Soft Robotics

Advances in science and engineering often reveal the limitations of classical approaches initially used to understand, predict, and control phenomena. With progress, conceptual categories must often be re-evaluated to better track recently discovered invariants across disciplines. It is essential to refine frameworks and resolve conflicting boundaries between disciplines such that they better facilitate, not restrict, experimental approaches and capabilities. In this essay, we address specific questions and critiques which have arisen in response to our research program, which lies at the intersection of developmental biology, computer science, and robotics. In the context of biological machines and robots, we explore changes across concepts and previously distinct fields that are driven by recent advances in materials, information, and life sciences. Herein, each author provides their own perspective on the subject, framed by their own disciplinary training. We argue that as with computation, certain aspects of developmental biology and robotics are not tied to specific materials; rather, the consilience of these fields can help to shed light on issues of multiscale control, self-assembly, and relationships between form and function. We hope new fields can emerge as boundaries arising from technological limitations are overcome, furthering practical applications from regenerative medicine to useful synthetic living machines.

We present a compression sensor based on a strain-sensitive carbon black–silicone composite cast on top of a printed circuit board with interdigitated electrodes. This results in a very sensitive and soft capacitive compression sensor not requiring a structured dielectric or compliant electrodes. We show how the optimal loading of carbon black to maximize the sensitivity depends on the type of carbon black and the stiffness of the silicone matrix. The optimal quantity of carbon black leads to a high sensitivity of 252% for an input force of 10 N (this corresponds to an input pressure of 17 kPa), without stiffening the silicone matrix or increasing the viscoelastic losses noticeably. The fabrication process of the sensors is much simpler than that of other soft capacitive sensors, and unlike carbon black–silicone resistive sensors, these capacitive sensors do not exhibit time-dependent impedance creep. They can be made thick without affecting their base capacitance or sensitivity, leading to compliant and conformable sensing interfaces suitable for a variety of applications, such as robotic tactile sensors.

Soft robots aim to revolutionize how robotic systems interact with the environment thanks to their inherent compliance. Some of these systems are even able to modulate their physical softness. However, simply equipping a robot with softness will not generate intelligent behaviors. Indeed, most interaction tasks require careful specification of the compliance at the interaction point; some directions must be soft and others firm (e.g., while drawing, entering a hole, tracing a surface, assembling components). On the contrary, without careful planning, the preferential directions of deformation of a soft robot are not aligned with the task. With this work, we propose a strategy to prescribe variations of the physical stiffness and the robot's posture so to implement a desired Cartesian stiffness and location of the contact point. We validate the algorithm in simulation and with experiments. To perform the latter, we also present a new tendon-driven soft manipulator, equipped with variable-stiffness segments and proprioceptive sensing and capable to move in three dimensional. We show that, combining the intelligent hardware with the proposed algorithm, we can obtain the desired stiffness at the end-effector over the workspace.

The majority of sprawling-posture quadrupedal vertebrates, such as geckos and lizards, adopt a cyclical lateral swing pattern of their trunk that is coordinated with limb movements to provide extraordinary flexibility and mobility. Inspired by the gecko's locomotory gait and posture, a gecko-like robot with a flexible spine driven by shape memory alloy (SMA) springs was proposed in this work. The static parameters of the SMA spring were experimentally measured, and the flexible spine driven by SMA springs can be deflected bidirectionally. A kinematic model of the spine mechanism was established, and the mathematical relationship between the thermodynamic behavior of the SMA springs and spinal deflection was systematically analyzed. When a gecko trots with a lateral swing pattern of its trunk, the body and the spine show a standing wave shape and a single-peak C-type curve, respectively. The lateral spine deflection and trotting gait were combined in a collaborative model of a flexible spine and limbs to describe in detail the specific relationships between leg joint variables and spine deflection angle. Planar motion tests of a prototype robot were also conducted by using four high-speed cameras to record the trajectory of each point of the body, which verified the proposed model. From the acquired results, it was demonstrated that, compared with a rigid body, a robot with a flexible spine has a longer stride length, higher speed, and a greatly reduced turning radius.

