Keywords: Soft Robot Applications, Wearable Robots
Abstract: Abstract—TMD case requires correct and sufficient guide to the patients’ mandible movement. It is the most ideal application where robotic device is demanded for the movement training apart from the surgical operations done by the doctors. This paper presents a two-soft-actuator robotic joint design applied on an exoskeleton soft wearable device with substantial improvements over the existing training device. The soft device helps reduce tremendous weight of the device and reserves the system compliance considering patients’ comfort and safety, which brings highly capacity of wearing and self-training. The pneumatic-control-based trajectory planning enables customization of the device for the purpose of satisfying accommodating patients’ individual difference. The design, modeling, fabrication, and validation of an exoskeleton soft wearable device for TMD are presented in detail. Both on-table unit and the on-skull testing are conducted and discussed, showing the remarkable ability of guiding the mandible to move according to the real human nature, paving the way for further clinical applications of such disease. Index terms-TMD, exoskeleton, soft robotics, lightweight, safe, customization.

Keywords: Cellular and Modular Robots, Legged Robots, Soft Robot Materials and Design
Abstract: This work investigates the locomotion of a modular C–legged miniature robot with soft or rigid backbones on smooth, rough, and inclined terrain. SMoLBot–C is a C–legged miniature robot with soft or rigid backbones and foldable modules. The robot's climbing capabilities with soft and rigid C–legs and different backbones on rough terrain with obstacles and the robot's mobility on an inclined surface are compared. Our results show that the C–legged robot with soft legs and soft backbones can climb up to a higher obstacle, and walk on surfaces with higher inclination angles compared to the same robot with rigid legs and backbones, regardless of the number of modules (legs). Additionally, a velocity comparison study using SMoLBot–C operating at two different gaits is conducted. The results show that the robot with soft legs and compliant-I backbones operating with trot gait possesses the highest velocity compared to the other robots with similar leg numbers. Moreover, the effect of a compliant tail on the robot's locomotion on smooth and rough terrains is investigated, where the results show that the robot with the compliant tail is capable of walking on surfaces with higher inclination angles compared to the same robot without a tail. Furthermore, adding a tail to the two-legged SMoLBot–C doubles the maximum scalable obstacle height; the robot with a tail can climb up an obstacle 2 times higher than a module's height. Locomotion analysis in this manuscript provides a better insight into C–legged miniature robots' locomotion with soft or rigid legs while the modular connections' structural stiffness varies from rigid to soft.

Keywords: Hydraulic/Pneumatic Actuators, Search and Rescue Robots, Soft Robot Applications
Abstract: RoBoa is a vine-like search and rescue robot that can explore narrow and cluttered environments such as destroyed buildings. The robot assists rescue teams in finding and communicating with trapped people. It employs the principle of vine robots for locomotion, everting the tip of its tube to move forward. Inside the tube, pneumatic actuators enable lateral movement. The head carries sensors and is mounted outside at the tip of the tube. At the back, a supply box contains the rolled up tube and provides pressurized air, power, computation, as well as an interface for the user to interact with the system. A decentralized control scheme was implemented that reduces the required number of cables and takes care of the low-level control of the pneumatic actuators. The design, characterization, and experimental evaluation of the system and its crucial components is shown. The complete prototype is fully functional and was evaluated in a realistic environment of a collapsed building where the remote-controlled robot was able to repeatedly locate a trapped person after a travel distance of about 10 m.

Keywords: Soft Robot Applications, Medical Robots and Systems
Abstract: Colonoscopy is the gold standard for colorectal cancer diagnosis; however, limited instrument dexterity and no sensor feedback can hamper procedure safety and acceptance. We propose a soft robotic sleeve to provide sensor feedback and additional actuation capabilities to improve safety during navigation in colonoscopy. The robot can be mounted around current endoscopic instrumentation as a disposable “add-on”, avoiding the need for dedicated or customized instruments and without disrupting current surgical workflow. We focus on design, finite element analysis, fabrication, and experimental characterization and validation of the soft robotic sleeve. The device integrates soft optical sensors to monitor contact interaction forces between the colon and the colonoscope and soft robotic actuators that can be automatically deployed if excessive force is detected, to guarantee pressure redistribution on a larger contact area of the colon. The system can be operated by a surgeon via a graphic user interface that displays contact force values and enables independent or coordinated pressurization of the soft actuators upon demand, in case deemed necessary to aid navigation or distend colon tissue.

Keywords: Hydraulic/Pneumatic Actuators, Modeling, Control, and Learning for Soft Robots, Soft Robot Materials and Design
Abstract: Inextensible material inflatables, such as those made from heat-sealable fabric or Mylar, are lightweight, robust, and easily packed into compact spaces and self-deployed. They are commonly made by heat-pressing two sheets together to seal them along a desired curvilinear path. Upon inflation, the sheets wrinkle about the constraints imposed by the seals, giving rise to fascinating and functional shapes. In previous literature, once an inflatable has been manufactured, it can only attain a single inflated shape. Changing task demands of the real world motivate adaptive inflatables that are not fixed to a single deformation. Herein we present a method for creating inflatables that rapidly switch between multiple deformation modes. By patterning conductive fabric on the surface, we bestow the ability to locally form or remove seals during real-time operation. Namely, pulling a vacuum to supply compression force and locally Joule heating regions of the conductive fabric mimics the action of a heat press. Furthermore, we present a finite element model to aid in the analysis and inverse design of inextensible inflatables. Together, the reconfigurable inflatables and inverse model unlock a vast array of programmed inflated shapes with a single enclosed volume.

Keywords: Soft Sensors and Actuators, Soft Robot Materials and Design, Hydraulic/Pneumatic Actuators
Abstract: In the present study, we propose a largely deformable and miniaturized soft actuator that is made by an elastic rubber bladder (called a pouch) with a low-boiling-point liquid. When the temperature of the low-boiling-point liquid reaches 34 ˚C, the liquid inside the pouch evaporates, and the whole structure inflates. Thanks to the proposed fabrication method, we can make a miniaturized pouch of approximately 5 mm in diameter with a thin rubber membrane, and the pouch can inflate to a volume of 86 times or more compared to its initial volume and can generate approximately 20 N at maximum. We calculated the deformation model and developed the fabrication process through investigation of the thickness and the inflation volume of the pouch with respect to the process parameters. We then experimentally characterized the actuator with respect to the generated force, time response, and repeatability of the inflation. We believe that micro elastic pouch motors will contribute to soft robotic systems as a new component as a result of having unique characteristics, such as millimeter size and large deformability.

Keywords: Soft Robot Materials and Design, Compliant Joint/Mechanism
Abstract: For rescue or endoscope applications, snake-like robots have been extensively studied to access and explore confined spaces, such as small-diameter holes or complicated debris. Among them, eversion robot which can evert their flexible surface membrane to extend, exhibit high-mobility performance, even in fragile or soft ground, because they can move without friction or slippage. However, the steering mechanism of these flexible robots elicits the requirement of a rigid environment or complex mechanisms to maintain their curved shape. In this study, we realize a long eversion robot with a selectable extension direction and with a retractable function using an "unsealed" liquid-driven system that takes advantage of a high-density liquid. It comprises a container whose upper-part is open, an eversion robot, and a hollow steering mechanism inserted within the robot. The theoretical analysis of the steering is presented, and the generated friction and required tension under several conditions are measured. Experimentally, we determine the minimum diameter of the steering mechanism, which can minimize friction and enable retraction. The inner tubular mechanism can be operated independently during eversion of the outer membrane structure; therefore, the steering mechanism can be replaced with other structures, such as cameras and inspection sensors.

