Keywords: Soft Sensors and Actuators, Soft Robot Applications
Abstract: McKibben artificial muscles are used in many musculoskeletal robots because they have characteristics similar to those of natural skeletal muscles in terms of the contraction ratio and force generated. However, they differ from natural skeletal muscles in that they cannot perform passive elongation movements (referred to as “back-stretching” in this study), in which the muscle is stretched by an external force from its natural length while deactivated. Therefore, when using McKibben artificial muscles for antagonist muscle drives, it is necessary to use artificial muscles that are longer than the linear distance between the origin and insertion point of the muscle (causing them to sag while deactivated). However, when acting as an agonist muscle, such an artificial muscle does not fully utilize its contractile capacity and reduces the range of motion of the joint. This is different from natural skeletal muscles, which are placed along the bone without sagging under the skin. In this study, we proposed a back-stretchable McKibben muscle that contracts like a conventional McKibben artificial muscle when air pressure is applied and back-stretches like a natural skeletal muscle with no applied pressure. In addition, we developed a design method based on a mechanical model. In comparative experiments on a robotic arm, we achieved a 1.22-fold increase in the antagonist muscle driving range compared with conventional McKibben artificial muscles without causing the muscles to sag significantly.

Keywords: Soft Sensors and Actuators, Soft Robot Applications, Soft Robot Materials and Design
Abstract: Wirelessly actuated miniature soft robots actuated by magnetic fields that can overcome gravity by climbing soft and wet tissues are promising for accessing challenging enclosed and confined spaces with minimal invasion for targeted medical operation. However, existing designs lack the directional steerability to traverse complex terrains and perform agile medical operations. Here we propose a rod-shaped millimeter-size climbing robot that can be omnidirectionally steered with a steering angle up to 360 degrees during climbing beyond existing soft miniature robots. The design innovation includes the rod-shaped robot body, its special magnetization profile, and the spherical robot footpads, allowing directional bending of the body under external magnetic fields and out-of-plane motion of the body for delivery of medical patches. With further integrated bio-adhesives and microstructures on the footpads, we experimentally demonstrated inverted climbing of the robot on porcine gastrointestinal (GI) tract tissues and deployment of a medical patch for targeted drug delivery.

Keywords: Soft Sensors and Actuators, Soft Robot Applications, Modeling, Control, and Learning for Soft Robots
Abstract: A soft inflatable actuator composed of low shore hardness elastomer with thin chamber walls will exhibit high nonlinearity and hysteresis in its motion. The nonlinearity is in the relation between pressure and volume which contains some unstable working zones where there is no one-to-one mapping. Hysteresis causes the actuator to follow different trajectories between the loading (inflating) and unloading (deflating) motions. This makes precise control of its position difficult. To cope with the nonlinearity, we design an adaptive super-twisting controller and account for the uncertain relation between volume and pressure in the control design by fitting a nonlinear function. To address hysteresis, we propose a method to force the tip of the actuator to converge to any reference position on the global deflating path. This method helps to eliminate the uncertainty in the position of the actuator's tip. The controller presented moves the actuator to the desired position in the shortest time with minimal chattering in the control actions. This control method has good performance which is demonstrated through empirical results.

Keywords: Soft Robot Applications, Micro/Nano Robots, Soft Robot Materials and Design
Abstract: As the field of soft robotics matures, we find an increasing need for improved energy sources. Untethered soft robots have primarily used batteries for electric power and micropumps or cannisters of compressed gas for pneumatic energy. Hydrocarbons present an energy dense and power dense option, but untethered centimeter-scale cyclic soft combustion, similar in concept to an internal combustion engine, is not yet available. As a step toward untethered soft microengines, we present a soft Microfluidic Air-intake and eXhaust (MAX) valve to regulate gas flow in future untethered soft robots. We present a valve and explore the design rules behind key geometry which governs gas flow rates, pressures, and the blocking of flow. The MAX valve is designed to 1. regulate the flow of air into a combustion chamber, 2. regulate exhaust flow from the chamber, and 3. block flow during combustion.

Keywords: Soft Sensors and Actuators, Soft Robot Applications
Abstract: The compliance of soft robots offers benefits in handling disturbances and contact dynamics in real-world environments. A common actuation method for soft robotics is pneumatics, but this often requires tethering to cumbersome air and power supplies. While there are existing options for portable pneumatic systems, they are limited in dynamic capabilities, constraining their applicability to low pressure and/or small-volume soft robots. In this work, we propose a pressure supply and regulator for use in untethered, weight-constrained, dynamic soft robot applications. It leverages high-flow proportional valves, an integrated pressure reservoir, and Venturi vacuum generation to achieve portability and dynamic performance. We present a set of models that describe the system dynamics, experimentally validate them on physical hardware, and discuss the influence of design parameters on system operation. Lastly, we integrate a proof-of-concept prototype with a soft robot arm mounted on an aerial vehicle to demonstrate the system's applicability to mobile robotics. Our system enables new opportunities in mobile soft robotics by making untethered pneumatic supply and regulation available to a wider range of soft robots.

Keywords: Compliant Joint/Mechanism, Tendon/Wire Mechanism, Legged Robots
Abstract: Handling complex terrains is often problematic for miniature mobile robots due to their small size and low weight. Soft robots can utilize their compliance to overcome obstacles in the terrain, but their performances decline for tasks that require load-bearing capabilities. In this study, we present a miniature modular robot with tendon-driven variable stiffness backbones and investigate the effectiveness of the rigid and soft configurations for climbing obstacles and crossing gaps. The mechanism utilizes the design of a 3D-printed soft backbone with a layered structure that becomes rigid under compression applied by the linear actuator in the modules. In rigid mode, the robot can climb a 20mm step obstacle and cross a 105mm gap. In contrast, the soft mode obstacle height threshold jumps to 30mm, and the length of the gap that the robot can cross decreases to 55mm, showing that backbone stiffness modulation allows better adaptability for complex terrains.

Keywords: Soft Robot Applications, Modeling, Control, and Learning for Soft Robots
Abstract: Inspired by the octopus and other animals living in water, soft robots should naturally lend themselves to underwater operations, as supported by encouraging validations in deep water scenarios. This work deals with equipping soft arms with the intelligence necessary to move precisely in wave-dominated environments, such as shallow waters where marine renewable devices are located. This scenario is substantially more challenging than calm deep water since, at low operational depths, hydrodynamic wave disturbances can represent a significant impediment. We propose a control strategy based on Nonlinear Model Predictive Control that can account for wave disturbances explicitly, optimising control actions by considering an estimate of oncoming hydrodynamic loads. The proposed strategy is validated through a set of tasks covering set-point regulation, trajectory tracking and mechanical failure compensation, all under a broad range of varying significant wave heights and peak spectral periods. The proposed control methodology displays positional error reductions as large as 84% with respect to a baseline controller, proving the effectiveness of the method. These initial findings present a first step in the development and deployment of soft manipulators for performing tasks in hazardous water environments.

Keywords: Modeling, Control, and Learning for Soft Robots, Soft Robot Applications, Optimization and Optimal Control
Abstract: Modeling and control of soft robotic systems remains a challenging and active field of research, especially for robots actuated with shape-memory-alloys (SMA). Difficulties in controlling SMA-actuated robots arise in modeling the nonlinearities of the SMA dynamics as well as accounting for their hysteresis behavior. This article helps address these challenges by using sensorization of the end effector along with SMA actuators combined with a simplified two-axis pendulum model to implement an optimal control scheme on a soft digit. The control stack presented uses a direct collocation method (DIRCOL) for initial trajectory optimization, with the actual state of the soft digit then captured and used to refine the system inputs using Iterative Learning Control (ILC) to increase trajectory tracking accuracy. The system is demonstrated on hardware, achieving very close trajectory tracking performance for two-dimensional motion tasks.

Keywords: Biologically-Inspired Robots, Soft Robot Materials and Design, Soft Sensors and Actuators
Abstract: Climbing up the slopes and scaling the obstacles are challenging tasks for miniature robots. By taking inspiration from nature, this paper investigates the use of a tail, like a lizard to aid the climbing capabilities of our miniature robot. We present the design of an active soft tail controlled by the force feedback from a 3D-printed, custom, soft force sensor. This paper also investigates the benefit of using an active tail controlled by force to climb slopes and obstacles. Increasing the slope that the miniature robot attempts to scale increases the need for the force applied by the tail to avoid the pitch-back movement of the robot. We can observe a positive correlation between the force applied by the tail and the slope of the surface. The experiments were conducted until the maximum degree of incline of slope that the robot could climb without any adhesive feet, i.e., 20 degrees. Additionally, this paper proves that the tail also improves the tail obstacle scaling capability of the robot. The maximum heights of the obstacle that the robot scales with and without the tail are 19 mm and 9 mm respectively

Keywords: Soft Robot Applications, Legged Robots, Compliant Joint/Mechanism
Abstract: Compared with the conventional rigid-link-based robots, walking robots with soft legs have the advantages of high environmental adaptability and safety, which can greatly enhance the performance of locomotion robots when exploring unknown regions. In order to further explore the design potential for soft walking robots, we propose in this paper a novel quadruped walking robot called Toqro, in which an improved design of topology optimized soft leg is introduced to achieve flexible walking motions. To simplify the kinematic analysis, the realized soft robotic leg is modeled as a two-linkage structure with two rotating degree-of-freedoms (DOFs). Each leg of the robot is actuated by two servo motors and different actuation inputs are also designed to realize forward, backward, left-turn and right-turn motion patterns. In addition, the robot has integrated micro-controller, signal receiver and other electronic components to enable remote control. Experimental results show that the realized robot can successfully achieve flexible straight-line and turning motions, which verifies the feasibility of topology optimized soft legs for creating walking robots.

Keywords: Soft Sensors and Actuators, Soft Robot Materials and Design, Modeling, Control, and Learning for Soft Robots
Abstract: In this paper, we introduce a novel open-source toolbox for design optimization in Soft Robotics. We consider that design optimization is an important trend in Soft Robotics that is changing the way in which designs will be shared and adopted. We evaluate this toolbox on the example of a cable-driven, sensorized soft finger. For devices like these, which feature both actuation and sensing, the need for multi-objective optimization capabilities naturally arises, because at the very least, a trade-off between these two aspects has to be found. Thus, multi-objective optimization capability is one of the central features of the proposed toolbox. We evaluate the optimization of the soft finger and show that extreme points of the optimization trade-off between sensing and actuation are indeed far apart on actually fabricated devices for the established metrics. Furthermore, we provide an in depth analysis of the sim-to-real behavior of the example, taking into account factors such as the mesh density in the simulation, mechanical parameters and fabrication tolerances.

