Design Of Soft Robots Research Articles

A Versatile Topology-Optimized Compliant Actuator for Soft Robotic Gripper and Walking Robot.

The remarkable interaction capabilities of soft robots within various environments have captured substantial attention from researchers. In recent years, bionics has provided a rich inspiration for the design of soft robots. Nevertheless, predicting the locomotion of soft actuators and determining material layouts solely based on intuition or experience remain a formidable challenge. Previous actuators predominantly targeted separate applications, leading to elevated costs and diminished interchangeability. The objective of this article is to extract the common requirements of diverse application domains and develop a versatile compliant actuator. A mathematical model of the compliant mechanism is proposed under the framework of topology optimization, resulting in an optimal distribution of both structure and material. Through comparison with empirical and semioptimal designs, the results show that the proposed versatile actuator has the advantages of both stiffness and flexibility. We propose an associative design strategy for soft grippers and walking robots. The soft gripper can perfectly complete adaptive grasping of objects with varying sizes, shapes, and masses. The successful in-water gripping experiment underscores the robust cross-medium operational capabilities of the soft gripper. Notably, our experimental results show that the walking robot can move quickly for 5 cycles in 8.25 s and can guarantee the control accuracy of continuous motion. Moreover, the robot swiftly switches walking directions within a mere 0.45 s. The optimization and design strategy presented in this article can furnish novel insights for shaping the next generation of soft robots.

Preface

Intelligence emerging from interactions between the body and the environment at the material and morphological levels attracts the attention of many different research communities. Researchers with engineering, social sciences, computer sciences, biology, and materials science backgrounds all study and understand embodied intelligence from their own perspectives. Therefore, providing a common definition of ‘Embodied Intelligence’ remains challenging.Furthermore, the intricate connection between the body and mind remains an unresolved philosophical question. Exploring this relationship not only deepens our understanding of animals and humans but also serves as a crucial element in the development of embodied artificial intelligence. By unraveling this connection, we can pave the way for creating robots endowed with practical intelligence. The long-standing philosophical debates surrounding consciousness have gained utmost significance in the realm of AI-powered machines.This book presents a comprehensive selection of papers authored by renowned researchers who participated in the 2nd International Conference on Embodied Intelligence held on 23-25 March, 2022, and the Embodied Intelligence Workshop, held at the RoboSoft 2022 Conference. This collection features reviews and perspectives articles, as well as the original research. The collection aims to stimulate interdisciplinary discussions and presenting novel ideas on the topic of Embodied Intelligence. By exploring the latest concepts and future directions in this field, these papers offer fresh perspectives and help paving the way for breakthroughs in both understanding and practical implementation.The central focus of this year’s conference revolved around two key topics: the significance of modeling in the design of soft robots and the pivotal role of the brain in embodied agents. The design of soft robots can follow a modeling-based approach using formal models and optimization techniques, similar to traditional rigid robotics. However, accurately modeling the behavior of soft robots is challenging. An exploratory approach inspired by biological organisms involves an iterative process, drawing insights from their locomotion and other behaviors. The role of the brain and central nervous system in bio-inspired robotics is significant, with self-organization and embodied intelligence allowing problem-solving without extensive centralized control. Researchers emulate cognitive processes observed in animals to develop intelligent robots, requiring advances in computational models and algorithms. Finding a good balance between exploiting the physical body and relying on computational capabilities remains an open topic of discussion.The book consists of a wide range of topics surrounding Embodied Intelligence and is loosely structured in two parts. The first set of chapters discuss the principles and perspectives on Embodied Intelligence and the links to robotics and artificial life. In the second half of the book, there is discussion on the connection between humans and Embodied Intelligence and the surrounding philosophy, psychology and cognitive science which ground and situate the research.We express our sincere gratitude to all the participants of the Conference and Workshop participants, the authors, and the reviewers for their outstanding contributions to this volume.