Keywords: Hydraulic/Pneumatic Actuators, Modeling, Control, and Learning for Soft Robots, Soft Sensors and Actuators
Abstract: The adaptability and inherent safety of soft material robotic systems offer great potential for applications in which their rigid counter parts reach their limits in terms of flexibility and safety. The soft materials used in these systems allow for a safe interaction between humans and robots. Despite advances in the development of soft robots in the recent years, for them to step into application, more research needs to be conducted in the field of accurate modeling and control. For model-based design, path planning, and control computationally efficient models need to be developed that are able to capture the often highly nonlinear deformation behavior of soft actuators. Our previous research showed that artificial neural networks (ANN) are a powerful tool for representig an actuator’s nonlinear kinematics, while at the same time they are computationally efficient. In this article, we propose a transfer learning scheme for minimizing the effort of generating realworld data for neural network training. We showed that the generation of 50 real-world data pairs is sufficient to train an ANN that has a mean accuracy of less than 0.6% with respect to initial actuator length. The resulting ANN is applicable to open and closed loop kinematic control.

Keywords: Modeling, Control, and Learning for Soft Robots, Deep Learning in Robotics and Automation
Abstract: Unlike rigid robots which operate with compact degrees of freedom, soft robots must reason about an infinite dimensional state space. Mapping this continuum state space presents significant challenges, especially when working with a finite set of discrete sensors. Reconstructing the robot's state from these sparse inputs is challenging, especially since sensor location has a profound downstream impact on the richness of learned models for robotic tasks. In this work, we present a novel representation for co-learning sensor placement and complex tasks. Specifically, we present a neural architecture which processes on-board sensor information to learn a salient and sparse selection of placements for optimal task performance. We evaluate our model and learning algorithm on six soft robot morphologies for various supervised learning tasks, including tactile sensing and proprioception. We also highlight applications to soft robot motion subspace visualization and control. Our method demonstrates superior performance in task learning to algorithmic and human baselines while also learning sensor placements and latent spaces that are semantically meaningful.

Keywords: Soft Robot Applications, Soft Sensors and Actuators, Soft Robot Materials and Design
Abstract: Due to their ability to move without sliding relative to their environment, soft growing robots are attractive for deploying distributed sensor networks in confined spaces. Sensing of the state of such robots would add to their capabilities as human-safe, adaptable manipulators. However, incorporation of distributed sensors onto soft growing robots is challenging because it requires an interface between stiff and soft materials, and the sensor network needs to undergo significant strain. In this work, we present a method for adding sensors to soft growing robots that uses flexible printed circuit boards with self-contained units of microcontrollers and sensors encased in a laminate armor that protects them from unsafe curvatures. We demonstrate the ability of this system to relay directional temperature and humidity information in hard-to-access spaces. We also demonstrate and characterize a method for sensing the growing robot shape using inertial measurement units deployed along its length, and develop a mathematical model to predict its accuracy. This work advances the capabilities of soft growing robots, as well as the field of soft robot sensing.

Keywords: Soft Robot Materials and Design, Grippers and Other End-Effectors, Underactuated Robots
Abstract: In this letter we present a design and fabrication framework for soft, underactuated grippers that utilize reconfigurable laminate layers for finger stiffness modulation. The grippers consist of internal flexoskeleton layers, which are hybrid soft-rigid structures composed of a flexible thermoplastic sheet with rigid structures 3D printed directly onto the flexible layer. The flexoskeleton structures are encased in an external silicone skin which enables smooth and soft contact surfaces between the gripper and objects. We designed the flexoskeleton layers to be reconfigurable through layer sliding which enables grasp stiffness modulation by two methods: 1) continuum stiffness modulation through layer sliding to enable strong overlap gripping, and 2) locking and unlocking of flexoskeleton ridge structures which enable stable grasps without actuation. The gripper designs presented here are extremely easy to design and fabricate and present a broad template for future soft grippers.

Keywords: Soft Robot Materials and Design, Modeling, Control, and Learning for Soft Robots, Soft Sensors and Actuators
Abstract: In this work, we propose a novel design methodology to magnify the displacement of a soft robotic system driven by dielectric elastomer actuators (DEAs). The system consists of a 2-degrees of freedom (DoF) module, in which pairs of antagonist rolled DEAs are used to induce a bidirectional bending in a flexible backbone. In the context of 1-DoF DEAs, bistable biasing mechanisms have been extensively used to increase the actuation stroke. In case of multi-DoF DEA systems such as soft robots, however, displacement magnification via bistable concepts has not been investigated so far.

Motivated by the need of designing high-performance DEA soft robots, in this paper we present a method to integrate bistable concepts within the considered 2-DoF module. The key element is represented by the flexible backbone of the structure, whose buckling instability can be properly triggered via the DEAs and exploited to achieve large bending angles.

Based on a physical model of the device, we first derive an energy-based criterion which permits to to differentiate between monostable and bistable configurations. The developed design rule is then exploited to perform a parameter optimization of the structure geometry. Extensive simulation studies are finally conducted to demonstrate the effectiveness of the novel design.

Keywords: Medical Robots and Systems, Soft Robot Applications
Abstract: Vocal folds simulators have been identified as useful tool for understanding the human larynx behavior in pathophysiological conditions. The main objective of the present study is to develop a vocal folds simulator and to provide a quantitative method for monitoring synthetic replica vibration in pathophysiologic conditions, based on electroglottography (EGG). The biorobotic simulator is developed following the composition of a three-layer synthetic model with the addition of a superficial conductive layer in order to acquire an electrical signal to be compared to an EGG signal. Results showed an inverse correlation between vocal folds contact area and resistance during vibration, suggesting that the developed simulator is able to replicate the EGG signal in physiological conditions. This tool has potential for simulating multiple pathologies and clustering the derived EGG signals according to their characteristics, in order to help clinicians in the diagnosis of laryngeal diseases.

Keywords: Soft Robot Materials and Design, Soft Robot Applications, Biologically-Inspired Robots
Abstract: Robotic systems are used in various fields, including environmental exploration and conservation. It may be difficult to retrieve these robots or more cost-effective to discard them after achieving their purpose. Discarding such robots could pose a threat to the environment, especially if they are composed of plastics and metals. Therefore, various motion-producing biodegradable materials and actuators are being researched and developed. However, once biodegradable robots have achieved its purpose, it becomes passive and awaits microbial degradation. In this study, a biodegradable laminated foam-based soft actuator with self-germination ability was developed and its feasibility to return to nature by controlling the rate of degradation was ascertained. Our results indicate that after the actuator achieved its goal, it self-destructed and self-germinated, which confirms its active biodegrading capability through actuation and germination to enter the natural cycle.

Keywords: Sensor-based Control, Modeling, Control, and Learning for Soft Robots, Biologically-Inspired Robots
Abstract: This paper investigates the emergence of high-level behaviors, i.e., support localization, in climbing plants upon the interaction of low-level behaviors, i.e., tropisms, activated by environmental stimuli. Light plays antagonistically in phototropic –attraction to light– and skototropic –attraction to shadow– responses in plant shoots. Here, we hypothesize that climbing plants must find a trade-off between shade avoidance and attraction for support localization. A plant-inspired robotic platform with light-sensing capability is used as a robo-physical system to study the possible role of this environmental stimulus in climbing plants' behavior. Out of this analysis, we propose a biomimetic control that can ultimately be integrated into plant-inspired growing robots for improving their ability in environment exploration and mapping.