Keywords: Soft Robot Applications, Soft Robot Materials and Design, Cellular and Modular Robots
Abstract: Diverse space infrastructure is required for exploration missions to the Moon, Mars, and beyond. However, the cost of sending materials into space is high. One approach to ease this cost is the use of adaptive infrastructure, which may leverage discrete building blocks that can be assembled, disassembled, and reassembled into diverse mechanical structures based on the relevant environment and task demands. Indeed, the NASA Automated Reconfigurable Mission Adaptive System (ARMADAS) project is taking this approach. The discrete building component selected by ARMADAS engineers is a cuboctahedron, or more simply a "voxel," as a volumetric pixel. The voxels are lightweight and simple, and assemble into programmable mechanical metamaterial structures with high stiffness and stability. However, transportation of complete voxels remains volume-inefficient, and fabrication of voxels in-situ adds notable complexity to the system. Herein, we introduce a cuboctahedron voxel design that compresses to 35% of its deployed volume during transport and passively locks in its expanded state at its destination, where a multitude of voxels can then be assembled. Inspired by the Hoberman sphere, the voxel is designed to deploy using a 1D force input. We further confirm that the new deployable voxel is compatible with existing ARMADAS assembly agents.

Keywords: Soft Robot Applications, Grasping
Abstract: Aerial robots have garnered significant attention due to their potential applications in various industries, such as inspection, search and rescue, and drone delivery. Successful missions often depend on the ability of these robots to grasp and land effectively. This paper presents a novel modular soft gripper design tailored explicitly for aerial grasping and landing operations. The proposed modular pneumatic soft gripper incorporates a feed-forward proportional controller to regulate pressure, enabling compliant gripping capabilities. The modular connectors of the soft fingers offer two configurations for the 4-tip soft gripper, H-base (cylindrical) and X-base (spherical), allowing adaptability to different target objects. Additionally, the gripper can serve as a soft landing gear when deflated, eliminating the need for an extra landing gear. This design reduces weight, simplifies aerial manipulation control, and enhances flight efficiency. We demonstrate the efficacy of indoor aerial grasping and achieve a maximum payload of 217 g using the proposed soft aerial vehicle and its H-base pneumatic soft gripper (808 g).

Keywords: Soft Robot Materials and Design, Soft Sensors and Actuators, Hydraulic/Pneumatic Actuators
Abstract: One of the major challenges in the design and construction of soft-rigid hybrid systems is having robust bonding at soft-rigid interfaces. Soft robots tend to be compliant and adaptive but weak, while rigid robots tend to be strong and precise but uncompromising. Soft-rigid hybrid systems can provide a blend of both compliant interactions with environments as well as fast and precise body position controls. In this paper, we propose a fabrication strategy using flocking to achieve strong bonding between soft and rigid parts. Flocking is a fabrication method that bonds short fibers to fabrics or plastics. The fibers create a fuzzy surface texture on rigid components, which increases the surface area. In the context of soft robotic molding, flocked surface texture increases mechanical bonding between soft and rigid components and enables incorporation of rigid components with increased complexity or challenging placement that could be overmolded but not glued. In this paper, we investigate design parameters for flocking such as substrate materials, adhesives, and flocking materials; we recommend design and fabrication guidelines for the use of flocking to incorporate printed ABS and PLA components in silicone. To demonstrate the utility of flocking in a range of soft systems, we have fabricated several example soft systems with integrated components, including a pneumatic network (pneu-net) actuator, soft chambers connected to semi-rigid tubing, and a sensorized soft actuator. The performance of these demonstrations was comparable or exceeded that of silicone glues and allows for direct overmolding of complex structures, making flocking applicable and versatile in soft-rigid hybrid systems.

Keywords: Biologically-Inspired Robots, Legged Robots, Tendon/Wire Mechanism
Abstract: Soft crawling robots can potentially access locations that are unreachable by humans and traditional rigid robots, playing a crucial role in conducting missions like environmental monitoring or search and rescue. Due to their flexible body structures, soft robots can adapt to uncertain environments and operate safely in contact with humans. We present a new design for a caterpillar-inspired soft robot in the form of a series of 3D printed flexible tendon-driven bending segments with individual motor control. A constant-curvature quasi-static kinematic model of the robot locomotion is developed, and we describe periodic gait inputs that coordinate bending in multiple segments to lift the legs and move forward in a traveling-wave motion. We present simulations and experimental results for locomotion in a straight line, along with experimental demonstration of a modified segment design with an additional degree of freedom for steering navigation.

Keywords: Soft Sensors and Actuators, Soft Robot Materials and Design, Force and Tactile Sensing
Abstract: We present a soft gelatin-based hydrogel e-skin capable of detecting up to six simultaneous tactile stimuli, using electrical impedance tomography (EIT) measurements and convolutional neural networks. Our networks are trained on only real-world data, for which we present two custom data-collecting end-effectors. These allow multi-touch responses to be measured quickly and autonomously (up to 8 seconds per datapoint), giving datasets more than 10x larger than those existing in the literature. To demonstrate the benefits of this approach, we train a non-homogeneous skin to predict `macro-braille' patterns in a 3x2 grid, achieving a 89 percent classification accuracy.

Keywords: Optimization and Optimal Control, Modeling, Control, and Learning for Soft Robots
Abstract: This paper presents a method for optimal motion planning of soft continuum robots. The method employs Bernstein surfaces to approximate the system's kinematics and impose complex constraints, including collision avoidance. The main contribution is the approximation of infinite-dimensional continuous problems into their discrete counterparts, facilitating their solution using standard optimization solvers. This discretization leverages the unique properties of Bernstein surface, providing a framework that extends previous works which focused on ODEs approximated by Bernstein polynomials. Numerical validations are conducted through several numerical scenarios. The presented methodology offers a promising direction for solving complex optimal control problems in the realm of soft robotics.

Keywords: Soft Robot Applications, Soft Robot Materials and Design, Hydraulic/Pneumatic Actuators
Abstract: Sediment sampling is a prevalent approach for exploring and understanding the ocean and its change over time. Unfortunately, the sampling process can be very costly due to the logistics that involve the transportation and deployment of the Remotely Operative Vehicle (ROV), specifically designed for this task. In a collaboration of marine scientists and engineers, this work focuses on developing a lightweight, modular and cost efficient actuation system for deep-sea suction-sampling. We propose a binary actuation system to manipulate the sampling tube directly instead of the tube being guided by a traditional manipulator. The core of the actuation system are bistable actuators that combine origami-inspired soft actuators with a bistable mechanism to form a lightweight but still robust system. This concept aims to lower the cost of deep-sea sediment sampling by offering the option to replace the currently used hydraulic titanium manipulator, that is traditionally used for deep-sea research.

Keywords: Grippers and Other End-Effectors, Force and Tactile Sensing, Deep Learning in Robotics and Automation
Abstract: With the growing interest in vision-based tactile sensor technology for applications such as fruit harvesting based on ripeness, accurate object softness recognition has become increasingly important. In our study, we examined the capability of soft biomimetic optical tactile sensor, a TacTip with a flat sensing surface, for this task. By systematically pressing the TacTip against hardness-controlled silicone samples, we linked sequential TacTip tactile images of patterns of markers with the known Shore 00 hardness values of the samples. Trained on 1323 data points, the multichannel 2D CNN showed good accuracy across the entire Shore 00 hardness range. Yet, its performance diminished for hardness values above 70 during online tests. We interpret these differences in performance as due to the relative softness differential between the sensor's skin and the silicone samples.

Keywords: Medical Robots and Systems, Surgical Robotics: Steerable Catheters/Needles, Soft Sensors and Actuators
Abstract: Flexible robotic endoscopy has the potential to reduce invasiveness and improve patient outcomes in ventricular neurosurgeries. Many promising technologies exist for navigating and interacting within such highly critical and constrained spaces as the brain. With objective assessment of surgical device safety and capabilities, a standardised method of evaluation could accelerate development. We present a soft-sensorised testbed of a 1:1 scale lateral ventricle, capable of simulating procedures and measuring distributed contact forces as low as 5 mN and up to 1 N. The testbed can provide surgical device evaluation on flexible robotic demonstrators with known capabilities. For example, analytical observations from sensor data highlight tradeoffs between inherent safety from device compliance and safety from device controllability. We also demonstrate that contact feedback can improve users' manual control, with a reduction in maximum unwanted contact forces of at least 20%. With improvements to the realism of the testbed and customisation of sensor distribution for specific surgical procedures, there is potential for utility beyond robotic design and control evaluation and towards surgeon training or even pre-operative planning.

Keywords: Soft Sensors and Actuators, Force and Tactile Sensing
Abstract: This paper aims to present an innovative and cost-effective design for Acoustic Soft Tactile (AST) Skin, with the primary goal of significantly enhancing the accuracy of 2-D tactile feature estimation. The existing challenge lies in achieving precise tactile feature estimation, especially concerning contact geometry characteristics, using cost-effective solutions. We hypothesise that by harnessing acoustic energy through dedicated acoustic channels in 2 layers beneath the sensing surface and analysing amplitude modulation, we can effectively decode interactions on the sensory surface, thereby improving tactile feature estimation. Our approach involves the distinct separation of hardware components responsible for emitting and receiving acoustic signals, resulting in a modular and highly customisable skin design. Practical tests demonstrate the effectiveness of this novel design, achieving remarkable precision in estimating contact normal forces (MAE<0.8 N), 2D contact localisation (MAE<0.7 mm), and contact surface diameter (MAE<0.3 mm). In conclusion, the AST skin, with its innovative design and modular architecture, successfully addresses the challenge of tactile feature estimation. The presented results showcase its ability to precisely estimate various tactile features, making it a practical and cost-effective solution for robotic applications.