Imitation and reinforcement learning to control soft robots: a perspective

It would not be an over-stretch to appraise soft robotics as one of the most sizzling topic in this era, owing to its unparalleled performance in terms of exhibited deformability, soft-interaction and luscious dexterity. In spite of that, we see minimal applications of this class around us. We believe the reason roots in the gap between design and fabrication of the soft robots and the capability to control them. The remedy to this imbalance, we believe, is a necessity for a climacteric rise in the capability to control them. The control, however poses challenges due to virtually infinite degrees of freedom of soft robot design, in terms of modelling the behavior of the robot, modelling its interaction with the environment or the environment’s effect on the robot. These challenges provoke the preponderant need for solutions that either can work with the inaccurate models of the robot obtained or avoid it altogether. To answer what can be used with these limitations we present here two potential classes of algorithms from machine learning capable of performing well under just the listed conditions: reinforcement learning (RL) can provide a solution in the form of a policy to control a platform with sophisticated dynamics even when the presented environment to train said policy has questionable accuracy, while Imitation Learning (IL) trains a policy while avoiding the need of a model or its constituent parts altogether and a policy is learned based on the teachings of an expert.

Task-Mediated Design: A latent space for dexterous soft robotic design

Soft robotics has created a paradigm shift within robotic grasping and manipulation. Rather than using complex control policies and path planning methods to undertake grasp objects, soft robots use their embodied intelligence to deform around an object and securely hold it. Yet despite major advances in the field in recent years, there remains an absence of practical methods for designing new high performing soft manipulators. In this perspective, we propose a novel task-mediated approach to soft manipulator design and discuss its application to robust and dexterous manipulation. The task-mediated approach first abstracts the manipulation task into a characteristics latent space, then designs a soft robot to minimise the distance between the actual performance and characteristic latent variables. In conjunction with state-of-the-art generative design tools and simulators, this approach can accelerate the development of bespoke and general purpose manipulators

Characterization of Temperature and Humidity Dependence in Soft Elastomer Behavior.

Soft robots are predicted to operate well in unstructured environments due to their resilience to impacts, embodied intelligence, and potential ability to adapt to uncertain circumstances. Soft robots are of further interest for space and extraterrestrial missions, owing to their lightweight and compressible construction. Most soft robots in the literature to-date are made of elastomer bodies. However, limited data are available on the material characteristics of commonly used elastomers in extreme environments. In this study, we characterize four commonly used elastomers in the soft robotics literature-EcoFlex 00-30, Dragon Skin 10, Smooth-Sil 950, and Sylgard 184-in a temperature range of -40°C to 80°C and humidity range of 5-95% RH. We perform pull-to-failure, stiffness, and stress-relaxation tests. Furthermore, we perform a case study on soft elastomers used in stretchable capacitive sensors to evaluate the implications of the constituent material behavior on component performance. We find that all elastomers show temperature-dependent behavior, with typical stiffening of the material and a lower strain at failure with increasing temperature. The stress-relaxation response to temperature depends on the type of elastomer. Limited material effects are observed in response to different humidity conditions. The mechanical properties of the capacitive sensors are only dependent on temperature, but the measured capacitance shows changes related to both humidity and temperature changes, indicating that component-specific properties need to be considered in tandem with the mechanical design. This study provides essential insights into elastomer behavior for the design and successful operation of soft robots in varied environmental conditions.

Shape-Programmable Liquid-Crystalline Polyurethane-Based Multimode Actuators Triggered by Light-Driven Molecular Motors.

In recent years, light-driven soft actuators have been rapidly developed as enablers in the fabrication of artificial robots and biomimetic devices. However, it remains challenging to amplify molecular isomerization to multiple modes of macroscopic actuation with large amplitude and complex motions. Here, a strategy is reported to build a light-responsive liquid-crystalline polyurethane elastomer by phototriggered overcrowded alkene-based molecular motors. A trifunctional molecular motor modified with an ethylene glycol spacer on the rotor and stator functions as a crosslinker and unidirectional stirrer that amplifies molecular motion into macroscopic movement. The shape-programmable polymeric film presents superior mechanical properties and characteristic shape-memory effect. Furthermore, diverse modes of motions including bending, unwinding, and contracting with tunable actuation speed over a wide range are achieved. Such research is hoped to pave a new way for the design of advanced light-responsive soft actuators and robots.