Keywords: Modeling, Control, and Learning for Soft Robots, Grasping, Biologically-Inspired Robots
Abstract: Previous research reveals that a flat micropatterned soft pad, which mimics the structure of tree-frog’s toes, increases adhesion when gripping an object in a wet environment. However, soft interfaces may change shape to adapt to curved environments, therefore, it is necessary to clarify the mechanics of wet adhesion in such cases. In this study, we propose a method for evaluation of the adhesive ability of a soft curved interface with a specific micropattern in a concave contact interface. We focused on wet adhesion force in the normal direction on the contact interface in different contact scenarios. The micropattern soft pad used in this analysis has 3600 cells, each has 85 µm×85 µm separated by grooves 15 µm in width ×44 µm in depth. This micropattern soft pad may deform to fit a concave surface. We also compared this micropattern soft pad with a similar soft pad without a micropattern in term of adhesion ability at the interface between the pad and the substrate. Obtained results have good agreement with the estimations, demonstrating that the surface of the micro-patterned pad enhanced contact force at the interface approximately 1÷2 times than the non-parttern surface. This approach can be utilized in evaluation of wet adhesion in grasping objects with curved surface using soft pads with patterned surfaces.

Keywords: Biologically-Inspired Robots, Soft Robot Materials and Design
Abstract: Elastomer based, fabric-reinforced, inflatable soft robots bend when inflated because the fabric-reinforced section has negligible strain compared to the unreinforced section. The inherent displacement mismatch will cause the robot to stretch in the manner of a bi-metallic strip. Using a similar principle, we alter the inflation-dependent motion of various fabric reinforced soft robots by changing the stiffness of different regions of their chamber walls. A concatenated workspace volume of these many robots presents an increase in volume by a factor of six when compared to a robot of uniform rubber composition. A finite element method for a magnetically responsive truss demonstrates an increase in stiffness twofold from a magnetic field strength of 0.01 Tesla to a field strength of 0.02 Tesla. It is postulated that by utilizing these magnetically activated truss configurations as channels within silicone rubber, a fabric-reinforced robot will be able to move about a workspace of similar size by varying magnetic field strength along with the inflation pressure.

Keywords: Biomimetics, Tendon/Wire Mechanism, Soft Robot Applications
Abstract: Although robots with flexible bodies are superior in terms of the contact and adaptability, it is difficult to control them precisely. On the other hand, human beings make use of the surrounding environments to stabilize their bodies and control their movements. In this study, we propose a method for the bracing motion and extension of the range of motion using the environment for the musculoskeletal humanoid. Here, it is necessary to recognize the stability of the body when contacting the environment, and we develop a method to measure it by using the change in sensor values of the body when actively vibrating a part of the body. Experiments are conducted using the musculoskeletal humanoid Musashi, and the effectiveness of this method is confirmed.

Keywords: Compliant Joint/Mechanism, Multifingered Hands, Soft Robot Materials and Design
Abstract: Stiffness control is critical in human manipulation. The ability to transition between a low stiffness state, allowing for compliant interactions with the environment, through to rigid states, where it is possible to exert high forces, enables much functionality. Particle jamming provides an elegant method of modulating stiffness online. We develop an un-actuated anthropomorphic hand, with jamming particles enclosed in the joints surrounded by a moulded silicone skin. This approach to stiffness control also allows for control of posture, through `pre-conditioning' by interacting with the environment in a soft state and then jamming the joints when in a new posture using a single vacuum source and control valve. To demonstrate the capabilities of this new design and fabrication approach, we introduce a `pre-conditioning' algorithm for exploiting the soft/rigid state transition and environmental interactions to fix the hand in a given demand posture. This approach allows for accurate posture control, which translates to high grasping success rates. In conclusion, we demonstrate the advantages of the new design and fabrication approach, where jamming joints can be used to passively perform a variety of tasks through pre-conditioning of the hand posture.

Keywords: Deep Learning in Robotics and Automation, Modeling, Control, and Learning for Soft Robots
Abstract: Soft robots have more passive degrees of freedom (DoFs) than rigid-body robots, which makes controller design difficult. Model-free reinforcement learning (RL) is a promising tool to resolve control problems in soft robotics alongside detailed and elaborate modeling. However, the adaptation of RL to soft robots requires consideration of the unique nature of soft bodies. In this work, a continuum robot arm is used as an example of a soft robot, and we propose an Ensembled Light-weight model-Free reinforcement learning Network (ELFNet), which is an RL framework with a computationally light ensemble. We demonstrated that the proposed system could learn control policies for a continuum robot arm to reach target positions using its tip not only in simulations but also in the real world. We used a pneumatically controlled continuum robot arm that operates with nine flexible rubber artificial muscles. Each artificial muscle can be controlled independently by pressure control valves, demonstrating that the policy can be learned using a real robot alone. We found that our method is more suitable for compliant robots than other RL methods because the sample efficiency is better than that of the other methods, and there is a significant difference in the performance when the number of passive DoFs is large. This study is expected to lead to the development of model-free RL in future soft robot control.

Keywords: Deep Learning in Robotics and Automation, Soft Robot Applications, Perception for Grasping and Manipulation
Abstract: In this paper, we proposed the implementation of an imitation learning algorithm to support a simplified control scheme of a grasping task for a soft gripper. To do so we combined an instance segmentation algorithm, such as the state of the art Mask RCNN, for the object localization in the neural network architecture. The proposed scheme based on combination of scene features mapping and object localization with deep learning supports to grasp objects regardless of target object pose. As a result, the proposed system exploits such advantages of soft grippers such as compliance with the target object shape. We compare the performance of the model to the expert demonstrations use to train the imitation learning algorithm. To do that we changed the configuration of the environment position, pose, and shape of three different target objects, in which the system shows great performance following expert trajectories. Additionally, we tested the grasping successful rate in random environment configurations.

Keywords: Force and Tactile Sensing, Computer Vision for Other Robotic Applications, Soft Sensors and Actuators
Abstract: This paper presents 3D printed structure and a measurement algorithm to sense bending and compression/extension deformations for a soft-bodied robot. The proposed method utilizes a 3D printed structure painted with multiple colors to visualize the deformation. Capturing the deformation state with a cheap web camera allows us to simultaneously measure the bending and compression/extension deformations with the proposed algorithm using the image processing library, OpenCV. The experiments with the prototype demonstrate that the method successfully and easily measures the multi-modal deformation distribution. The proposed method can be a powerful tool to measure the complex and rich multi-modal deformations of soft-bodied robots and design the feedback controllers.

Keywords: Grippers and Other End-Effectors, Soft Robot Applications, Grasping
Abstract: In the field of soft robotics there is still a great need for a versatile, simple, and affordable gripper with a high level of adaptability to unknown objects of different sizes, shapes, and stiffness. Most of the existing soft robotic grippers are complex solutions realized with fluid-mechanically driven actuators, active smart materials, cable-driven actuation, and different form-closure principles. However, soft grippers based on compliant mechanisms are rarely introduced and explored so far. Therefore, we present a novel compliant two-finger gripper mechanism for adaptive and gentle gripping, especially of soft and easily squeezable objects like fruits, vegetables, sweets, and sushi. The structurally inherent adaptability is achieved using an optimally synthesized compliant mechanism in combination with a conventional linear actuator. Furthermore, the two-finger gripper passively realizes pinch (parallel) or/and encompass (power) grasping. It is shown by FEM simulations and confirmed by prototype tests that the developed gripper realizes both pinch and encompass grasping with high adaptability. A special advantage of the gripper is the possibility to achieve gentle food-handling of objects with comparable weight independent of the object shape, size, and position without the need for sensors. Moreover, the precise, safe, and fast manipulation of very delicate objects is exemplarily demonstrated for different sushi pieces using the gripper mechanism with an industrial robotic arm.