Keywords: Soft Sensors and Actuators, Compliant Joint/Mechanism, Soft Robot Materials and Design
Abstract: In this work, we present two embedded soft optical waveguide sensors designed for real-time onboard configuration sensing in soft actuators for robotic locomotion. Extending the contributions of our collaborators who employed external camera systems to monitor the gaits of twisted-beam structures, we strategically integrate our OptiGap sensor system into these structures to monitor their dynamic behavior. The system is validated through machine learning models that correlate sensor data with camera-based motion tracking, achieving high accuracy in predicting forward or reverse gaits and validating its capability for real-time sensing. Our second sensor, consisting of a square cross-section fiber pre-twisted to 360 degrees, is designed to detect the chirality of reconfigurable twisted beams. Experimental results confirm the sensor's effectiveness in capturing variations in light transmittance corresponding to twist angle, serving as a reliable chirality sensor. The successful integration of these sensors not only improves the adaptability of soft robotic systems but also opens avenues for advanced control algorithms.

Keywords: Soft Robot Materials and Design, Wearable Robots, Prosthetics and Exoskeletons
Abstract: Movement disorders reduce muscle strength and mobility, and while therapeutic interventions aim to maintain mobility, many individuals with impairments are unable to function independently. Soft wearable robots (exosuits) are envisioned to provide long-term daily physical assistance to the mobility impaired, however, there is still no such commercial device widely available. A main challenge is the design, fabrica- tion, and mounting of soft actuators to the human body. Here, we describe a canonical design framework for the development of soft, modular, and reconfigurable pneumatically driven soft actuators manufactured using textiles. Through the use of an innovative 3D-printed self-sealing end-cap, our method provides a simple and effective way for uniting and hermetically sealing actuators constructed through a layered fabrication process, where a (mechanically programmable) textile sleeve surrounds an internal bladder. To mount the actuators to the body, we have developed a semi-rigid interface consisting of modular segments that fasten together to form cylindrical units that can be mounted to the limb and include snap-in fasteners to attach actuators. The human-robot interfaces act to secure the actuators to the body and to optimize and distribute mechanical power transfer over a large area. Taken together, our proposed modular architecture allows the actuators and their attachment points to be easily modified so that an exosuit for the knee, elbow, or other joints, can be realized with the same set of hardware. We demonstrated our proposed design on a realistic human leg mannequin and our results verify its ability to provide substantial force to the body.

Keywords: Modeling, Control, and Learning for Soft Robots, Optimization and Optimal Control
Abstract: Incorporating both flexible and rigid components in robot designs offers a unique solution to the limitations of traditional rigid robotics by enabling both compliance and strength. This paper explores the challenges and solutions for controlling soft-rigid hybrid robots, particularly addressing the issue of self-contact. Conventional control methods prioritize precise state tracking, inadvertently increasing the system's overall stiffness, which is not always desirable in interactions with the environment or within the robot itself. To address this, we investigate the application of Control Barrier Functions (CBFs) and High Order CBFs to manage self-contact scenarios in serially connected soft-rigid hybrid robots. Through an analysis based on Piecewise Constant Curvature (PCC) kinematics, we establish CBFs within a classical control framework for self-contact dynamics. Our methodology is rigorously evaluated in both simulation environments and physical hardware systems. The findings demonstrate that our proposed control strategy effectively regulates self-contact in soft-rigid hybrid robotic systems, marking a significant advancement in the field of robotics.

Keywords: Soft Robot Materials and Design, Hydraulic/Pneumatic Actuators, Soft Robot Applications
Abstract: Fibre-reinforced soft robots are often considered in the design of fluid elastomer actuators, to counter ballooning and potential bursting when exposed to high levels of pressure. They also enhance deformation and navigation through confined spaces. These attributes are critical in applications such as minimally invasive surgical (MIS) procedures that use sub-12 mm diameter trocar ports. While soft robots with fully reinforced actuation chambers have not yet attained this level of miniaturisation, this paper outlines the fabrication and characterisation of miniaturised soft manipulators with reinforced actuation chambers on the sub-centimetre scale (i.e., less than 10 mm). Two robots are presented with diameters of 9.5 mm and 7.8 mm. They have four pneumatic actuation chambers per robotic segment, with a free central working lumen. Additionally, two robotic segments are serially connected to enhance dexterity and flexibility. This research advances the miniaturisation of soft manipulators with reinforced chambers and an inner free lumen, enhancing their use in applications within confined and unstructured environments.

Keywords: Biologically-Inspired Robots, Modeling, Control, and Learning for Soft Robots, Soft Sensors and Actuators
Abstract: Nature-inspired robotic manipulators are an active research area because of their efficient multi-functional integration. Of these mechanisms, the tendon-driven human finger is capable of sophisticated manipulation tasks but is challenging to implement as a robotic design. A key challenge is managing tendons for force transmission from muscle to fingertip within the limited space of the hand. Another challenge is controlling in underactuated tendon-driven systems. Sensor feedback is usually the answer, but an increase in sensor systems adds bulk, which is the opposite direction to develop for a dexterous design. Therefore in this article, a novel design of a human index finger-inspired robotic finger is presented. The finger is composed of three major parts that make up the functionality of the finger motion and detection. First, a rigid resin material for the bone structure. Second, a soft rubber resin for sheaths that guide tendons and set each joint's angular range. Third, the soft optical tendons that transmit force and sense the total joint angle of the finger through the light intensity. The correlation of the force and joint angle from the soft optical tendons measurements is further analyzed by neural network. Evaluation of the sensor reliability is demonstrated through image acquisition. The data shows that the maximum RSME of training and testing session are 2.36(deg) and 5.69(deg) respectively.

Keywords: Prosthetics and Exoskeletons, Wearable Robots, Hydraulic/Pneumatic Actuators
Abstract: Exoskeletons provide excellent assistance and rehabilitation to people with mobility difficulties including ageing people, stroke survivors and people suffering from frailty and sarcopenia. However, comfortable wearing and easy donning and doffing of exoskeletons remain the major challenges. Standard exoskeleton anchoring methods, such as tight braces and Velcro straps, have drawbacks including long attachment time and discomfort, causing skin irritation and muscle soreness. A soft fabric shrink-to-fit pneumatic sleeve was previously developed, introducing comfortable and active anchoring for upper limb assistance. This study further develops the mathematical model deriving the shrink-to-fit size range and the maximum pulling resistance based on selected design parameters of an anchoring module and its applied pressure. The study also investigates various limb shapes of human body and explores four different designs of soft anchoring units by assessing their anchoring performance, where high pulling resistance at low body compression is preferred. It was found that rectangular units work well for smooth cylindrical-shaped limbs, conical units perform well with conical-shaped limbs, multiple-row pouch designs are best for concave limbs, and Kirigami designs are ideal for expanding limbs due to their inherent stretchability. Additionally, a prototype combining multiple anchoring designs for an upper limb was developed.

Keywords: Soft Robot Materials and Design, Additive Manufacturing, Education Robotics
Abstract: Existing fluidic soft logic gates for controlling soft robots typically depend on labor-intensive manual fabrication or costly printing methods. In our research, we utilize Fused Deposition Modeling to create fully 3D-printed fluidic logic gates, fabricating a valve from thermoplastic polyurethane. We investigate the 3D printing of tubing and introduce a novel extrusion nozzle for tubing production. Our approach significantly reduces the production time for soft fluidic valves from 27 hours using replica molding to 3 hours with FDM printing. We apply our 3D-printed valve to develop optimized XOR gates and D-latch circuits, presenting a rapid and cost-effective fabrication method for fluidic logic gates that aims to make fluidic circuitry more accessible to the soft robotics community.

Keywords: Multifingered Hands, Soft Robot Applications, Tendon/Wire Mechanism
Abstract: The functional replication and actuation of com- plex structures inspired by nature is a longstanding goal for humanity. Creating such complex structures combining soft and rigid features and actuating them with artificial muscles would further our understanding of natural kinematic structures. We printed a biomimetic hand in a single print process comprised of a rigid skeleton, soft joint capsules, tendons, and printed touch sensors. We showed it’s actuation using electric motors. In this work, we expand on this work by adding a forearm that is also closely modeled after the human anatomy and replacing the hand’s motors with 22 independently controlled pneumatic artificial muscles (PAMs). Our thin, high-strain (up to 30.1%) PAMs match the performance of state-of-the-art artificial muscles at a lower cost. The system showcases humanlike dexterity with independent finger movements, demonstrating successful grasping of various objects, ranging from a small, lightweight coin to a large can of 272g in weight. The performance evaluation, based on fingertip and grasping forces along with finger joint range of motion, highlights the system’s potential.

Keywords: Soft Robot Materials and Design, Additive Manufacturing, Soft Robot Applications
Abstract: Soft robots promise groundbreaking advancements across various industries. However, soft robots are susceptible to wear, fatigue, and material degradation. Their durability and long-term reliability are often overlooked, despite being critical for the successful deployment of these systems in real-world applications. This article contributes to solving this challenge by identifying metrics that reflect material wear, mechanical hysteresis, and drift occurring during long-term operations in soft architectured materials. While this same pipeline can be generalized to different soft robots, we test these metrics on the trimmed helicoid architectured materials, and we validate the improvement in performance on the Helix soft manipulator. Thanks to the proposed metrics, we demonstrate a 75% reduction in repeatability errors over long-duration experiments.

Keywords: Cellular and Modular Robots, Soft Robot Materials and Design, Robotics and Automation in Construction
Abstract: In this paper, we present a soft modular block inspired by tensegrity structures that can form load-bearing structures through self-assembly. The block comprises a stellated compliant skeleton, shape memory alloy muscles, and permanent magnet connectors. We classify five deformation primitives for individual blocks: bend, compress, stretch, stand, and shrink, which can be combined across modules to reason about full-lattice deformation. Hierarchical function is abundant in nature and in human-designed systems. Using multiple self-assembled lattices, we demonstrate the formation and actuation of 3-dimensional shapes, including a load-bearing pop-up tent, a self-assembled wheel, a quadruped, a block-based robotic arm with gripper, and non-prehensile manipulation. To our knowledge, this is the first example of active deformable modules (blocks) that can reconfigure into different load-bearing structures on-demand.