In this study, we present a method to construct meter-scale deformable structures for underwater robotic applications by discretely assembling mechanical metamaterials. We address the challenge of scaling up nature-like deformable structures while remaining structurally efficient by combining rigid and compliant facets to form custom unit cells that assemble into lattices. The unit cells generate controlled local anisotropies that architect the global deformation of the robotic structure. The resulting flexibility allows better unsteady flow control that enables highly efficient propulsion and optimized force profile manipulations. We demonstrate the utility of this approach in two models. The first is a morphing beam snake-like robot that can generate thrust at specific anguilliform swimming parameters. The second is a morphing surface hydrofoil that, when compared with a rigid wing at the same angles of attack (AoAs), can increase the lift coefficient up to 0.6. In addition, in lower AoAs, the L ∕ D ratio improves by 5 times, whereas in higher angles it improves by 1.25 times. The resulting hydrodynamic performance demonstrates the potential to achieve accessible, scalable, and simple to design and assemble morphing structures for more efficient and effective future ocean exploration and exploitation.

Soft robots have received much attention due to their impressive capabilities including high flexibility and inherent safety features for humans or unstructured environments compared with hard-bodied robots. Soft actuators are the crucial components of soft robotic systems. Soft robots require dexterous soft actuators to provide the desired deformation for different soft robotic applications. Most of the existing soft actuators have only one or two deformation modes. In this article, a new soft pneumatic actuator (SPA) is proposed taking inspiration from Kirigami. Kirigami-inspired cuts are applied to the actuator design, which enables the SPA to be equipped with multiple deformation modes. The proposed Kirigami-inspired soft pneumatic actuator (KiriSPA) is capable of producing bending motion, stretching motion, contraction motion, combined motion of bending and stretching, and combined motion of bending and contraction. The KiriSPA can be directly manufactured using 3D printers based on the fused deposition modeling technology. Finite element method is used to analyze and predict the deformation modes of the KiriSPA. We also investigated the step response, creep, hysteresis, actuation speed, stroke, workspace, stiffness, power density, and blocked force of the KiriSPA. Moreover, we demonstrated that KiriSPAs can be combined to expand the capabilities of various soft robotic systems including the soft robotic gripper for delicate object manipulation, the soft planar robotic manipulator for picking objects in the confined environment, the quadrupedal soft crawling robot, and the soft robot with the flipping locomotion.

It is still challenging to achieve agility and trajectory control for untethered soft robots on an insect scale given their low mechanical impedance and compact structures. In this study, fast translational movements and swift turning motions are demonstrated on a power autonomous soft robot with a piezoelectric-thin-film-actuated body and electrostatic turning footpads. A high relative running speed of 2.5 body length per second compared with existing untethered robots is realized on a 24-mm-long untethered prototype integrated with power source, control, and wireless communication modules. An arc-shaped leg structure is adopted to self-regulate the frication forces on different footpads during turning by an inclination-induced redistribution of the payload gravity on legs and footpads. The trajectory maneuverability is demonstrated by navigating a 380 mg robot prototype with an 1810 mg payload to pass through a 58-cm-long S-shaped path with wireless control in 43.4 s. Due to the flexibility of the all-polymer body structure, the robustness of the untethered robot to large strain is demonstrated when compressed by 91 times the weight of the robot. A maximum travel distance of 58.6 m is achieved for the robot equipped with a 40 mA·h lithium battery, corresponding to the cost of transport of 261. This work provides a feasible solution to achieve high agility and advance the practicability of untethered soft robots on an insect scale.

Twisted string actuators (TSAs) have exhibited great promise in robotic applications by generating high translational force with low input torque. To further facilitate their robotic applications, it is strongly desirable but challenging to enhance their consistent strain generation while maintaining compliance. Existing studies predominantly considered overtwisting and coiling after the regular twisting stage to be undesirable—nonuniform and unpredictable knots, entanglements, and coils formed to create an unstable and failure-prone structure. Overtwisting would work well for TSAs when uniform coils can be consistently formed. In this study, we realize uniform and consistent coil formation in overtwisted TSAs, which greatly increases their strain. Furthermore, we investigate methods for enabling uniform coil formation upon overtwisting the strings in a TSA and present a procedure to systematically “train” the strings. To the authors' best knowledge, this is the first study to experimentally investigate overtwisting for TSAs with different stiffnesses and realize consistent uniform coil formation. Ultrahigh molecular-weight polyethylene strings form the stiff TSAs, whereas compliant TSAs are realized with stretchable and conductive supercoiled polymer strings. The strain, force, velocity, and torque of each overtwisted TSA were studied. Overtwisting and coiling resulted in ∼70% strain in stiff TSAs and ∼60% strain in compliant TSAs. This is more than twice the strain achieved through regular twisting. Finally, the overtwisted TSA was successfully demonstrated in a robotic bicep.