Keywords: Grippers and Other End-Effectors, Soft Sensors and Actuators, Force and Tactile Sensing
Abstract: While compliant grippers have become increasingly commonplace in robot manipulation, finding the right stiffness and geometry for grasping the widest variety of objects remains a key challenge. Adjusting both stiffness and gripper geometry on the fly may provide the versatility needed to manipulate the large range of objects found in domestic environments. We present a system for actively controlling the geometry (inflation level) and compliance of Soft-bubble grippers - air filled, highly compliant parallel gripper fingers incorporating visuotactile sensing. The proposed system enables large, controlled changes in gripper finger geometry and grasp stiffness, as well as simple in-hand manipulation. We also demonstrate, despite these changes, the continued viability of advanced perception capabilities such as dense geometry and shear force measurement - we present a straightforward extension of our previously presented approach for measuring shear induced displacements using the internal imaging sensor and taking into account pressure and geometry changes. We quantify the controlled variation of grasp-free geometry, grasp stiffness and contact patch geometry resulting from pressure regulation and we demonstrate new capabilities for the gripper in the home by grasping in constrained spaces, manipulating tools requiring lower and higher stiffness grasps, as well as contact patch modulation.

Keywords: Modeling, Control, and Learning for Soft Robots
Abstract: Underwater soft robots are challenging to model and control because of their high degrees of freedom and their intricate coupling with water. In this paper, we present a method that leverages the recent development in differentiable simulation coupled with a differentiable, analytical hydrodynamic model to assist with the modeling and control of an underwater soft robot. We apply this method to Starfish, a customized soft robot design that is easy to fabricate and intuitive to manipulate. Our method starts with data obtained from the real robot and alternates between simulation and experiments. Specifically, the simulation step uses gradients from a differentiable simulator to run system identification and trajectory optimization, and the experiment step executes the optimized trajectory on the robot to collect new data to be fed into simulation. Our demonstration on Starfish shows that proper usage of gradients from a differentiable simulator not only narrows down its simulation-to-reality gap but also improves the performance of an open-loop controller in real experiments.

Keywords: Tendon/Wire Mechanism, Compliant Joint/Mechanism, Medical Robots and Systems
Abstract: Continuum and soft robots may offer many advantages for use in miniature diagnostic and interventional surgical devices. Tendon-driven continuum manipulators are simple, robust, and can offer large ranges of curvature through actuation. However, obtaining precision motion at the distal end of a tendon-driven soft continuum manipulator while the robot traverses a tortuous or highly curved path remains a challenging task. We present the design concept and initial proof-of-concept prototype evaluation for a flexible, soft-skinned continuum robot that can exhibit both large-scale bending with tendons and precise motion through the rotation of cam-fitted Nitinol rods eccentric with respect to the axial centerline of the robot. We demonstrate experimentally that antagonistic pre-tension in the tendons allows the small-scale motion to be tailored to a specific axis if desired. Experimental results are demonstrated on a prototype which is 102 mm long and can generate 80° of total bending with the tendons and 6 mm of controlled end-effector motion using the cam rotation.

Keywords: Modeling, Control, and Learning for Soft Robots, Legged Robots, Learning and Adaptive Systems
Abstract: Efficient and tractable dynamics models of soft robots are needed for many purposes. For soft robots powered by shape memory actuators, models must simultaneously capture actuator dynamics alongside material deformations. This article examines one possible modeling framework using Gaussian Process (GP) regression, applied in two settings. First, we attempt predictions of bending deformation in a low-dimensional hardware task of a single limb with one shape memory alloy (SMA) actuator, where the SMA temperature is estimated in open loop. Second, we consider locomotion in a simulation of a rolling robot, where the actuator state is known perfectly but the state space is high-dimensional and hybrid. Our locomotion tests examine the applicability of standard model selection choices for a GP, particularly the commonly-used squared exponential (SE) kernel, by studying the hyperparameter optimization problem. We cross-validate one-step-ahead dynamics predictions for both robots. All results have significant noise, but for the single limb in bending, the GP predictions are sufficient to simulate motions over a time horizon of 30 seconds. With further work to address issues with data quality, underfitting, and other sources of error, these dynamics models have the potential to assist in trajectory generation and control for soft robots.

Keywords: Modeling, Control, and Learning for Soft Robots, Soft Robot Applications, Manipulation Planning
Abstract: A lot of works highlight the soft material properties, used in grasping tasks by soft fingers. However, the kinematics as well as the dynamics of these soft fingers are strongly influenced by the material's properties along their soft structure. Due to their compliance, the soft grippers are more often used to achieve form closure grasping which is safer than force closure grasping. One main issue related to soft grasping concerns the shape control of the finger, allowing obtaining perfect compliance when attempting a form closure grasping. In this work, we propose interoperable models based on textbf{Pythagorean Hodograph and Euler-Bernoulli's beam dynamics} to model both dynamics and shape of Fluidic Elastomeric soft fingers. This makes a relationship between the physical actuators and the virtual control points of the parametric Pythagorean Hodograph (PH) curve which drive the finger shape. The PH curve with its finite control points is used to model and control the kinematics of the shape of the soft fingers, characterized by an infinite degree of freedom (DoF). This modeling will allow controlling the position of the virtual control points of soft fingers. The results of this modeling are validated numerically and experimentally with a soft finger made up of Fluidic Elastomeric Actuators (FEA).

Keywords: Modeling, Control, and Learning for Soft Robots, Soft Robot Applications, Simulation and Animation
Abstract: Controlling the configuration of a soft continuum robot arm is challenging due to the hyper-redundant kinematics of such robots. We propose a new model-based, inverse dynamic control approach to this problem that is defined on the configuration state variables of the geometrically exact Cosserat rod model. Our approach is capable of controlling a soft continuum robot to track static or time-varying 3D configurations through bending, torsion, shear, and extension deformations. The controller has a decentralized structure, in which the gain matrices can be defined in terms of the physical and material properties of distinct cross-sections of the robot arm. This structure facilitates its implementation on continuum robot arms composed of independently-controllable segments that have local sensing and actuation. The controller is validated with numerical simulations in MATLAB with a hydrogel-based soft robot arm that can produce the four primary types of deformations. The simulated arm successfully tracks these configurations with average normalized root-mean-square errors (NRMSE) below 7% in all cases. To demonstrate the generality of the control approach, its performance is also validated on a larger simulated robot arm made of silicone.