Keywords: Modeling, Control, and Learning for Soft Robots, Soft Sensors and Actuators, Calibration and Identification
Abstract: The control possibilities for soft robots have long been hindered by the need for reliable methods to estimate their configuration. Inertial measurement units (IMUs) can solve this challenge, but they are affected by well-known drift issues. This paper proposes a method to eliminate this limitation by leveraging the Piecewise Constant Curvature model assumption. We validate the reconstruction capabilities of the algorithm in simulation and experimentally. To this end, we also present a novel large-scale, foam-based manipulator with embedded IMU sensors. Using the filter, we bring the accuracy in IMU-based reconstruction algorithms to 93% of the soft robot's length and enable substantially longer measurements than the baseline. We also show that the proposed technique generates reliable estimations for closed-loop control of the robot's shape.

Keywords: Soft Robot Materials and Design, Soft Sensors and Actuators, Modeling, Control, and Learning for Soft Robots
Abstract: Soft robots have immense potential given their safer contact with environments, but challenges in soft actuator forces and design constraints have limited scaling up soft robots to larger sizes. Electrothermal shape memory alloy (SMA) artificial muscles have the potential to create these large forces and high displacements, but consistently using these muscles under a well-defined model, in-situ in a soft robot, remains an open challenge. This article provides a system for maintaining the highest-possible consistent SMA forces, over long lifetimes, by combining a fatigue testing protocol with a supervisory control system for the muscles' internal temperature state. We introduce a soft limb with swappable SMA muscles, and deploy the limb in a blocked-force test to quantify the maximum applied force at different temperatures over different cyclic fatigue lifetimes. Then, by applying an invariance-based control system to maintain temperatures under our proposed long-life limit, we demonstrate consistent high forces in a practical task over hundreds of cycles. The method we developed allows for practical implementation of SMAs in soft robots through characterizing and controlling their behavior in-situ, and provides a method to impose limits that maximize their consistent, repeatable behavior.

Keywords: Tendon/Wire Mechanism, Underactuated Robots, Computational Geometry
Abstract: Coupled actuation is a common strategy for reducing the number of actuators in robots with high degrees of freedom. Coupled actuation leads to an underactuation that lowers system complexity and weight. However, an approach for a controlled nonlinear coupling of multiple tendons does not exist for tendon-driven actuation. We propose a method to enable task-defined non-linearly coupled actuation by designing eccentric pulleys of variable radii. Given a target profile of tendon length changes, we perform piecewise fitting of the target curve to generate a composite pulley geometry. Theoretical verification of the method with 200 randomly generated tendon profiles shows stable results with an average of 2.19 % relative error. In addition, we built a practical demonstration by implementing non-linearly coupled control of a tendon-driven finger. The six tendons that control the robotic finger were all actuated using pulleys connected to a single motor, resulting in a 5.35 % average fingertip orientation tracking error. In conclusion, the pulley-shaping method proposed in this project enables the task-defined nonlinear coupling of multiple degrees of freedom to a single actuator of tendon-driven systems. We believe that the algorithm’s generalizability will enable further practical use in tendon-driven dexterous hands, animatronics, manipulators, and legged robots, among various other possible applications.

Keywords: Modeling, Control, and Learning for Soft Robots, Underactuated Robots, Soft Sensors and Actuators
Abstract: In this paper, we investigate model-based trajectory tracking position control of an articulated soft robotic system driven by rolled dielectric elastomer actuators. The system's features, including underactuation with a configuration-dependent actuation matrix, open-loop bi-stable behavior, and significant elastic as well as kinematic nonlinearities, make the design of a tracking controller a highly challenging task. Starting from an accurate Euler-Lagrange dynamic model of the soft robot, we propose a nonlinear coordinate transformation to achieve the so-called collocated form. Conditions for the existence of such change of coordinates are investigated using a geometric argument, which in turn provides an analytical expression for the inverse transformation as well as a characterization of the region in which such inverse exist. Next, a partial state feedback linearization law is designed for trajectory tracking, and the zero dynamics stability is analyzed. The effectiveness of the approach is finally verified via numerical simulation based on an accurate physical model.

Keywords: Grippers and Other End-Effectors, Soft Robot Materials and Design, Compliant Joint/Mechanism
Abstract: Pneunets are the primary form of soft robotic grippers. A key limitation to their wider adoption is their inability to grasp larger payloads due to objects slipping out of grasps. We have overcome this limitation by introducing a torsionally rigid strain limiting layer (TR-SLL). This reduces out-of-plane bending while maintaining the gripper’s softness and in-plane flexibility. We characterize the design space of the strain limiting layer for a Pneu-net gripper using simulation and experiment and map bending angle and relative grip strength. We found that the use of our TR-SLL reduced out- of-plane bending by up to 97.7% in testing compared to a benchmark Pneu-net gripper from the Soft Robotics Toolkit. We demonstrate a lifting capacity of 5kg when loading using the TR-SLL. We also see a relative improvement in peak grip force of 3N and stiffness of 1200N/m compared to 1N and 150N/m for a Pneu-net gripper without our TR-SLL at equal pressures. Finally, we test the TR-SLL gripper on a suite of six YCB objects above the demonstrated capability of a traditional Pneu-net gripper. We show success on all but one demonstrating significant increased capabilities.

Keywords: Soft Sensors and Actuators, Soft Robot Applications, Soft Robot Materials and Design
Abstract: Multifunctional materials, such as those with several self-x properties, enable new designs and applications of soft robots. The CN-Hydrogel material incorporates several of these self-x properties, which have been used separately in previous works for the development of soft sensors and actuators. In this work we use all these capabilities together to achieve modularity, controllability, and durability in soft bending pneumatic actuators. In particular, we use the self-adhesion in the modular design and fabrication, the self-sensing for a closed loop control scheme and the self-healing for damage repair. The experimental validation of our modular approach is fulfilled with a bidirectional bending prototype.

Keywords: Soft Robot Materials and Design, Additive Manufacturing, Computer Vision for Other Robotic Applications
Abstract: Pneumatic soft robots are typically fabricated by molding, a manual fabrication process that requires skilled labor. Additive manufacturing has the potential to break this limitation and speed up the fabrication process but struggles with consistently producing high-quality prints. We propose a low-cost approach to improve the print quality of desktop fused deposition modeling by adding a webcam to the printer to monitor the printing process and detect and correct defects such as holes or gaps. We demonstrate that our approach improves the air-tightness of printed pneumatic actuators while reducing the need for fine-tuning printing parameters. Our approach presents a new option for robustly fabricating airtight, soft robotic actuators.

Keywords: Soft Robot Materials and Design, Cellular and Modular Robots, Biologically-Inspired Robots
Abstract: Soft robots are often designed to accomplish a single function and cannot be repurposed for other tasks. In an effort to create multi-functional robots, researchers have proposed robotic skins, which are flexible, planar substrates with embedded actuation and sensing that can be applied to different soft bodies. By ``roboticizing" otherwise inert bodies from their surface, robotic skins can be repurposed to create bespoke soft robots as needed. However, current robotic skins are unable to support their own structure and can only attain a single function in the absence of a host. Here, we present a variable stiffness robotic skin (VSRS), a concept that integrates stiffness-changing capabilities, sensing, and actuation into a single, thin modular robot design. Reconfiguring, reconnecting, and reshaping VSRSs allows them to achieve new functions both on and in the absence of a host body. We demonstrate how a single set of skins with PneuFlex-style pneumatic actuators, a geometrically-patterned polyethylene terepthalate (PET) jamming membrane, and liquid metal-based capacitive sensors can operate as closed-loop locomotion robots while being able to support weight during locomotion, as well as stiffen to hold complex shapes. To highlight the generality of the concept and illuminate the design space, we also test a second embodiment with McKibben actuators and a woven-mesh jamming membrane that can be reconfigured to serve in a manipulation context. We see VSRSs having application as adaptable linkages in larger robots, smart reconfigurable garments, and reconfigurable active structures, thereby allowing the robotic system to adapt to time-varying task requirements.

Keywords: Modeling, Control, and Learning for Soft Robots, Soft Robot Applications
Abstract: The ability of a soft robot to perform specific tasks is determined by its contact configuration, and tran- sitioning between configurations is often necessary to reach a desired position or manipulate an object. Based on this observation, we propose a method for controlling soft robots that involves defining a graph of configuration spaces. Different agents, whether learned or not (convex optimization, expert trajectory, and collision detection), use the structure of the graph to solve the desired task. The graph and the agents are part of the prior knowledge that is intuitively integrated into the learning process. They are used to combine different optimization methods, improve sample efficiency, and provide interpretability. We construct the graph based on the contact configurations and demonstrate its effectiveness through two scenarios, a deformable beam in contact with its environment and a soft manipulator, where it outperforms the baseline in terms of stability, learning speed, and interpretability.

Keywords: Soft Robot Materials and Design, Grippers and Other End-Effectors
Abstract: Light-responsive hydrogels are intelligent materials that respond to external light stimuli. When exposed to light, they shrink by releasing water, enabling non-invasive, cost-effective, and remotely controllable actuation. Their adaptability to light parameters such as intensity, direction, wavelength, and irradiation time makes these materials ideal for developing soft robotic actuators. However, hydrogel-based actuators face several challenges due to poor mechanical properties, complex fabrication, and biocompatibility concerns. To address these limitations, this study presents a light-driven 3D-printed elastomer/hydrogel composite actuator. The soft photo-actuator combines TangoPlus, a flexible 3D printing material, with a poly(N-isopropylacrylamide) (PNIPAM) hydrogel copolymerized with the photochromic molecule spiropyran. The study's key contributions include an investigation into prototypes that demonstrate enhanced mechanical integrity, where hydrogel thickness and curing time are shown to affect the actuator's shrinkage response in a predictable manner. Furthermore, a proof-of-concept of a 3D gripping mechanism is proposed to demonstrate the actuator's potential applicability.

Keywords: Soft Robot Applications, Modeling, Control, and Learning for Soft Robots, Telerobotics and Teleoperation
Abstract: Integrating Brain-Machine Interfaces into non-clinical applications like robot motion control remains difficult - despite remarkable advancements in clinical settings. Specifically, EEG-based motor imagery systems are still error-prone, posing safety risks when rigid robots operate near humans. This work presents an alternative pathway towards safe and effective operation by combining wearable EEG with physically embodied safety in soft robots. We introduce and test a pipeline that allows a user to move in real-time a soft robot's end effector via brain waves that are measured by as few as three EEG channels. A robust motor imagery algorithm interprets the user's intentions to move the position of a virtual attractor to which the end effector is attracted, thanks to a new Cartesian impedance controller. We specifically focus here on planar soft robot-based architected metamaterials, which require the development of a novel control architecture to deal with the peculiar nonlinearities - e.g., non-affinity in control. We preliminarily but quantitatively evaluate the approach on the task of setpoint regulation. We observe that the user reaches the proximity of the setpoint in 66% of steps and that for successful steps, the average response time is 21.5s. We also demonstrate the execution of simple real-world tasks involving interaction with the environment, which would be extremely hard to perform if it were not for the robot's softness.