Smart materials such as magnetoactive elastomers (MAEs) combine elastic and magnetic properties that can be significantly changed in response to a magnetic field and therefore offer enormous potential for applications in both scientific research and engineering. When such an elastomer contains microsized hard magnetic particles, it can become an elastic magnet once magnetized in a strong magnetic field. This article studies a multipole MAE with the aim of utilizing it as an actuation element of vibration-driven locomotion robots. The elastomer beam has three magnetic poles overall with the same poles at the ends and possesses silicone bristles protruding from its underside. The quasi-static bending of the multipole elastomer in a uniform magnetic field is investigated experimentally. The theoretical model exploits the magnetic torque to describe the field-induced bending shapes. The unidirectional locomotion of the elastomeric bristle-bot is realized in two prototype designs using magnetic actuation of either an external or an integrated source of an alternating magnetic field. The motion principle is based on cyclic interplay of asymmetric friction and inertia forces caused by field-induced bending vibrations of the elastomer. The locomotion behavior of both prototypes shows a strong resonant dependency of the advancing speed on the frequency of applied magnetic actuation.

Recent advances in soft robotics demonstrate the requirement of modular actuation to enable the rapid replacement of actuators for maintenance and functionality extension. There remain challenges to designing soft actuators capable of different motions with a consistent appearance for simplifying fabrication and modular connection. Origami structures reshaping along with their unique creases became a powerful tool to provide compact constraint layers for soft pneumatic actuators. Inspired by Waterbomb and Kresling origami, this article presents three types of vacuum-driven soft actuators with a cubic shape and different origami skins, featuring contraction, bending, and twisting-contraction combined motions, respectively. In addition, these modular actuators with diversified motion patterns can be directly fabricated by molding silicone shell and constraint layers together. Actuators with different geometrical parameters are characterized to optimize the structure and maximize output properties after establishing a theoretical model to predict the deformation. Owing to the shape consistency, our actuators can be further modularized to achieve modular actuation via mortise and tenon-based structures, promoting the possibility and efficiency of module connection for versatile tasks. Eventually, several types of modular soft robots are created to achieve fragile object manipulation and locomotion in various environments to show their potential applications.

Electrostatic adhesion, as a promising actuation technique for soft robotics, severely suffers from the failure caused by the unpredictable electrical breakdown. This study proposes a novel self-clearing mechanism for electrostatic actuators, particularly for electrostatic adhesion. By simply employing an enough thin conductive layer (e.g., <7 μm for copper), this method can spontaneously clear the conductor around the breakdown sites effectively once breakdowns onset and survive the actuator shortly after the electrical damage. Compared with previous self-clearing methods, which typically rely on new specific materials, this mechanism is easy to operate and compatible with various materials and fabrication processes. In our tests, it can improve the maximum available voltage by 260% and the maximum electrostatic adhesive force by 276%. In addition, the robustness and repeatability of the self-clearing mechanism are validated by surviving consecutive breakdowns and self-clearing of 173 times during 65 min. This method is also demonstrated to be capable of recovering the electrostatic pad from severe physical damages such as punctures, penetrations, and cuttings successfully and enabling stable and reliable operation of the electrostatic clutch, or gripping, for example, even after the short-circuit takes place for hundreds of times. Therefore, the proposed self-clearing method sheds new light on high performance and more extensive practical applications of electrostatic actuators in the future.