Keywords: Modeling, Control, and Learning for Soft Robots, Soft Sensors and Actuators, Simulation and Animation
Abstract: The Electro-ribbon Actuator (ERA) is a new class of soft robotic actuator that is light weight, low cost and has high contraction strain. The combination of compliance and dielectrophoretic liquid zipping introduces significant nonlinearity to the ERA and makes modelling challenging. This article introduces a lumped-parameter model (LPM) to simulate the actuation behavior and performance of ERAs. The ERA is made of two flexible opposite insulated electrodes attached together at both ends. The application of a bead of liquid dielectric to the attaching points of the electrodes provides a large force amplification and enables high contraction over 99% and high force-to-weight ratio. The proposed method can simulate a flexible and deformable beam, the main structure of the ERA, predicting the ERA’s deformation under external loads with < 5% errors. It computes the electrostatic force generated between two electrodes and simulates the zipping behaviour. A multiphysics finite element analysis has been performed to validate the model and, a comparison is show with the experimental data in a series of stationary and time-dependent tests. This work provides a rapid route to design and modelling of future soft robots and soft machines

Keywords: Modeling, Control, and Learning for Soft Robots, Wearable Robots, Medical Robots and Systems
Abstract: This paper presents a passive control method for multiple degrees of freedom in a soft pneumatic robot through the combination of flow resistor tubes with series inflatable actuators. We designed and developed these 3D printed resistors based on the pressure drop principle of multiple capillary orifices, which allows a passive control of its sequential activation from a single source of pressure. Our design fits in standard tube connectors, making it easy to adopt it on any other type of actuator with pneumatic inlets. We present its characterization of pressure drop and evaluation of the activation sequence for series and parallel circuits of actuators. Moreover, we present an application for the assistance of postural transition from lying to sitting. We embedded it in a wearable garment robot-suit designed for infants with cerebral palsy. Then, we performed the test with a dummy baby for emulating the upper-body motion control. The results show a sequential motion control of the sitting and lying transitions validating the proposed system for flow control and its application on the robot-suit.

Keywords: Soft Robot Applications, Compliant Joint/Mechanism, Soft Robot Materials and Design
Abstract: Abstract— This paper introduces a method of transmitting actuation forces through soft, curved materials for use in swimming applications. This concept leverages the mechanics of materials to generate highly nonlinear stiffness and buckling behavior that induces an asymmetric paddling gait in the end-effector, a locomotion strategy seen throughout biology. This approach can be used to simplify actuation signals in soft robotic systems. A soft tubular swimming device has thus been developed which utilizes the proposed shape propagation concept; it is actuated by a soft pneumatic actuator which has been adapted to be co-printed within the tubular geometry and change the tube’s curvature when inflated. This work is validated experimentally as well as through the use of FEA and dynamic models, which tell us how altering various design geometry and dynamic parameters can play a role in generating non-zero forward thrust and positive work on the environment. The final, 40 mm long prototype reaches 53 mm/s, 1.33 body lengths per second, when swimming underwater.

Keywords: Soft Robot Applications, Modeling, Control, and Learning for Soft Robots, Physical Human-Robot Interaction
Abstract: In this study, we developed a novel learning framework from physical human-robot interactions. Owing to human domain knowledge, such interactions can be useful for facilitation of learning. However, applying numerous interactions for training data might place a burden on human users, particularly in real-world applications. To address this problem, we propose formulating this as a model-based reinforcement learning problem to reduce errors during training and increase robustness. Our key idea is to develop 1) an advisory and adversarial interaction strategy and 2) a human-robot interaction model to predict each behavior. In the advisory and adversarial interactions, a human guides and disturbs the robot when it moves in the wrong and correct directions, respectively. Meanwhile, the robot tries to achieve its goal in conjunction with predicting the human's behaviors using the interaction model. To verify the proposed method, we conducted peg-in-hole experiments in a simulation and real-robot environment with human participants and a robot, which has an underactuated soft wrist module. The experimental results showed that our proposed method had smaller position errors during training and a higher number of successes than the baselines without any interactions and with random interactions.

Keywords: Soft Robot Applications, Prosthetics and Exoskeletons, Biomimetics
Abstract: One degree-of-freedom (DoF) virtual rolling-contact joint for the prosthetic wrist is proposed in this paper. For prosthetic wrists, the wrist mechanism should basically be lightweight and have a wide range of motion (RoM). In addition, it is desirable to have compliant characteristics to protect amputees or prosthetics from unexpected external forces. The design of the proposed wrist is based on the concept of tensegrity structure which is similar to ligamentous structure combined with bones and ligaments so that it has compliant and lightweight properties. Actually, the proposed mechanism structurally mimics three rows of the human wrist. Since these three rows move simultaneously and create a single-degree-of-freedom in flexion and extension, the proposed wrist covers a wide RoM without any interference between the links, which is similar to the RoM of human wrist. The inherent compliant features of the proposed wrist are validated through experiments.

Keywords: Soft Robot Applications, Robot Companions
Abstract: It is important for social robots to be capable of changing its behavior or other capacity to sustain interaction with the user. In this paper, we discuss changing the softness of the body of a robot. The robot is supposed to be used in haptic interaction contexts such as therapy. To sustain the interest of the user, the robot changes the softness of its body elements and provide the user with variable tactile sensations depending on the haptic interaction history. In this paper, we report the design process of our creating robot prototypes by using a thermoresponsive gel that changes in viscoelasticity with temperature variations. The gel is soft in an inactive state, whereas it becomes hard when it is activated by heat. After identifying a chemical composition that was suitable for building the variable-softness robot, we created octopus-like prototypes having tentacles whose softness could be changed based on tactile sensing. User tests were conducted to check if participants could recognize such softness changes and to discuss the feasibility and prospects of this approach.

Keywords: Soft Robot Applications, Swarms, Modeling, Control, and Learning for Soft Robots
Abstract: The paper proposes a novel concept of docking drones to make this process as safe and fast as possible. The idea behind the project is that a robot with the gripper grasps the drone in midair. The human operator navigates the robotic arm with the ML-based gesture recognition interface. The 3-finger robot hand with soft fingers and integrated touch-sensors is pneumatically actuated. This allows achieving safety while catching to not destroying the drone's mechanical structure, fragile propellers, and motors.

Additionally, the soft hand has a unique technology of providing force information through the color of the fingers to the remote computer vision (CV) system. In this case, not only the control system can understand the force applied but also the human operator. The operator has full control of robot motion and task execution without additional programming by wearing a motion-capture glove with gesture recognition, which was developed and applied for the high-level control of DroneTrap.

The experimental results revealed that the developed color-based force estimation can be applied for rigid object capturing with high precision (95.3%). The proposed technology can potentially revolutionize the landing and deployment of drones for parcel delivery on uneven ground, structure inspections, risque operations, etc.

Keywords: Soft Robot Applications, Underactuated Robots, Grasping
Abstract: Grasping in unstructured environments requires highly adaptable and versatile hands together with strategies to exploit their features to get robust grasps. This paper presents a method to grasp objects using a novel reconfigurable soft gripper with embodied constraints, the Soft ScoopGripper (SSG). The considered grasp strategy, called scoop grasp, exploits the SSG features to perform robust grasps. The embodied constraint, i.e., a scoop, is used to slide between the object and a flat surface (e.g., table, wall) in contact with it. The fingers are first configured according to the object geometry and then used to establish reliable contacts with it. This work introduces an algorithm that, given the object point cloud, computes the best pre-grasp gripper configuration from which to start the scoop grasp strategy. Several experimental trials in different scenarios confirmed the effectiveness of the proposed method.

Keywords: Soft Robot Materials and Design
Abstract: Many soft robots are made of hyperelastic silicone rubbers and usually experience large nonlinear deformations in actions. Accurate material parameters are essential to provide reliable analysis and support robot designs. This paper presents a practical material parameter determination method by iteratively fitting the force-displacement curves measured from two biaxial tension and one uniaxial tension specimens. It reveals the insufficient constraint of one biaxial and one uniaxial test data towards the correct set of material coefficients. Based on three specimens, the material parameter obtained leads to high consistency with the bending validations of four soft fingers, demonstrating the proposed method is capable to accurately determine material properties for hyperelastic soft structures and can be readily used in soft robot designs and analysis.

Keywords: Soft Robot Materials and Design
Abstract: The ability to 3D print soft materials with integrated strain sensors enables significant flexibility for the design and fabrication of soft robots. Hydrogels provide an interesting alternative to traditional soft robot materials, allowing for more varied fabrication techniques.