Keywords: Wearable Robots, Rehabilitation Robotics, Soft Robot Applications
Abstract: Wearable soft robots can be an effective tool for rehabilitation due to their inherent safety and compliance. Challenges, however, exist regarding the development of suitable on-body actuation methods. Furthermore, the majority of existing soft wearable devices are not accessible and easy to use for those with physical disabilities. This paper presents the design, fabrication, and characterization of a soft robotic wrist orthosis tailored for flexion and extension continuous passive motion therapy. We developed bending textile pneumatic actuators that can be mechanically programmed to conform to the target joint’s anatomy when mounted on the body. The textile pneumatic actuators can achieve up to 2.24 Nm of torque at 124 kPa. We embedded the textile pneumatic actuators into a soft wrist orthosis that we designed to ensure it is easy to don/doff without assistance. To determine the operating pressures and range of motion achievable by our soft robotic wrist orthosis, we conducted a device evaluation study with three healthy individuals. Our device can achieve over 101 degrees of flexion/extension assistance at operating pressures below 90 kPa. This work takes the first steps towards developing a wearable soft robotic device that can deliver passive therapy at home without the need of a physical therapist or assistant.

Keywords: Soft Robot Materials and Design, Compliant Joint/Mechanism, Grasping
Abstract: Soft grasping has become the accepted standard to grasp geometrically complex and deformable objects; however, the in the absence of efficient design tools, 'universal' designs have proliferated. Bespoke design approaches, which exploit morphological computation to increase contact area and grasp success and reduce contact force, have been limited by the complexity of modelling the grasping behaviour of geometrically uncertain deformable designs. We present a framework for bespoke soft gripper design based on functionally graded topology optimisation, which exploits both macroscale geometry and microscale material properties to generate high-quality grasps. Using a model of the grasped object, we simulate the interactions between the deformable gripper and object to find the optimal material properties and material distribution across a voxelised design domain. We develop a material interpolation method which generates custom metamaterials by combining hard and soft materials at high resolution and explore multi-material polyjet 3D printing to produce functionally graded soft grippers with the metamaterials. We show that our bespoke design method produces unique geometries tailored to specific objects, and that the combination of bespoke geometric design and localised metameterials produces unique designs which enhance grasp performance.

Keywords: Soft Robot Materials and Design, Hydraulic/Pneumatic Actuators, Force Control
Abstract: A minimal number of rigid constraints make soft robots versatile, but many of these robots use soft pneumatic actuators (SPAs) designed to inflate through a single trajectory. In an unloaded actuator, this trajectory is dictated by the arrangement of in-extensible and elastic materials. External strain limiters can be added post-fabrication to SPAs, but these are passive devices. In this paper, we offer design and control techniques for an electrically active strain limiter that is easily adhered to existing SPAs to provide signal-controlled force output. These sheathed electroadhesive (EA) clutches apply antagonistic forces through the constitutive properties of their silicone sheathing and through the variable friction of the clutch itself. We are able to design the sheathing to passively support loads or minimize passive stiffness. We control clutch forces via an augmented pulse-width-modulation (PWM) of the high voltage square-wave input. We perform an initial, empirical characterization on the system with tensile material testing. The clutch system resists motion with sustained forces ranging from 0.5N to 22N. We then demonstrate its ability to apply predictable nonconservative work in a dynamic catching task, where it can limit catching height from 15cm to 1cm. Finally, we attach it to an inverse pneumatic artificial muscle (IPAM) to show that variable strain limitation can control position of the SPA endpoint.

Keywords: Modeling, Control, and Learning for Soft Robots, Biologically-Inspired Robots, Underactuated Robots
Abstract: Non-contact, fluid-mediated manipulation of objects using underactuated soft robots or structures presents unique control challenges, demanding a nuanced understanding of fluid dynamics and innovative control methods. In this study, we investigate methods for efficiently manipulating objects in water, exploiting the fluid structure interactions of soft underactuated soft tentacles. To leverage fluid interactions, we identify behavioral primitives that enable object manipulation through different modalities of vortex generation, and demonstrate this through PIV imaging. This reduced order control space can be used to aid both teleoperation-based manipulation, and also to develop a Finite State Machine (FSM) based controller, which offers an efficient means to exploit fluids for manipulation. This lays the ground for more data intensive approaches for learning controllers for this complex control challenge.

Keywords: Modeling, Control, and Learning for Soft Robots, Sensor Fusion, Deep Learning in Robotics and Automation
Abstract: Perception is essential for the active interaction of physical agents with the external environment. The integration of multiple sensory modalities, such as touch and vision, enhances this perceptual process, creating a more comprehensive and robust understanding of the world. Such fusion is particularly useful for highly deformable bodies such as soft robots. Developing a compact, yet comprehensive state representation from multi-sensory inputs can pave the way for the development of complex control strategies.

This paper introduces a perception model that harmonizes data from diverse modalities to build a holistic state representation and assimilate essential information. The model relies on the causality between sensory input and robotic actions, employing a generative model to efficiently compress fused information and predict the next observation. We present, for the first time, a study on how touch can be predicted from vision and proprioception on soft robots, the importance of the cross-modal generation and why this is essential for soft robotic interactions in unstructured environments.

Keywords: Biologically-Inspired Robots, Soft Robot Materials and Design, Soft Robot Applications
Abstract: The development of food products that are safe whilst also nutritious and sustainable is a key challenge for the food industry. However, evaluating the safety of food, and in particular swallowing safety, is a fundamental challenge to ensure safety, perception, and nutritional contributions. This becomes especially complex when ethical considerations preclude the use of human panels for certain demographics like children, the elderly, and the ill, or when assessing disruptive food technologies such as cultivated products. To address this challenge, we propose the development of a robotic swallowing simulator that emulates the swallowing process, leveraging soft actuation of the tongue and epiglottis to simulate the swallowing of chewed `bolus'. By showing the sensitivity of the robot to the viscosity of bolus, and tilt angle, we show the ability to capture similar responses to humans. This provides some first insights into developing robotic means of evaluating swallowing safety, and how soft robotic technologies can be deployed to achieve this goal.

Keywords: Soft Sensors and Actuators, Force and Tactile Sensing
Abstract: The different receptors in human skin show not only diversity in the stimuli to which they respond, but also variable sensitivity and directionality. This is often determined by their location or morphology, and can play an important role in filtering or amplifying the stimuli applied to the skin. We require similar capabilities for `programming' the response of soft sensors, such that their responsivity can be varied for the specific task they are performing. We introduce a novel approach that employs hall-effect sensors, with magnets embedded in custom designed soft filters. By modifying the material properties and introducing morphological features into these filters, we mechanically tune the sensor response to normal and shear force. This embodied tuning allows sensors to be adapted to specific tasks without altering robot control policies. We demonstrate the concept through a number of exemplar tasks that leverage amplification, filtering or reduction in sensor signals. This approach provides a scalable means of programming the spatial resolution and directionality of sensor sensors, contributing to more capable sensor-motor control for robots.

Keywords: Multifingered Hands, Grasping, Soft Robot Materials and Design
Abstract: We automate soft robotic hand design iteration by co-optimizing design and control policy for dexterous manipulation skills in simulation. Our design iteration pipeline combines genetic algorithms and policy transfer to learn control policies for nearly 400 hand designs, testing grasp quality under external force disturbances. We validate the optimized designs in the real world through teleoperation of pickup and reorient manipulation tasks. Our real world evaluation, from over 900 teleoperated tasks, shows that the trend in design performance in simulation resembles that of the real world. Furthermore, we show that optimized hand designs from our approach outperform existing soft robot hands from prior work in the real world. The results highlight the usefulness of simulation in guiding parameter choices for anthropomorphic soft robotic hand systems, and the effectiveness of our automated design iteration approach, despite the sim-to-real gap.

Keywords: Soft Robot Applications, Simulation and Animation, Soft Robot Materials and Design
Abstract: We create a mechanism inspired by bacterial swimmers, featuring two flexible flagella with individual control over rotation speed and direction in viscous fluid environments. Using readily available materials, we design and fabricate silicone-based helical flagella. To simulate the robot's motion, we develop a physics-based computational tool, drawing inspiration from computer graphics. The framework incorporates the Discrete Elastic Rod method, modeling the flagella as Kirchhoff's elastic rods, and couples it with the Regularized Stokeslet Segments method for hydrodynamics, along with the Implicit Contact Model to handle contact. This approach effectively captures polymorphic phenomena like bundling and tumbling. Our study reveals how these emergent behaviors affect the robot's attitude angles, demonstrating its ability to self-reorient in both simulations and experiments. We anticipate that this framework will enhance our understanding of the directional change capabilities of flagellated robots, potentially encouraging further research into the mobility of microscopic robots for a variety of tasks, including drug delivery in blood.

Keywords: Soft Robot Materials and Design, Soft Robot Applications
Abstract: Modular and climbing robots have employed electropermanent magnets as a power-efficient alternative to electromagnets for tasks that involve attaching modules or exerting forces on ferromagnetic surfaces. In this paper, we present compliant electropermanent magnets that extend the benefits of electropermanent magnets to the field of soft robotics. We describe a process for designing compliant electropermanent magnets with different materials and mixing ratios to achieve desired properties without sacrificing the mechanical compliance necessary for integration into soft robots. Finally, we characterize the performance of the compliant electropermanent magnets and demonstrate their ability to repeatably and reversibly switch their magnetization ON and OFF.