Muscle driving is a critical actuation mode of soft or flexible robots and plays a key role in the motion of most animals. Although the system development of soft robots has been extensively investigated, the general kinematic modeling of soft bodies and the design methods used for muscle-driven soft robots (MDSRs) are inadequate. With a focus on homogeneous MDSRs, this article presents a framework for kinematic modeling and computational design. Based on continuum mechanics theory, the mechanical characteristics of soft bodies were first described using a deformation gradient tensor and energy density function. The discretized deformation was then depicted using a triangular meshing tool according to the piecewise linear hypothesis. Deformation models of MDSRs caused by external driving points or internal muscle units were established by the constitutive modeling of hyperelastic materials. The computational design of the MDSR was then addressed based on kinematic models and deformation analysis. Algorithms were proposed to infer the design parameters from the target deformation and to determine the optimal muscles. Several MDSRs were developed, and experiments were conducted to verify the effectiveness of the presented models and design algorithms. The computational and experimental results were compared and evaluated using a quantitative index. The presented framework of deformation modeling and computational design of MDSRs can facilitate the design of soft robots with complex deformations, such as humanoid faces.

Compared with rigid robots, soft robots are inherently compliant and have advantages in the tasks requiring flexibility and safety. But sensing the high dimensional body deformation of soft robots is a challenge. Encasing soft strain sensors into the internal body of soft robots is the most popular solution to address this challenge. But most of them usually suffer from problems like nonlinearity, hysteresis, and fabrication complexity. To endow the soft robots with body movement awareness, this work presents a bioinspired architecture by taking cues from human proprioception system. Differing from the popular usage of smart material-based sensors embedded in soft actuators, we created a synthetic analog to the human muscle system, using paralleled soft pneumatic chambers to serve as receptors for sensing body deformation. We proposed to build the system with redundant receptors and explored deep learning tools for generating the kinematic model. Based on the proposed methodology, we demonstrated the design of three degrees of freedom continuum joint and how its kinematic model was learned from the unified pressure information of the actuators and receptors. In addition, we investigated the response of the soft system to receptor failures and presented both hardware and software level solutions for achieving graceful degradation. This approach offers an alternative to enable soft robots with proprioception capability, which will be useful for closed-loop control and interaction with environment.

Current aerial robots demonstrate limited interaction capabilities in unstructured environments when compared with their biological counterparts. Some examples include their inability to tolerate collisions and to successfully land or perch on objects of unknown shapes, sizes, and texture. Efforts to include compliance have introduced designs that incorporate external mechanical impact protection at the cost of reduced agility and flight time due to the added weight. In this work, we propose and develop a lightweight, inflatable, soft-bodied aerial robot (SoBAR) that can pneumatically vary its body stiffness to achieve intrinsic collision resilience. Unlike the conventional rigid aerial robots, SoBAR successfully demonstrates its ability to repeatedly endure and recover from collisions in various directions, not only limited to in-plane ones. Furthermore, we exploit its capabilities to demonstrate perching where the three-dimensional collision resilience helps in improving the perching success rates. We also augment SoBAR with a novel hybrid fabric-based bistable (HFB) grasper that can utilize impact energies to perform contact-reactive grasping through rapid shape conforming abilities. We exhaustively study and offer insights into the collision resilience, impact absorption, and manipulation capabilities of SoBAR with the HFB grasper. Finally, we compare the performance of conventional aerial robots with the SoBAR through collision characterizations, grasping identifications, and experimental validations of collision resilience and perching in various scenarios and on differently shaped objects.

Soft actuators that operate with overpressure have been successfully implemented as soft robotic grippers. Naturally, as these pneumatic devices are prone to cuts, self-healing properties are attractive. Here, we prepared a gripper that operates based on the liquid-gas phase transition of ethanol within its hollow structure. The gripping surface of the device is coated with a self-healing polymer that heals with heat. This gripper also includes a stainless steel wire along the device that heats the entire structure through resistive heating. This design results in a soft robotic gripper that actuates and heals in parallel driven by the same practical stimulus, that is, electricity. Compared to other self-healing soft grippers, this approach has the advantage of being simple and having autonomous self-healing. However, there remain fundamental drawbacks that limit its implementation. The current work critically assesses this overpressure approach and concludes with a broad perspective regarding self-healing soft robotic grippers.