In this work, we investigate the 3D printing of a gelatin-glycerol hydrogel, where transglutaminase is used to catalyse the crosslinking of the hydrogel such that its material properties can be controlled for 3D printing. By including electron-conductive elements (aqueous carbon black) in the hydrogel we can create highly flexible and linear soft strain sensors. We present a first investigation into adapting a desktop 3D printer and optimizing its control parameters to fabricate sensorized 2D and 3D structures which can undergo >300% strain and show a response to strain which is highly linear and synchronous.

To demonstrate the capabilities of this material and fabrication approach, we produce some example 2D and 3D structures and show their sensing capabilities.

Keywords: Soft Robot Materials and Design, Biologically-Inspired Robots, Biomimetics
Abstract: In this paper, we present an evaluation of swimming efficiency of a previously developed tethered eel-inspired soft robot, when the body suffered from partial damage (i.e., losing control) at its lower region (tail part). Swimming strategy of body damage was constructed based on controlling inputs of four pairs of soft actuators that constitute the eel robot. The tail part will be passive (i.e., without active control). We also varied shifting phase of control inputs in order to seek the best range for creating smooth propagation waves from anterior to posterior part of the robot body, which mimics the movement of an anguilliform swimmer. At two modes (including normal body and passive tail), the robot performed better velocity in the range of shifting phase s from 30% to 50%. Interestingly, the robot's swimming velocity with a passive tail was improved compared to that of the robot with normal state (without damaged parts). We also evaluated cost of transport (COT) in all cases, and the best value of COT is 11.06 created by the robot with passive body. In this mode, the robot also swims with the highest velocity of 14.34cm/s (0.27BL/s). The result in this paper can be utilized to optimize the design and efficiency of swimming elongated soft robots.

Keywords: Soft Robot Materials and Design, Biologically-Inspired Robots, Modeling, Control, and Learning for Soft Robots
Abstract: The evolutionary method is an approach to the difficulties of designing soft-bodied robots. One of the prominent methods is compositional pattern producing network with neuroevolution of augmenting topologies (CPPN-NEAT). However, previous research has focused on single-function robots, and the design of multi-functional robots is still unsolved. This study provides a method for generating multi-functional robots by combining the genotype networks of single-functional robots in a modular manner. The proposed method includes the addition of a weight layer during network combination and the selection of populations with a fitness estimator. We conducted experiments to design voxel-based creatures that can perform two types of tasks in the simulation. Target tasks include terrestrial and aquatic locomotion. The results show that the proposed method was able to search for a form that satisfied the two tasks simultaneously faster than the existing methods. Observations of the generated populations indicated that the proposed method enables the efficient exploration of body morphology. Further, a modularized combination helps focus the exploration in a feasible morphology space. Finally, we fabricated evolved soft creatures in the real world as soft-bodied robots by limiting the arrangement of actuation voxels. We believe that the proposed method of designing a multi-functional robot while utilizing existing single-functional robots will contribute to the automatic design of multi-functional soft robots.

Keywords: Soft Robot Materials and Design, Biologically-Inspired Robots, Tendon/Wire Mechanism
Abstract: A novel method for the generation of travelling waves in soft robots is presented. Here a soft elastomer membrane is embedded with freely sliding nylon tendons. Instead of being anchored to a point on the membrane, these tendons transmit force via friction generated by sliding within the interior of the membrane. This system can produce continuous travelling waves with amplitudes of 27-45mm at wave speeds of up to 23mm/s, using only a single actuator to apply tension to the tendons. The travelling waves were able to move granular material (poppy seeds) as well as a 147g apple. Experimental results demonstrate that the wave progresses through three phases; the initial static phase, followed by the travelling wave phase and finally the (end of travel) blocked phase, with curvature increasing and wave amplitude decreasing across the travelling and blocked phases. This represents wave degradation in which the membrane compresses relative to the tendon, though this did not limit wave travel over the displacements tested. The wave speeds produced were an order of magnitude higher than tendon winding speed suggesting the system acts with natural gearing. This mechanism shows promise for applications in matter transport of unstructured or soft objects and the principle could also be applied to locomoting robots as the low amount of actuators and degrees of control would reduce the complexity and bulkiness of the robots.

Keywords: Soft Robot Materials and Design, Compliant Joint/Mechanism, Soft Robot Applications
Abstract: Tendon-driven continuum robots (TDCR) have been researched to utilize their slender structure, compliance, large workspace, and follow-the-leader deployment capabilities. Improving the performances of TDCR by increasing its length and extensibility is however challenging due to the need of guiding the tendons along the backbone. A standard design uses rigid spacer disks, which mass may cause stability issues in the case of robots with long length. In this paper, we propose a design of lightweight and extensible TDCR taking advantage of extensible paper-based origami structures to guide the tendons along a superelastic nitinol backbone. The four tendons and the backbone control the three degrees of freedom of the robot, yaw, pitch, and axial translation. The robot is composed of multisegments, and the manufacturing process with water-based ink printing provides fast, easily customizable, and scalable fabrication of the robots. The design allows for a reduction of up to 95% of the robot mass with respect to a standard design of TDCR. The prototype demonstrates the extension ratio of more than 10 times and ±167 degrees yaw/pitch angle with 21.9 g weight. The proposed robot design can be applied for search and rescue missions and minimally invasive surgical applications.

Keywords: Soft Robot Materials and Design, Compliant Joint/Mechanism, Soft Robot Applications
Abstract: Soft continuum robots present novel advantages over their rigid, linkage-based counterpart, by expanding the range of achievable kinematic configurations through their flexibility and lack of discrete joints. However, the lack of discrete joints presents challenges for estimation and control of movement in continuum robots. In this paper we present an intermediate approach towards achieving the same versatility of continuum robots while maintaining the traditional control and estimation methods for rigid robots. Our design focuses around a soft tubular element which can be buckled through an internal negative pressure, with the buckling angle set by a confining sleeve. Once the tube is buckled it approximates a revolute joint with torsional stiffness. In this paper we present the design, fabrication, and performance of tube-pinching reconfigurable revolute joints. Through experiment and modeling we identify the appropriate sleeve shape that enables joint axis control to within an error of 5.4°. Force-displacement experiments demonstrate that internal vacuum pressure controls the torsional stiffness of the joint. Lastly, to demonstrate the applicability of soft joint reconfiguration we perform experiments with a flapping tail in water to observe how joint reconfiguration enables different swimming modes.

Keywords: Soft Robot Materials and Design, Grasping, Deep Learning in Robotics and Automation
Abstract: This paper presents a lobster-inspired design of a soft finger's contact surface for grasping with enhanced robustness. The lobsters, while living on the seabed with sediments of various sizes, sources, materials, and life forms exhibit exceptional capabilities in object manipulation underwater using angled-claws with two fingers. By inspecting the geometric features of the lobster tooth, we proposed a series of finger surface designs molded with silicone. We tested the surface friction using traditional methods to shortlist our design pool and further verified their performance using robotic arm grasping against a series of challenging objects from the EGAD, the Evolved Grasping Analysis Dataset. Results show that, in certain cases, the lobster-inspired finger surface design yields an enhanced grasping success rate by 56% at most than those without the surface. Furthermore, we propose a minimum setup for robotic grasping using NVidia Jetson Xavier, Intel RealSense D435, and the proposed soft gripper to be compatible with most robotic manipulators as a cost-effective configuration for shareable and reproducible research.