Keywords: Modeling, Control, and Learning for Soft Robots, Visual Servoing
Abstract: Soft robots, due to their adaptability and safety, can make a significant impact in specialized fields such as surgical robotics owing to their compliance. However, such highly flexible robots are especially susceptible to modeling and control challenges due to non-linearities, large deformations, and infinite degrees of freedom. Combined with material variations, manufacturing inconsistencies, and environmental influences, these robots exhibit stochastic behavior. To address this, the paper introduces a learning-based approach supported by a Neural Network-based Generative Model designed to address the inherent stochastic nature of such robots in visual servoing tasks. By generating large quantities of synthetic data that represent the stochastic effects, another learning model used for control can be trained to mitigate them. The method's efficacy is demonstrated in visual servoing tasks by significantly improving the accuracy of the robot. Implementing the proposed model in a feedback control loop improves the performance when compared to the open loop approach in more challenging trajectories, marking a substantial stride in overcoming the challenges associated with stochastic behavior in soft robotics.

Keywords: Modeling, Control, and Learning for Soft Robots, Soft Robot Materials and Design, Soft Robot Applications
Abstract: The multimodal Zig-zag Soft Pneumatic Actuator (SPA) provides an effective design approach for achieving desired extensions and bending geometries under specific pressure conditions. The rigid-body approximated model introduced in this study brings valuable insights into SPA dynamics by enabling faster simulations when compared to methods such as Finite Element Analysis (FEA). The model outlined in this paper forecasts static behavior by estimating the linear expansion of linear SPA and the bending angle of bending SPA. These two modes of motion can be combined to expand the degree of freedom. Depending on the configuration of the Strain Limiting Layer (SLL), the bending angle can be adjusted by controlling the actuator stiffness, a parameter that can be precisely characterized using the proposed actuator model. To address the hysteresis phenomena in linear expansion SPA, the Bouc-Wen hysteresis model is employed to model the actuator hysteresis responses at higher actuation rates. The validity of the proposed model is experimentally confirmed through the use of 3D-printed SPA prototypes that are designed for both extension and bending actuation.

Keywords: Soft Robot Materials and Design, Biologically-Inspired Robots, Tendon/Wire Mechanism
Abstract: Conventional soft robots are designed with constant, passive stiffness properties, based on desired motion capabilities. The ability to encode two fundamentally different stiffness characteristics promises to enable a single robot to be optimized for multiple divergent tasks simultaneously. In this paper, we propose phase-changing metallic spines of various geometries to independently control specific stiffness parameters of soft robots, and change how they respond to their actuation inputs and external loads. We fabricate spine-like structures using a low melting point alloy (LMPA), enabling us to switch on and off the effects of the stiff metal structure on the overall robot’s stiffness during use. Changing soft robot morphology in this manner will enable these robots to adapt to different environments and tasks that require divergent motion and force/moment application capabilities.

Keywords: Soft Robot Materials and Design, Soft Robot Applications, Legged Robots
Abstract: The limbs of aquatic and terrestrial animals generally differ in their shape and stiffness, and many bio-inspired robots adopt these specialized forms. For example, some robots use flippers and legs for aquatic and terrestrial locomotion, respectively. Robotic limbs that can access different shapes and modulate their stiffness can facilitate robotic transitions between multiple environments. Herein, we report a morphing limb that quickly and efficiently switches between a flexible flipper for swimming and a rigid leg for walking/crawling by combining layer jamming and pouch-based pneumatic actuation. The internal pouch actuator contributes to the pressure that jams the external layers of the limb, which we call dual-mode jamming. We elucidate the extent of shape-morphing conferred by the pouch actuator, the maximum load-bearing capability of the limb in leg mode, and the hydrodynamic characteristics of the limb in flipper mode. The maximum load-bearing capability in leg mode is increased by ~30% with the dual-mode jamming system compared with only using jamming. The limb also boasts rapid morphing, low energetic cost of morphing, and high hydrodynamic efficiency in the flipper shape. With its own lightweight and compact electronics system, the morphing limb is a plug-and-play component for building an untethered multi-environment robot.

Keywords: Simulation and Animation, Optimization and Optimal Control, Modeling, Control, and Learning for Soft Robots
Abstract: Soft robotics aims to develop robots able to adapt their behavior across a wide range of unstructured and unknown environments. A critical challenge of soft robotic control is that nonlinear dynamics often result in complex behaviors that are hard to model and predict. Typically behaviors for mobile soft robots are discovered through empirical trial and error and hand-tuning. More recently, optimization algorithms such as Genetic Algorithms (GA) have been used to discover gaits, but these behaviors are often optimized for a single environment or terrain, and can be brittle to unplanned changes to terrain. In this paper we demonstrate how Quality Diversity Algorithms, which search of a range of high-performing behaviors, can produce repertoires of gaits that are robust to changing terrains. This robustness significantly out-performs that of gaits produced by a single objective optimization algorithm.

Keywords: Additive Manufacturing, Micro/Nano Robots, Surgical Robotics: Steerable Catheters/Needles
Abstract: A wide range of endovascular interventions rely on surgical tools such as guidewire-catheter systems for navigating through blood vessels to, for example, deliver embolic materials, stents, and/or therapeutic agents to target sites as well as biopsy tools (e.g., forceps and punch needles) for medical diagnostics. In response to the difficulties in maneuvering such endovascular instruments safely and effectively to access intended sites in the body, researchers have developed an array of soft robotic surgical tools that harness fluidic (e.g., pneumatic or hydraulic) actuation schemes to support on-demand steering and control. Despite considerable progress, scaling these tools down to the sizes required for medical procedures such as cerebral aneurysm treatment and liver chemoembolization have been hindered by manufacturing-induced constraints. To provide a pathway to overcome these miniaturization challenges, this work presents a novel additive manufacturing strategy for 3D microprinting integrated soft actuators directly atop multilumen microfluidic tubing via “Two-Photon Direct Laser Writing (DLW)”. As an exemplar, a two-actuator tip was 3D printed onto custom dual-lumen tubing—resulting in a system akin to a 1.5 French (Fr) guidewire with a steerable tip. Experimental results revealed independent actuator control via the discretized lumens, with tip bending of approximately 60º under input pressures of 130 kPa via hydraulic actuation. These results suggest that the presented strategy could be extended to achieve new classes of fluidically actuated soft robotic surgical tools at unprecedented length scales for emerging applications in minimally invasive surgery.

Keywords: Soft Robot Applications, Grasping, Soft Sensors and Actuators
Abstract: Although bin packing has been a key benchmark task for robotic manipulation, the community has mainly focused on the placement of rigid rectilinear objects within the container. We address this by presenting a soft robotic hand that combines vision, motor-based proprioception, and soft tactile sensors to identify, sort, and pack a stream of unknown objects. This multimodal sensing approach enables our soft robotic manipulator to estimate an object's size and stiffness, allowing us to translate the ill-defined human conception of a "well-packed container" into attainable metrics. We demonstrate the effectiveness of this soft robotic system through a realistic grocery packing scenario, where objects of arbitrary shape, size, and stiffness move down a conveyor belt and must be placed intelligently to avoid crushing delicate objects. Combining tactile and proprioceptive feedback with external vision resulted in a significant reduction in item-damaging packing maneuvers compared to a sensorless baseline (9x fewer) and vision-only (4.5x fewer) techniques, successfully demonstrating how the integration of multiple sensing modalities within a soft robotic system can address complex manipulation applications.

Keywords: Wearable Robotics, Soft Robot Applications, Physically Assistive Devices
Abstract: A significant part of the parcel delivery service occurs outside the warehouse, relying entirely on human resources to deliver parcels to the customer’s doorstep. The parcel delivery officers carry and hold parcels of about 25 kg of weight during the delivery process through diverse terrains such as elevated ground and staircases especially in many crowded cities. As a result of holding and carrying heavy parcels repeatedly, the officers report upper body musculoskeletal disorders in the arms, and lower back. Robotic exosuits are actively being developed but are primarily oriented toward lifting assistance only and do not cater to the entire upper body assistance. In this paper, we propose a load-redistribution strategy in the form of a fully soft passive wearable robot, that provides load-dependent compression around the lower back for back support and arm assistance. This is achieved through the coupling of the load and the human body, which ensures the wearer receives appropriate assistance only when in need. The suit design parameters are as follows: the elastic component that inherently enhances comfort in breathing even in its tightened state while transmitting compression force onto the human abdominal muscles; and the number of pulleys on the belt to control the amount of belt compression in users of different size; and the length of the corset tendon. The mannequin mock-up experiment and analytical modeling demonstrate the relationship between the design parameters and pressure on the human body. Human experiment also verifies the upper body assistance performance of the suit in significantly reducing the arms' muscle efforts (p < 0.05) in parcel delivery.

Keywords: Modeling, Control, and Learning for Soft Robots, Computer Vision for Medical Robotics, Data Sets for Robot Learning
Abstract: Continuum robots are promising candidates for interactive tasks in medical and industrial applications due to their unique shape, compliance, and miniaturization capability. Accurate and real-time shape sensing is essential for such tasks yet remains a challenge. Embedded shape sensing has high hardware complexity and cost, while vision-based methods require stereo setup and struggle to achieve real-time performance. This letter proposes a novel eye-to-hand monocular approach to continuum robot shape sensing. Utilizing a deep encoder-decoder network, our method, MoSSNet, eliminates the computation cost of stereo matching and reduces requirements on sensing hardware. In particular, MoSSNet comprises an encoder and three parallel decoders to uncover spatial, length, and contour information from a single RGB image, and then obtains the 3D shape through curve fitting. A two-segment tendon-driven continuum robot is used for data collection and testing, demonstrating accurate (mean shape error of 0.91 mm, or 0.36% of robot length) and real-time (70 fps) shape sensing on real-world data. Additionally, the method is optimized end-to-end and does not require fiducial markers, manual segmentation, or camera calibration. Code and datasets are available at https://github.com/ContinuumRoboticsLab/MoSSNet.

Keywords: Micro/Nano Robots, Kinematics, Motion Control
Abstract: Locomotion is a fundamental capability that all mobile robots strive to achieve. A large variety of magnetic miniature robots have been proposed to leverage the magnetic forces and torques between internal magnetic agents and external magnetic fields to enable various locomotion on different terrains. However, few of them can achieve diverse locomotion capabilities. And their locomotion capabilities depend on specific environments, which hinders their applicability in the real world. This letter presents a magnetic repulsion-based robot (MR^2) with diverse locomotion capabilities, demonstrating agile and robust movement in diverse environments. The MR^2 has two embedded free-to-rotate spherical magnets. The local magnetic force between these two magnets is leveraged to generate reciprocating motions with the help of a pair of one-crease linkages. While, the asymmetrical design of MR^2 transduces this reciprocating motion into controlled directional locomotion. By tuning the global magnetic field, the MR^2 demonstrates non-holonomic mobility and steerability. It can also switch between locomotion modes of crawling, tumbling, and climbing, making it adaptable to diverse terrains and environments. The MR^2 demonstrates a robust locomotion capability with a crawling speed of 84.10 mm·s^-1 (3.50 bodylength/s), a turning speed of 25.2 °/s, a tumbling speed of 68.98 mm·s^-1 (2.87 bodylength/s) and a climbing ability up a slope of 45°.

