Performance quantification of strain sensors for flexible manipulators

<div>The development of soft materials for various smart applications, such as in</div><div>soft robotic devices derived from elastomers, naturally occurring rubbers and polymers,</div><div>can be traced back to 1940s. Contrary to conventional robotics, soft robotic research</div><div>was primarily dedicated to reproducing and mimicking the elasticity and compliance of</div><div>biological substrates. In the last few decades, however, subsequent progress in soft</div><div>robotic devices and manipulators has been witnessed within the subcategories of</div><div>material & processing, sensor and actuators. In this chapter, a comprehensive</div><div>introduction to soft robotics engineering is highlighted exclusively from the perspective</div><div>of materials development. Soft material prototypes are eventually exploited towards</div><div>designing biomimetic prosthetic devices with sensing capabilities and soft actuating</div><div>bodies. We present an elaborate discussion on soft materials engineering, including</div><div>elastomers, polymer composites containing fillers and associated processing</div><div>methodologies. Despite high flexibility and inherent biocompatibility, conventional</div><div>soft elastomer-based (silicone and polyurethane) matrices often suffer from either poor</div><div>mechanical strength or reduced mechanical output at higher temperatures. This review</div><div>briefly summarizes and critically discusses the different types of compliant materials,</div><div>i.e. elastomers, fluids, gels and others, which are currently being employed in soft</div><div>robotics. This chapter also highlights new opportunities and paves some potential</div><div>avenues to address several challenges, particularly the ones concerning and soft robotic</div><div>materials. Moreover, utilization of soft rubber for sensors and other applications could</div><div>ameliorate the versatility of soft material applications. Therefore, challenges and future</div><div>direction in soft robotics research have to be explicitly integrated within the subdomain</div><div>of materials development and processing and, therefore, addressed in-depth in this</div><div>chapter, with an emphasis on autonomous soft robotic arms capable of stimuliresponsive</div><div>operations.</div>

Emerging classes of soft robotics with flexible actuation, intelligent sensibility, and biomimetic functionality are driving significant advances in academic researches and commercial applications. Such new generation robotics relies heavily on important breakthroughs in soft matter engineering and flexible actuation systems. Unlike conventional rigid robots, soft robots generally have unique sporting styles and manufacturing strategies. Recently, a series of newly developed soft materials—gallium‐based liquid metals (LMs) are found to display dramatical roles in making soft machines and robotics with their unusual properties in soft robotic actuation and self‐driven field. With superior merits of both high stretchability and electroconductivity over conventional soft materials, LM is increasingly innovated as flexible sensors and actuators in constructing intelligent soft robots. Typical advances in LM enabled soft machines and robotics are summarized and interpreted, herein, with special focus on the driving principles of the LM objects, the preparation methods of LM flexible electronics for making soft robots, and the applications of LM in biomedicines and intelligent robots, together with the consideration of key challenges facing LM‐based soft robotics and its future prospects.

Soft robotics is a fast growing field of engineering where there are significant opportunities to realize new forms of actuation and sensing. However, there is also a challenge to translate some of the lab-based developments into a robust industrial manufacturing process. Linked to this is also the opportunity to create new forms of functionality in soft robotic devices by employing a flexible, digital manufacturing process for their creation. Overcoming these hurdles, and unlocking the possibilities for greater functionality, is likely to be a key enabler for wider applications and adoption of soft robotics in practical applications. We present a system of computer-controlled Aerosol Jet Printing that will enable complex soft robotic structures to be manufactured. The process is demonstrated through the deposition of a carbon-based conductive ink on to elastomeric substrates for high resolution, conformal and multilayer patterning. Functional demonstrators, in the form of a dielectric elastomer actuator and strain sensor, are produced to showcase the potential of the technique.

