlinear time-variant behavior, which makes them difficult to model. In addition, the problems of sensor design, placement, and fabrication require a great deal of human input and previous knowledge. Drawing inspiration from the human perceptive system, we created a synthetic analog. Our synthetic system builds models using a redundant and unstructured sensor topology embedded in a soft actuator, a vision-based motion capture system for ground truth, and a general machine learning approach. This allows us to model an unknown soft actuated system. We demonstrate that the proposed approach is able to model the kinematics of a soft continuum actuator in real time while being robust to sensor nonlinearities and drift. In addition, we show how the same system can estimate the applied forces while interacting with external objects. The role of action in perception is also presented. This approach enables the development of force and deformation models for soft robotic systems, which can be useful for a variety of applications, including human-robot interaction, soft orthotics, and wearable robotics.

Scalable Manufacturing of Solderable and Stretchable Physiologic Sensing Systems.

Methods for microfabrication of solderable and stretchable sensing systems (S4s) and a scaled production of adhesive-integrated active S4s for health monitoring are presented. S4s' excellent solderability is achieved by the sputter-deposited nickel-vanadium and gold pad metal layers and copper interconnection. The donor substrate, which is modified with "PI islands" to become selectively adhesive for the S4s, allows the heterogeneous devices to be integrated with large-area adhesives for packaging. The feasibility for S4-based health monitoring is demonstrated by developing an S4 integrated with a strain gauge and an onboard optical indication circuit. Owing to S4s' compatibility with the standard printed circuit board assembly processes, a variety of commercially available surface mount chip components, such as the wafer level chip scale packages, chip resistors, and light-emitting diodes, can be reflow-soldered onto S4s without modifications, demonstrating the versatile and modular nature of S4s. Tegaderm-integrated S4 respiration sensors are tested for robustness for cyclic deformation, maximum stretchability, durability, and biocompatibility for multiday wear time. The results of the tests and demonstration of the respiration sensing indicate that the adhesive-integrated S4s can provide end users a way for unobtrusive health monitoring.