Keywords: Soft Sensors and Actuators, Soft Robot Materials and Design, Soft Robot Applications
Abstract: Soft robotics has sought to emulate natural behaviors. One impressive ability of living systems is operating in confined and narrow pathways,from caterpillars to tapeworms. Among the soft actuators, dielectric elastomer actuators (DEAs) are suitable candidates for this ability with fully soft systems, energy, and power densities on par with natural muscles and simple electro-mechanical drive. In this paper, we present the systematic guideline for designing and fabricating a steerable tip based on bimorph DEAs capable of guiding a small flexible insertion tube. We developed the tip by assembling identical DEAs into a multilayer structure, which induces stable bending at the same bias voltage. We investigated various structural parameters such as length, passive zone, and multilayer/scaling effect for active and smooth navigation. Then, we suggested the methodology to provide the tip with not only flexibility to move along with pathways but also sufficient stiffness to lead the flexible tube attached to the tip in the desired direction. The tip’s steerable performance was analyzed in various conditions, such as deflected by gravity or suspended in liquid media of various viscosities and conductivities. We demonstrated fast, reliable actuation with active tip control and the ability of shaking or stirring functions based on dynamic actuation.

Keywords: Micro/Nano Robots, Biomimetics, Biologically-Inspired Robots
Abstract: Controlled landing is essential for biological and engineered jumpers to perform repetitive jumps and avoid damage to the body. In this paper, we introduce a bio-inspired jumping robot. This robot, small in scale (body length of approximately 20 mm) and lightweight (around 100 mg), can jump directionally and land with a controlled posture. Its torque reversal catapult-based jumping mechanism facilitates rapid takeoff at a speed of 3 m/s and achieves a maximum jumping height of approximately 22 times its size. This performance is remarkably similar to the height reached by springtails. The aerodynamic torque, induced by drag flaps, can reduce the body's angular velocity by 70% compared to that of an uncontrolled robot. Moreover, the robot's mid-air posture can be passively controlled through an enhanced stable equilibrium.

Keywords: Grippers and Other End-Effectors, Soft Robot Materials and Design, Modeling, Control, and Learning for Soft Robots
Abstract: In the field of soft robotics, many intriguing robots incorporate helical deformation. Many of them rely on Pneumatic Artificial Muscles (PAMs) as a foundation; however, PAMs have certain limitations. In this paper, we propose a novel mechanism inspired by the twisted string actuators (TSAs) that can achieve helical deformation easier. The main components consist of a string installed within a hose, and the rotation of the string causes the hose to deform into a conical spiral shape. We conducted experiments to validate and explore this intriguing deformation. We derived some interesting tentatively conclusions: when the rigidity of the string and hose is determined, a virtual conical surface is established. The rotation of the string continuously causes the hose to spiral upward on this virtual conical surface, and altering the length of the hose merely increases the height of the conical spiral shape without changing the cone angle. We also conducted experiments utilizing this mechanism for grasping object. Furthermore, we conducted some simulation computations.

Keywords: Modeling, Control, and Learning for Soft Robots, Tendon/Wire Mechanism, Grippers and Other End-Effectors
Abstract: Pyshical flexibility is one of the good aspects of soft robotic hands when grasping an unknown-shaped object stably or interacting with around environment safely. On the other hand, considering controlling them dexterously, their flexibility can cause nonlinear and uncertain behaviors and this will be the barrier to accurate control. Furthermore, they deform continuously and entirely, which makes it difficult to use some sensors and to control by direct sensor feedback. For such a soft robot system, state estimation is the key to realizing accurate control. It is necessary to improve the accuracy of a model for good state estimation. Recently, probabilistic models have been proposed to represent uncertainties in soft robots, and this method can overcome traditional deterministic models that sometimes exhibit good but sometimes undesirable behaviors in terms of soft robots. We also have proposed the dynamic model of a soft finger with stochastic parameters. Because this model is the extension of the traditional dynamics, it is easy to apply the traditional state estimation method. In this paper, the state estimation method that uses the stochastic characteristics of the model is proposed. Through experiments, the efficiency of the proposed estimation is investigated.

Keywords: Biologically-Inspired Robots, Biomimetics, Soft Robot Materials and Design
Abstract: The human joint is an open-type joint composed of bone, cartilage, ligaments, synovial fluid, and joint capsule, and have advantages of flexibility and impact resistance. However, replicating this structure in robots introduces friction challenges due to the absence of bearings. To address this, our study focuses on mimicking the fluid-exuding function of human cartilage. We employ a rubber-based 3D printing technique combined with absorbent materials to create a versatile and easily designed cartilage sheet for biomimetic robots. We evaluate both the fluid-exuding function and friction coefficient of the fabricated flat cartilage sheet. Furthermore, we practically create a piece of curved cartilage and an open- type biomimetic ball joint in combination with bones, ligaments, synovial fluid, and joint capsule to demonstrate the utility of proposed cartilage sheet in the construction of such joints.

Keywords: Grippers and Other End-Effectors, Grasping, Tendon/Wire Mechanism
Abstract: Vertical farming has emerged as a sustainable, efficient, and climate-resilient food production method, which can improve food security. In most commercial vertical farms, harvesting is carried out manually, which are labor-intensive and costly. Numerous robotic grippers solutions have been developed for harvesting. However, they have limitations like restricted adaptivity, excessive mechanical stress on target, and poor accessibility, hindering their adoption for harvesting. Here, we present a tendon-driven gripper equipped with a capacitance-based contact sensor array. The proposed gripper can grow and twine around the target vegetable and adjust the tightness of its grip based on number of contacts. The preproposed gripper can generate 4 to 10 N pulling force on bok choy and can also grip various gourds, leafy and podded vegetables. This work paves the way for harvesting automation in vertical farms. Apart from agriculture field, the smart gripper can also be used to grasp objects with various size, shape and weight in warehouse, and food & beverage industry.

Keywords: Soft Robot Materials and Design, Soft Sensors and Actuators, Grippers and Other End-Effectors
Abstract: In this paper we further studies of viscous-driven fluidic elastomer actuators. Specifically, the one we investigate here consists of simple elastomer bellows connected in series by slender tubes and arranged in two columns around a neutral plane. The slender tubes and wide bellows configuration result in advective-diffusive flow, which causes non-uniform pressure distributions throughout the actuator and, as a consequence, complex transient 2D deformations that depends only on the shape of the input pressure profile, rather than multiple pressure sources and/or valves. We extend upon previous work by demonstrating and modeling a three-finger `manipulator' capable of stabilizing a computer mouse and operating its scroll wheel. This demonstration illustrates the interplay between input pressure gradients and motion output, and additionally how a single valve can further enable stationary poses throughout the workspace of the actuator. To further illustrate how the motion is affected by the input pressure gradients, we perform a frequency sweep using our model. This type of embodied control matches well the infinite passive degrees of freedom afforded by the soft material, and holds great promise for future applications in soft robotics.

Keywords: Soft Robot Materials and Design, Biologically-Inspired Robots
Abstract: Electro-ribbon zipping actuators harness electrostatic and dielectrophoretic forces to bring together insulated electrode ribbons, akin to the action of a zipper. This study explores improvements to the materials used in and design of Electro-Ribbon actuators, aiming to develop high-performance soft actuation building blocks for potential bio-mimetic actuators with stacked architecture. The use of Polyvinylidene fluoride copolymer as a thin insulator between ribbon electrodes is found to significantly improve the generated electrostatic force. Its higher dielectric constant and thinner thickness allow the actuator to perform at lower working voltages while improving actuation time, reducing weight and enhancing efficiency. Additionally, we demonstrate that by constricting the initial zipping angle, the load-lifting capacity can be increased. Beyond enhancing the performance of building block electro-ribbon actuators, this investigation places a primary focus on exploring a stacked configuration for future research and integration into robotic systems.

Keywords: Grippers and Other End-Effectors, Soft Robot Materials and Design, Soft Robot Applications
Abstract: To address apple harvesting labor shortages in Washington State, we are developing an innovative soft growing manipulator that aims to overcome the current limitations associated with conventional robotic solutions, specifically in terms of cost-effectiveness and efficiency. A critical aspect of this technology is the creation of a lightweight apple harvesting end-effector, weighing less than 0.8 kg, to account for the stringent payload restrictions of our custom soft growing manipulator. This paper presents the design of a lightweight cable-driven soft gripper, offers insights into its force characteristics, and provides a case study showcasing its effectiveness in a commercial orchard setting. The gripper’s weight is 0.306 kg, and it boasts a successful picking rate of 87.5% without damaging the fruit. In the future, our work will extend to further enhance the soft gripper by incorporating a twisting motion. It will also be seamlessly integrated with the soft growing manipulator and custom machine vision system, which will subsequently undergo evaluation in a commercial orchard.

Keywords: Grasping, Grippers and Other End-Effectors, Soft Robot Materials and Design
Abstract: Contact force sensing and grasp adaptation in soft robotic hands are still open challenges, although they represent fundamental requirements towards the achievement of delicate and accurate in-hand manipulation. In this paper, we present soft pneumatic pads that can be embedded into the rigid phalanges of a soft-rigid gripper to sense contact forces and consequently adapt the contact locations and grasping forces. Each pad is connected to a pressure sensor and can be independently inflated/deflated. The pads add sensing and actuation capabilities to the gripper. As a proof of concept, we present three applications where they are used for contact detection, in-hand manipulation, and grasp adjustment

Keywords: Soft Robot Materials and Design, Medical Robots and Systems, Tendon/Wire Mechanism
Abstract: In this paper, a design method for a Soft Micro-Robot (SMR) used for medical intervention in the context of cochlear implant insertion is proposed. Optimal design of cochlear implants has been a highly active research area in recent years. Dozens of articles address the topic of optimal design using different actuation strategies, resulting overall in promising outcomes. From magnetic to fluid actuation and concentric tubes, current strategies are based on generating an optimal bending moment. However, this approach gives optimal results that cannot be manufactured. Considering the manufacturing constraints of micro-scale soft robots, an optimal design method based on varying the robot bending stiffness is studied here. The cochlear implant is actuated by a tendon and has an optimal bending stiffness to achieve a given objective. In the context of cochlear insertion, this objective is to minimize the root mean square error (RMSE) of the robot neutral axis in comparison to the cochlea helicoidally shaped centerline. Simulation results are promising with an average distance error of 392 mu m and a standard-deviation of 33 mu m considering the robot material and manufacturing uncertainties.