Vertebrate animals benefit from a combination of rigidity for structural support and softness for adaptation. Similarly, integrating rigidity and softness can enhance the versatility of soft robotics. However, the challenges associated with creating durable bonding interfaces between soft and rigid materials have limited the development of hybrid robots. Existing solutions require specialized machinery, such as polyjet 3D printers, which are not commonly available. In response to these challenges, we have developed a 3D printing technique that can be used with almost all commercially available FDM printers. This technique leverages the common issue of underextrusion to create a strong bond between soft and rigid materials. Underextrusion generates a porous structure, similar to fibrous connective tissues, that provides a robust interface with the rigid part through layer fusion, while the porosity enables interlocking with the soft material. Our experiments demonstrated that this method outperforms conventional adhesives commonly used in soft robotics, achieving nearly 200% of the bonding strength in both lap shear and peeling tests. Additionally, we investigated how different porosity levels affect bonding strength. We tested the technique under pressure scenarios critical to soft and hybrid robots and achieved three times more pressure than the current adhesion solution. Finally, we fabricated various hybrid robots using this technique to demonstrate the wide range of capabilities this approach and hybridity can bring to soft robotics.

Soft robots made from soft materials can safely interact with humans and environments compared with the traditional rigid robots. However, the inherent compliance of the soft robots makes them difficult to realize the jumping motion. Although many soft robots can jump through the design of bistable structure. However, the existing soft robots need rigid spine to be embedded in the soft body. Therefore, it is still hard for the jumping of a soft robot with pure soft body. This paper offers the design method for the pure soft bistable robot with jumping ability. The critical buckling force and total elastic potential energy of the robot can be increased by designing the soft body with different thickness. We use the twisted artificial muscle (TAM) to realize the jumping motion of the soft bistable robot. The proposed robot can jump at a height nearly two times its body height. We envision that the design method will promote the application of the soft robot with pure soft body to realize more types of motion strategy.

Conventional robots are constructed with rigid parts and materials, restricting their ability to deform freely and adapt to the external environment. Performing tasks such as handling delicate materials and navigating narrow pathways is challenging for these typical robots made of stiff materials. However, there is a growing demand for such functions in various industries. Recent advances in soft robotics have garnered considerable attention as solutions to these challenges. Soft robotic systems in various forms present a systematic solution for performing unique tasks. The goal of soft robotics research is to develop advanced technologies, incorporating innovative robotic mechanisms based on soft materials and structures to enhance adaptability. Soft robots find broad applications in diverse fields, including industry, healthcare, and field exploration. Soft component technology plays a crucial role in configuring soft robots. Soft actuators introduce new types of motion and operation mechanisms, while soft sensors measure the deformation of the actuators with a tiny stiffness change. These advancements in soft actuators and sensors encourage researchers to explore new robotic designs and applications. Additionally, the component technology enables the integration of soft and typical robots into hybrid B Youngsu Cha

<p>Soft robots have become important members of the robot community with many potential applications owing to their unique flexibility and security embedded at the material level. An increasing number of researchers are interested in their designing, manufacturing, modeling, and control. However, the dynamic simulation of soft robots is difficult owing to their infinite degrees of freedom and nonlinear characteristics that are associated with soft materials and flexible geometric structures. In this study, a novel multi-flexible body dynamic modeling and simulation technique is introduced for soft robots. Various actuators for soft robots are modeled in a virtual environment, including soft cable-driven, spring actuation, and pneumatic driving. A pneumatic driving simulation was demonstrated by the bending modules with different materials. A cable-driven soft robot arm prototype and a cylindrical soft module actuated by shape memory alley springs inspired by an octopus were manufactured and used to validate the simulation model, and the experimental results demonstrated adequate accuracy. The proposed technique can be widely applied for the modeling and dynamic simulation of other soft robots, including hybrid actuated robots and rigid-flexible coupling robots. This study also provides a fundamental framework for simulating soft mobile robots and soft manipulators in contact with the environment.</p> <p> </p>