Keywords: Soft Robot Materials and Design, Modeling, Control, and Learning for Soft Robots, Soft Sensors and Actuators
Abstract: Fiber Reinforced Elastomeric Enclosures (FREEs) have gained significant popularity as a form of soft artificial muscle for the diversified deformation behaviors upon pressurization. In particular, modular FREEs connected in series, demonstrate enhanced flexibility and reconfigurability, thus are adaptable to more complex trajectory tasks. Morphology and motion parameters are strongly coupled for soft manipulators to achieve desired motion behaviors. In contrast to the traditional way of alternating between design optimization in either morphology or actuation space, we seek to co-optimize over parameters in both spaces in an end-to-end fashion with gradient-free optimization. The co-optimization framework allows for faster convergence towards optimal performance given desired trajectory plans. We demonstrated the feasibility of the framework with two simulated tasks: the multiple shape matching task and the octopus reaching task. The former task was further evaluated with real-world experiments.

Keywords: Soft Robot Materials and Design, Modeling, Control, and Learning for Soft Robots, Surgical Robotics: Steerable Catheters/Needles
Abstract: Magnetic soft robots are increasingly popular as they provide many advantages such as miniaturization and tetherless control that are ideal for applications inside the human body or in previously inaccessible locations.

While non-magnetic elastomers have been extensively characterized and modelled for optimizing the fabrication of soft robots, a systematic material characterization of their magnetic counterparts is still missing. In this paper, commonly employed magnetic materials made out of Ecoflex 00-30 and Dragon Skin 10 with different concentrations of NdFeB microparticles were mechanically and magnetically characterized. The magnetic materials were evaluated under uniaxial tensile testing and their behaviour analyzed through linear and hyperelastic model comparison. To determine the corresponding magnetic properties, we present a method to determine the magnetization vector, and magnetic remanence, by means of a force and torque load cell and large reference permanent magnet; demonstrating a high level of accuracy. Furthermore, we study the influence of varied magnitude impulse magnetizing fields on the resultant magnetizations. In combination, by applying improved, material-specific mechanical and magnetic properties to a 2-segment discrete magnetic robot, we show the potential to reduce simulation errors from 8.5% to 5.4%.

Keywords: Soft Robot Materials and Design, Simulation and Animation, Soft Sensors and Actuators
Abstract: The enhancement of stiffness in many soft actuators and architectures is required to produce a large blocking force or to achieve multidimensional deformations. This paper introduces a new method exploiting Kirigami inspired kinematic architecture. Usually, Kirigami structures are made of rigid materials (i.e., thin sheets). Instead, in this study we investigate Kirigami unit cells made of soft material. To validate this approach, different unit cells, having aspect ratio (w/l) ranging from 0.25 to 1 and wall thickness ratio (t/l) ranging from 0.03 to 0.12, are investigated by means of FEM simulations. A fatigue analysis is also carried out to study unit cell reliability for the imposed load. Results show that a wall thickness ratio over 0.08 enhances the axial stiffness rapidly with a good structure stability and a high design life, while with lower wall thickness the maximum strain can be increased. Then, a trade-off of these two parameters can be found in order to tune the mechanical characteristics of the structure (i.e., large deformation ratio with a relevant axial stiffness, high design life), according to the specific application. For instance, with an aspect ratio of 0.5 and wall thickness ratio of 0.09, the axial stiffness is 0.86 N/mm, and the maximum strain is 300%. Noticeably, this approach presents a design strategy for implementing multidimensional motions in complex architectures. Indeed, arranging the unit cells with different aspect ratios would allow the desired behavior (bending, torsional, etc.), while the different wall thicknesses can ensure the desired stiffness.

Keywords: Soft Robot Materials and Design, Soft Robot Applications, Soft Sensors and Actuators
Abstract: The benefits of soft robotic actuators over hard robots have been recognized and are increasingly used in various fields. Soft actuators capable of yielding a high force output often need a tradeoff between its size, extensibility, and weight. This paper presents a novel multilayer extending actuator (MEA) that is thin and light but also capable of high extension and high force output. When actuated, the MEA has visible layers of alternate inelastic and elastic elastomer layer. The MEA is fabricated using silicone elastomers and operated by pneumatic pressure. The inelastic layers help increase the actuator’s durability and extension by inhibiting the elastic layers to expand radially. This makes the MEA stronger, capable of a tip force more than 400 times its weight, and an extension of 5 times its body depth. The design and fabrication of the system are described, and a theoretical model is introduced for predicting the extension and force output. Finally, a simple demonstration of its modularity and application in operating a robotic arm is presented. The MEA can be conceptualized as a spring system as it helps to increase the total extension when connected in series while helping to increase the total force when connected in parallel instead.

Keywords: Soft Robot Materials and Design, Soft Robot Applications, Tendon/Wire Mechanism
Abstract: This work presents a novel concept to develop mobile robots enabling crawling locomotion in tubular environment. Chain-like systems are designed by serial cascading a uniform tensegrity module. Inspired by the movement of worms in nature, an undulating shape change of the system is targeted to generate locomotion. The shape changeability of an exemplary tensegrity module due to internal actuation is examined in simulations and experiments. A prototype consisting of these tensegrity modules is manufactured and the locomotion principle is verified in experiments. Comparing to existing prototypes this approach enables an enhanced compliance due to the modular assembly of tensegrity structures.

Keywords: Soft Robot Materials and Design, Soft Sensors and Actuators, Modeling, Control, and Learning for Soft Robots
Abstract: Soft robots often show a superior power-to-weight ratio using highly compliant, light-weight material, which leverages various bio-inspired body designs to generate desirable deformations for life-like motions. In this paper, given that most material used for soft robots is light-weight in general, we propose a volumetrically enhanced design strategy for soft robots, providing a novel design guideline to govern the form factor of soft robots. We present the design, modeling, and optimization of a volumetrically enhanced soft actuator (VESA) with a linear and rotary motion, respectively, achieving superior force and torque output, linear and rotary displacement, and overall extension ratio per unit volume. We further explored VESA's proprioceptive sensing capability by validating the output force and torque through analytical modeling and experimental verification. Our results show that the volumetric metrics hold the potential to be used as a practical design guideline to optimize soft robots' engineering performance.

Keywords: Soft Robot Materials and Design, Tendon/Wire Mechanism, Grippers and Other End-Effectors
Abstract: Variations in size and geometry of objects and the need for a delicate grasp are major challenges for the development of grippers for the agri-food industry. To address this, we present a novel reconfigurable soft (ReSoft) gripper based on monolithic silicone fingers and differential mechanism. One motor is used to achieve different configurations for the fingers (spread action) and a second motor is used to obtain the closing motion of fingers (grip action) using cables and differential mechanism. The combined effect of the softness of the fingers, underactuation of the system, and the differential mechanism allow the fingers to adapt to the shape of the object for a delicate and firm grasp. The spread action helps to rearrange the position and orientation of fingers and thereby increases the adaptability of the gripper for grasping objects of various geometries. Hence, a versatile soft gripping is achieved by using only two motors. We performed a set of experiments to quantify some of the performance characteristics and to demonstrate the grasping potential of the gripper.

Keywords: Soft Sensors and Actuators
Abstract: Knitted SMA actuators provide greater actuation stroke than single-strand SMA wire actuators by leveraging its knitted structure. However, due to short-circuiting through interlacing knit loops, existing knitted SMA sheet actuators are unsuitable for joule-heating actuation when uniform contractile actuation is desired. We explore an axially symmetric tubular i-cord knitted actuator as a possible solution. The fabrication process of an i-cord knitted SMA actuator and its electrical, thermal, and mechanics models are presented. After modifying existing models for single-strand SMA wire and adjusting their parameters, the proposed electrical, thermal, and mechanics models were verified with experimental results.