Keywords: Soft Robot Materials and Design, Soft Robot Applications, Biologically-Inspired Robots
Abstract: Continuous advances in soft robotic technologies have promoted the feasibility of exploration of complex environments and terrains. One prominent example is the class of tip-everting “vine” robots, which have enabled a new set of real-world applications. Vine robots navigate their environment through growth and have recently been used in practice for in-pipe inspection, maintenance, and exploration. While locomotion through these directed cylindrical systems is simplified by a vine robot’s growth, there are challenges with navigation. In complex pipe networks with many junctions, one question is how a vine can navigate around its own body during exploration. For example, a vine may navigate a pipe network that forces the robot to traverse a section of a pipe it already traversed in the opposite direction. This work presents an experimental approach to investigating and characterizing the interaction of a vine with its own body inside of a pipe T-junction. The results of this work provide starting design recommendations for facilitating the successful navigation of a vine robot in a T-junction.

Keywords: Biomimetics, Soft Robot Materials and Design, Biologically-Inspired Robots
Abstract: Underwater compliant-body jet propulsion is among the most efficient of all animal locomotion. Multi-jet propulsion, a less common method of transit used by the Salp, offers a lower cost of transit, higher maneuverability, and redundancy in case of individual failure. Single-jetting robots have been created that are capable of tethered, repeatable swimming and steering. However, these designs were primarily inspired by squid, jellyfish, or other single-jet propulsors. In this work, we instead start with an individual module inspired by a salp chain. We analyze the shape change of different soft bodies activated by artificial muscles. By comparing the effect of body morphology and muscle activation sequence on volumetric change and extrapolated thrust, we can compare our results to those seen by salps. We achieve a maximum volumetric decrease during contraction of 26%.

Keywords: Soft Robot Materials and Design, Hydraulic/Pneumatic Actuators, Additive Manufacturing
Abstract: The one-to-one mapping of control inputs to actuator outputs results in elaborate routing architectures that limit how complex fluidic soft robot behaviours can currently become. Embodied intelligence can be used as a tool to counter- act this phenomenon. Control functionality can be embedded directly into actuators by leveraging the characteristics of fluid flow phenomena. Whilst prior soft robotics work has focused exclusively on actuators operating in a state of transient/no flow (constant pressure), or pulsatile/alternating flow, our work begins to explore the possibilities granted by operating in the closed-loop flow recirculation regime. Here we introduce the concept of FlowBots: soft robots that utilise the characteristics of continuous fluid flow to enable the embodiment of complex control functionality directly into the structure of the robot. FlowBots have robust, integrated, no-moving-part control sys- tems, and these architectures enable: monolithic additive man- ufacturing methods, rapid prototyping, greater sustainability, and an expansive range of applications. Based on three FlowBot examples: a bidirectional actuator, a gripper, and a quadruped with a swimming gait - we demonstrate how the characteristics of flow recirculation contribute to simplifications in fluidic analogue control architectures. We conclude by outlining our design and rapid prototyping methodology to empower others in the field to explore this new, emerging design field, and design their own FlowBots.

Keywords: Biologically-Inspired Robots, Soft Robot Materials and Design, Soft Sensors and Actuators
Abstract: Snake locomotion has served as a source of inspiration for the development of slender robots capable of maneuvering through challenging environments. Within the array of crawling gaits exhibited by snakes, rectilinear locomotion stands out as a prominent method for navigating confined and narrow spaces. In this mode of movement, snakes propel themselves in a straight line by generating a sequential series of waves through the contraction and extension of their muscles, making effective use of their flexible body and the anisotropic friction properties of their ventral skin. To translate this biological principle into robotic systems, there is a need for a framework that seamlessly integrates body deformation with surface interactions. In this study, we bridge this crucial gap by drawing inspiration from three fundamental elements of snake anatomy: the flexible rib structure, the muscular system, and the anisotropic compliant skin. To achieve this objective, we employ flexible mechanical metamaterials comprised of repetitive building blocks, which enable the creation of an origami-like backbone and a kirigami-inspired wrapping to mimic the snake's flexible rib and skin, respectively. These components are activated through an integrated tendon-driven actuation system. We provide a comprehensive account of the bioinspired design and fabrication process, followed by a thorough characterization of our snake robot's performance across various surfaces. The proposed design introduces a scalable multifunctional soft robotic snake module tailored for rectilinear locomotion, showcasing the potential for real-world applications in challenging and confined environments.

Keywords: Cellular and Modular Robots, Biologically-Inspired Robots, Biomimetics
Abstract: The emerging field of biohybrid robotics aims to create the next generation of soft and sustainable robots by using engineered biological muscle tissues integrated with soft materials as artificial muscles (bio-actuators). Both cardiac and skeletal muscle cells can be used for biohybrid actuation. Generally, cardiac bio-actuators take the shape of thin cellular films, while locomotive skeletal muscle bio-actuators form bulk tissues. The geometry of a bio-actuator should be optimized for the type of desired motion, e.g., thin film layers are optimal for swimming actuators mimicking fish. Until now, the geometry of skeletal muscle bio-actuators has been constrained to ring- or block-like tissues generally differentiated around a pair of pillars due to the need to oppose the contraction force exerted during the skeletal muscle differentiation process. In this work, we extend the possible geometry of skeletal muscle bio-actuators by demonstrating a bilayered design that mimics the motion of jellyfish. We take advantage of a volumetric printing method, i.e., xolography, which allows us to micropattern poly(ethyleneglycol) diacrylate and gelatin methacrylate hydrogels to serve as scaffolds for seeding a layer of the skeletal muscle cell matrix. We demonstrate the locomotion speed of our bioactuators is 2.5x faster than previously reported counterparts. In addition, our skeletal bio-actuators outperform most cardiac ones. Further optimization of our bilayer biofabrication for improved reproducibility of the maturation process of the skeletal muscle tissue will pave the way for the next generation of performant skeletal muscle-based actuators for biohybrid robots.

Keywords: Soft Robot Materials and Design, Soft Robot Applications, Biologically-Inspired Robots
Abstract: Tendon-driven continuum robots' inherent flexibility which, while advantageous for manoeuvering through confined spaces, leads to reduced stiffness. In addressing this, we introduce a novel modular backbone design, where each segment consists of units employing compliant mechanisms. Three distinct unit designs are proposed, offering modularity to tailor the backbone stiffness. Each unit can bend upto 90 degrees and is easily manufacturable via 3D printing. A proof-of-concept robot, composed of two segments and 10 modular units, is demonstrated to validate the proposed design. This robot, weighing 78.8 g with a total length of 615.6 mm and a diameter of 40 mm, showcases enhanced stiffness without compromising on flexibility. Through this modular approach, we establish a systematic methodology to customize stiffness in tendon-driven continuum robots, paving the way for broader application and enhanced performance in complex environments.

Keywords: Biologically-Inspired Robots, Tendon/Wire Mechanism, Modeling, Control, and Learning for Soft Robots
Abstract: Octopus arms possess a remarkable capacity for intricate and diverse motions achieved through sequential deformation of the body. This paper aims to reproduce octopus-like reaching movements (extending the arm towards a target) on a cable-driven spiral robot. Our method capitalizes on the frictional interplay between cables and the robot's structure to enable reaching in various directions with only two cables. We propose an analytical friction model capable of calculating tension distribution along the robot's body, where the trajectory of the actuation is encoded in the direction of friction at each contact point between the cables and the robot structures. Through simulation and real-robot experiments, we establish that frictional effects can be harnessed to expand the cable-driven robot's workspace and mobility and accurately replicate octopus-like reaching movements in various scenarios.

Keywords: Soft Robot Applications, Soft Sensors and Actuators
Abstract: Significant progress has been achieved in the development of tensegrity robots with rolling capabilities. However, because rolling robots operate passively due to gravity, they are limited to certain environments. So, our aim is to enhance the versatility of tensegrity robots by modularizing a six-bar tensegrity structure, enabling the robot to operate in more diverse environments. Thus far, we have developed an active and large stretch module and a torsion module with six-bar tensegrity. In this study, we present the design and development of an active and large-bend module for a six-bar tensegrity robot using thin McKibben muscles. Similar to the stretch module developed previously, we employed the 4/3 muscle winding method to create the bend module. This approach enabled approximately 45 deg bending in six different directions. The arrangement of artificial muscles within the bend module is identical to that in the stretch module, allowing not only bending but also stretching and contracting. Further, we successfully constructed a tensegrity arm with bending functionality to demonstrate the capabilities of the bend module. We also conducted a pick-and-place demonstration using the arm to demonstrate the potential application of the bend module.

Keywords: Soft Robot Materials and Design, Soft Robot Applications, Mechanism Design
Abstract: This paper introduces a new type of soft continuum robot, called SCoReS, which is capable of self-controlling continuously its curvature at the segment level; in contrast to previous designs which either require external forces or machine elements, or whose variable curvature capabilities are discrete---depending on the number of locking mechanisms and segments. The ability to have a variable curvature, whose control is continuous and independent from external factors, makes a soft continuum robot more adaptive in constrained environments, similar to what is observed in nature in the elephant's trunk or ostrich's neck for instance which exhibit multiple curvatures. To this end, our soft continuum robot enables reconfigurable variable curvatures utilizing a variable stiffness growing spine based on micro-particle granular jamming for the first time. We detail the design of the proposed robot, presenting its modeling through beam theory and FEA simulation---which is validated through experiments. The robot's versatile bending profiles are then explored in experiments and an application to grasp fruits at different configurations is demonstrated.