SummaryA design and manufacturing method is described for creating a motor tendon–actuated soft foam robot. The method uses a castable, light, and easily compressible open-cell polyurethane foam, producing a structure capable of large (~70% strain) deformations while requiring low torques to operate (<0.2 N·m). The soft robot can change shape, by compressing and folding, allowing for complex locomotion with only two actuators. Achievable motions include forward locomotion at 13 mm/s (4.3% of body length per second), turning at 9◦/s, and end-over-end flipping. Hard components, such as motors, are loosely sutured into cavities after molding. This reduces unwanted stiffening of the soft body. This work is the first demonstration of a soft open-cell foam robot locomoting with motor tendon actuators. The manufacturing method is rapid (~30 min per mold), inexpensive (under $3 per robot for the structural foam), and flexible, and will allow a variety of soft foam robotic devices to be produced.

Dielectric elastomer actuators (DEA) have gained increased attention in the design of electrically driven soft and lightweight robotic devices. They rely on Coulomb forces for their actuation and are able to undergo large displacements as a function of the applied electrical field. Fabricating DEAs with additive manufacturing opens the way to a personalized and cost‐efficient fabrication of soft active devices. In particular, extrusion‐based techniques provide a versatile strategy to multi‐material 3D print DEAs by using electrically conductive and soft filaments with high elongation. One key aspect of DEAs is the electrode's performance, which has to provide a high electrical conductivity and a good adhesion to the sandwiched membrane. Herein, selected 3D printing parameters were varied to optimize the electrode infill density and electrode infill direction. Mechanical and electrical properties, as well as actuation performance, of fully 3D‐printed DEA demonstrators were studied comprehensively. With the optimized parameter set, a maximum DEA displacement of 91% was achieved with respect to the free length of the actuator. This is comparable to the performance of non‐3D‐printed DEAs and demonstrates the potential of 3D printing for the production of DEAs undergoing large deformations while leveraging the design and manufacturing freedom of multi‐material 3D printing.

In intelligent manufacturing and robotic technology, various sensors must be integrated with equipment. In addition to traditional sensors, stretchable sensors are particularly attractive for applications in robotics and wearable devices. In this study, a piezoresistive stretchable strain sensor based on laser-induced graphene (LIG) was proposed and developed. A three-dimensional, porous LIG structure fabricated from polyimide (PI) film using laser scanning was used as the sensing layer of the strain sensor. Two LIG pattern structures (parallel and vertical) were fabricated and integrated within the LIG strain sensors. Scanning electron microscopy, an X-ray energy dispersive spectrometer, and Raman scattering spectroscopy were used to examine the microstructure of the LIG sensing layer. The performance and strain sensing properties of the parallel and vertical stretchable LIG strain sensors were investigated in tensile tests. The relative resistance changes and the gauge factors of the parallel and vertical LIG strain sensors were quantified. The parallel strain sensor achieved a high gauge factor of 15.79 in the applied strain range of 10% to 20%. It also had high sensitivity, excellent repeatability, good durability, and fast response times during the tensile experiments. The developed LIG strain sensor can be used for the real-time monitoring of human motions such like finger bending, wrist bending, and throat swallowing.

A systematic trend analysis of 3D printing techniques used in specific soft robotic elements

Living organisms intertwine soft (e.g., muscle) and hard (e.g., bones) materials, giving them an intrinsic flexibility and resiliency often lacking in conventional rigid robots. The emerging field of soft robotics seeks to harness these same properties to create resilient machines. The nature of soft materials, however, presents considerable challenges to aspects of design, construction, and control—and up until now, the vast majority of gaits for soft robots have been hand-designed through empirical trial-and-error. This article describes an easy-to-assemble tensegrity-based soft robot capable of highly dynamic locomotive gaits and demonstrating structural and behavioral resilience in the face of physical damage. Enabling this is the use of a machine learning algorithm able to discover effective gaits with a minimal number of physical trials. These results lend further credence to soft-robotic approaches that seek to harness the interaction of complex material dynamics to generate a wealth of dynamical behaviors.