Keywords: Soft Sensors and Actuators, Additive Manufacturing, Wearable Robots
Abstract: In this paper, we developed a piezoresistive auxetic sensor structure based on a silicone elastomer and carbon-based conductive thermoplastic elastomer fiber sensor (CTPE fiber). Liquid silicone has been used as the matrix material. In addition silicone has been mixed with silica filler to tailor the stiffness of an auxetic elastic structure that improved the sensor behavior of silicone-based CTPE fiber composites. The 2D auxetic structures with and without silica fillers have been successfully printed with the direct ink writing method. The piezoresistive fiber was integrated and the auxetic structure were embedded in the silicone matrix in a second step, via casting method. To detect the electrical signal behavior of the integrated fiber sensor, the hybrid manufactured auxetic fiber sensor composite was investigated using dynamic cycle testing between 0 and 20% strain. Using silicone with silica filler for the printing of the auxetic structure, the sensor behavior of the piezoresistive fiber elastomer composite was improved and a secondary peak of the sensor signal could be avoided at low strains. Unfortunately, a constant gauge factor between 0 and 20% strain could not be obtained by implementing the auxetic structure element inside the CTPE fiber composite. However, this structure can already be integrated into a watchband and used for gesture-controlled applications.

Keywords: Soft Sensors and Actuators, Modeling, Control, and Learning for Soft Robots
Abstract: This paper focuses on a novel polyurethane-based soft actuator that is fabricated by an electrospinning process. The actuator is a bundle of aligned nanofibers of a polyurethane solution and a salt, which acts as a conductive filler. From the same bundle, three actuators are obtained. Electromechanical tests are performed on one specimen to evaluate the axial displacements and axial forces generated by the actuator, when stimulated by an external electric field. The data generated during the electromechanical tests are used to identify the non-linear dynamics of the specimen by means of a multi- layer perceptron. Subsequently, the identified dynamic model is used to design a position control architecture that controls the applied electric field to regulate the axial displacement of a second specimen. Finally, as a proof of concept for the usability of the nanofiber bundle soft actuator, a third specimen is tested in a robotic prototype, in which a rigid link moves thanks to the actuator’s contraction capability.

Keywords: Soft Sensors and Actuators, Sensor Fusion, Modeling, Control, and Learning for Soft Robots
Abstract: Soft robotic sensors have been limited in their applications due to their highly nonlinear time variant behavior. Current studies are either looking into techniques to improve the mechano-electrical properties of these sensors or into modelling algorithms that account for the history of each sensor. Here, we present a method for combining

multi-material soft strain sensors to obtain equivalent higher quality sensors; better than each of the individual strain sensors. The core idea behind this work is to use a combination of redundant and disjoint

strain sensors to compensate for the time-variant hidden states of a soft-bodied system, to finally obtain the true strain state in a static

manner using a learning-based approach. We provide methods to develop these variable sensors and metrics to estimate their dissimilarity and efficacy of each sensor combinations, which can double down as a benchmarking tool for soft robotic sensors. The proposed approach is experimentally validated on a pneumatic actuator with embedded soft strain sensors. Our results show that static data from a combination of

nonlinear time variant strain sensors is sufficient to accurately estimate the strain state of a system.

Keywords: Soft Sensors and Actuators, Soft Robot Applications, Rehabilitation Robotics
Abstract: Stroke, total knee replacement, and osteoarthritis are common causes that can result in temporary/permanent lower-limb motion impairments. Such patients require physiotherapy interventions to recover their lost motion capabilities. With the increasing number of such patients, there is also an ever-increasing demand on physiotherapists. Hence, there is a need for physiotherapy assistive devices that will reduce the burden on the physiotherapists and allow them to cater to a larger number of patients. One such requirement is to provide assistance for knee flexion and extension. Soft actuators present a novel solution for developing such devices. We propose a novel, low-profile (5,mm), contractile vacuum actuator that, is lightweight (2,g), can provide a high force-to-weight ratio (230), with an effective force of 4.5,N. This proposed actuator comprises an airtight pouch made of thermoplastic polyurethane (TPU) fabric with a helical spring skeleton. Once the air inside the pouch is evacuated, the actuator contracts longitudinally along the spring. This single actuator is combined to fabricate multi-actuator configurations of 3-,and 5-,actuators capable of producing 8,N and 14,N respectively. Both the single and multi-actuator configurations are experimentally evaluated to obtain isometric, isotonic, and isobaric performance characteristics. A numerical model is also developed to predict the multi-actuator isometric performance. The multi-actuator configurations were combined to evaluate the performance in a model leg extension test setup.The proposed actuators were able to lift a 0.8,kg leg model by 17degree ,in extension at a vacuum pressure of 40 kPa (abs.)

Keywords: Soft Sensors and Actuators, Soft Robot Materials and Design
Abstract: Large-deformation capacitive stretch sensors have proven to be a reliable sensing method for soft robots and wearables. However, the measurement rate at which capacitance is accurately measured is often limited by the relatively high resistance of the conductive composite electrodes. At high measurement frequencies, the measured capacitance underestimates the real capacitance, resulting in inaccurate strain estimation. High measurement rates allow for fast sensor feedback, which is essential for closed loop control of fast moving systems. In this work, we show that the measurement rate of elastic capacitive sensors with conductive composite electrodes can be increased by cyclic pre-stretching of the sensors before each use.

Keywords: Soft Sensors and Actuators, Soft Robot Materials and Design
Abstract: Air-hose-free thin McKibben muscles with a soft polymer electrolyte fuel cell (PEFC) tube can realize electrically controlled actuation with a soft body. However, they experience the following problems: low response speed, fast deterioration of PEFC tube electrodes, and the requirement for high driving voltage. In this paper, we propose two breakthrough technologies that improve the performance of air-hose-free McKibben muscles. One is an Au/Pt double-layer electrode, and the other is an expanding internal chamber. We use these technologies to successfully increase the expansion rate and decrease the excessive pressure rise inside a PEFC tube. The resistance of the PEFC tube with the Au/Pt double-layer electrodes increases only slightly after it is bent eight times. Theoretical calculations show that the installation of the expanding internal chamber can increase the pressure for contracting the muscle by up to 300%. The improved air-hose-free thin McKibben muscle achieves a maximum contraction ratio of 22%and a contraction time of 35 s. The contraction ratio is approximately four times larger than that obtained in previous research. The newly proposed air-hose free thin McKibben muscle is applied to an antagonistic drive robot arm to demonstrate its applicability in robotic systems. The prototype of the antagonistic drive robot arm is successfully operated with a rotation speed of 2.4 deg/s and a maximum displacement angle of 83 deg.

Keywords: Soft Sensors and Actuators, Soft Robot Materials and Design, Force and Tactile Sensing
Abstract: The food industry is dependent on human labor for tasks that require tactile sensing, due in part to a lack of robotic sensors that are delicate enough to interact with food. In this paper we present the design, modeling, and performance of a durometer constructed with soft materials. We performed experiments to investigate the sensor's material selection, repeatability, drift, probing speed, and calibration. We also integrated the sensor into a commercial soft robotic gripper and used it to measure the hardness of an orange. The orange would be damaged by a traditional durometer, but the soft durometer left no visible marks. These results suggest that soft robotic sensors can benefit the food industry and overcome limitations associated with the interaction between robotic systems and fragile objects.