Stretchable conductive materials have attracted great attention due to their potential applications as strain sensors, wearable electronics, soft robotics, and medical devices. The fabrication of these materials with customized object geometries is desirable, but the methods to achieve them are still highly limited. Additive manufacturing via vat photopolymerization can generate sophisticated object geometries, but there is still a significant need to print with materials that afford improved conductivity, mechanical properties, elastic recovery, and durability. Herein, stretchable strain sensors with a range of 3D printed designs are reported using vat photopolymerization. Ionic liquid resins are optimized for their printability using Sudan‐I as a photoabsorber and used to fabricate 3D objects that are subjected to compression, stretching, and bending loads that are detected as real‐time changes in current. Additionally, the self‐adhesive nature of these materials enables mechanically damaged structures to be mended together to regain its function as a strain sensor. These ionic liquid resins are compatible with commercial 3D printers, which enhances their applicability for on‐demand production of customized devices.

Stretchability and sensitivity are essential properties of wearable electronics for effective motion monitoring. In general, increasing the sensitivity of strain sensors based on ionic conductors trades off elasticity, which results in low sensitivity of the strain sensors at large mechanical deformations. To address this, ion‐permeable conducting polymer electrodes with low contact resistance are utilized in ionic gel‐based strain sensors. Using a rectangular‐shaped ionic gel and ion‐permeable electrodes significantly increase the gauge factor of the strain sensor, similar to the theoretical value at a given strain. To further increase the sensitivity of the strain sensor, the ionic gel is patterned with zigzagged tracks that gap apart as the gel stretches, and the gaps close as the gel contracts, leading to a large variation in the relative resistance upon stretching. By combining the zigzagged ionic gel and the ion‐permeable electrodes, highly sensitive stretchable sensors are realized with a record‐high gauge factor of 173, compared to existing ionic conductor‐based stretchable strain sensors. The zigzag‐patterned ionic sensor can successfully monitor various motions when attached to the human body. These results are expected to afford promising strategies for developing highly sensitive, stretchable sensing systems for E‐skin sensors and soft robotics.

This study presents a novel rolled self-sensing artificial muscle that integrates shape memory alloy actuators and interdigitated capacitive sensors within a monolithic polydimethylsiloxane matrix. An innovative 3D printing-based fabrication process is introduced for the co-design of actuator and sensor, allowing for the measurement of deformation during actuation. Experimental tests demonstrate the high signal stability and repeatability of the sensors, with gauge factor up to 0.76 and hysteresis lower than 0.013 pF. The actuators achieve peak forces of 12 N, approximately 100 times their self-weight, and displacements of 2.5 mm, corresponding to 3% strain. Actuation time ranges between 85–90 s and is primarily dependent on thermal effects. The dynamic characterization of the self-sensing artificial muscle incorporates both electromechanical and thermal effects, with a temperature compensation term introduced to correct for temperature-induced capacitance variations during actuation. As a proof of concept, a soft robot is developed, realized with three rolled self-sensing artificial muscles arranged in a parallel configuration. A kinematic model is derived to describe the relationship between the measured displacements of the artificial muscles in the actuation space and the three degrees of freedom pose (roll, pitch, and vertical displacement) in the workspace. The findings highlight the effectiveness of the proposed design and fabrication approach for achieving compact, integrated actuation and sensing in a soft robotic device. The proposed rolled, self-sensing artificial muscle is fabricated by integrating shape-memory alloy actuators and interdigitated capacitive sensors within a monolithic polydimethylsiloxane matrix. To validate the design and fabrication process, a 3-DOF soft robot is constructed that uses three self-sensing actuators arranged in a parallel configuration. • A novel rolled self-sensing artificial muscle is proposed which is realized by integrating shape memory alloy actuators and interdigitated capacitive sensors within a monolithic polydimethylsiloxane matrix. • A novel dynamic characterization of the self-sensing actuator incorporates both electromechanical and thermal effects, with a temperature compensation term introduced to correct for temperature-induced capacitance variations during actuation. • A proof of concept of a soft robot, actuated by three rolled self-sensing artificial muscles arranged in a parallel configuration, validates the proposed design and fabrication.