Materializing Autonomy in Soft Robots across Scales

The impressive capabilities of living organisms arise from the way autonomy is materialized by their bodies. Across scales, living beings couple computational or cognitive intelligence with physical intelligence through body morphology, material multifunctionality, and mechanical compliance. While soft robotics has advanced the design and fabrication of physically intelligent bodies, the integration of information‐processing capabilities for computational intelligence remains a challenge. Consequently, perception and control limitations have constrained how soft robots are built today. Progress toward untethered autonomy will require deliberate convergence in how the field codevelops new materials, fabrication methods, and control strategies for soft robots. Here, a new perspective is put forward: that researchers should use tasks alone to impose material and information constraints on soft robot design. A conceptual framework is proposed for a task‐first design paradigm that sidesteps limitations imposed by control strategies. This framework allows emergent synergies between material and information processing properties of soft matter to be readily exploited for task‐capable agents. Particular attention is paid to the scale dependence of solutions. Finally, an outlook is presented on emerging research opportunities for achieving autonomy in future soft robots as large as elephant trunks and as small as paramecia.

A biomimetic smart kirigami soft metamaterial with multimodal remote locomotion mechanisms

Several efforts have been made to develop walking smart soft robots through different strategies such as the use of complex aligned magneto-active materials. Here, we show a simple approach for the design of a smart soft robot using an elastomer film with randomly distributed ferrimagnetic nanoparticles able to be remotely controlled by a magnetic field. The magneto-active robot has a rotating-square kirigami geometry resulting in a flexible smart auxetic metamaterial (i.e., a negative Poisson-ratio structure). Alongside the standard translational locomotion on a smooth-surface under a steady magnetic force, the auxetic kirigami structure mimics the crawling-locomotion of worms over a high-roughness surface under an oscillatory horizontal field, even climbing vertical-obstacles. A theoretical understanding for this new locomotion mechanism stresses the relevance of the kirigami metamaterial design and the ferrimagnetic response of the particles. The soft robot can also transport a payload having weights higher than the weight of the smart elastomeric film. The smart auxetic structure further presents a rolling locomotion by properly orienting the magnetic field, meaning multiple remote locomotion mechanisms.

Modeling and Simulation of Dynamics in Soft Robotics: a Review of Numerical Approaches

Abstract Purpose of review In this review, we briefly summarize the numerical methods commonly used for the nonlinear dynamic analysis of soft robotic systems. The underlying mechanical principles as well as the geometrical treatment tailored for soft robots are introduced with particular emphasis on one-dimensional models. Additionally, the review encompasses three-dimensional frameworks, available simulation packages, and various types of interaction models, shedding light on the design, actuation, motion control, and internal and external forces of soft robots. Recent findings Reduced-order models can offer high efficiency in characterizing nonlinear deformations, allowing convenient tailoring based on specific structural and material configurations. For pursuing high simulation accuracy and detailed mechanics, the finite element method proves to be a valuable tool through numerous off-the-shelf platforms. Furthermore, machine learning has emerged as a promising tool to effectively address the challenges within the mechanics community. Summary A wide range of kinematic and dynamic numerical models is available for simulating the behaviors of soft robots, offering exceptional adaptability to different geometries and structures based on existing modeling theories and numerical solution algorithms. However, the trade-off between computational complexity and simulation accuracy remains a challenge in achieving fast, accurate, and robust control of soft robots in complex environments.

Omnidirectional compliance on cross-linked actuator coordination enables simultaneous multi-functions of soft modular robots

Earthworms have entirely soft bodies mainly composed of circular and longitudinal muscle bundles but can handle the complexity of unstructured environments with exceptional multifunctionality. Soft robots are naturally appropriate for mimicking soft animal structures thanks to their inherent compliance. Here, we explore the new possibility of using this compliance to coordinate the actuation movements of single-type soft actuators for not only high adaptability but the simultaneous multifunctionality of soft robots. A cross-linked actuator coordination mechanism is proposed and explained with a novel conceptual design of a cross-linked network, characterization of modular coordinated kinematics, and a modular control strategy for multiple functions. We model and analyze the motion patterns for these functions, including grabbing, manipulation, and locomotion. This further enables the combination of simultaneous multi-functions with this very simple actuator network structure. In this way, a soft modular robot is developed with demonstrations of a novel continuous-transportation mode, for which multiple objects could be simultaneously transported in unstructured environments with either mobile manipulation or pick-and-place operation. A comprehensive workflow is presented to elaborate the cross-linked actuator coordination concept, analytical modeling, modular control strategy, experimental validation, and multi-functional applications. Our understanding of actuator coordination inspires new soft robotic designs for wider robotic applications.

Performance enhancement of the soft robotic segment for a trunk-like arm.

Trunk-like continuum robots have wide applications in manipulation and locomotion. In particular, trunk-like soft arms exhibit high dexterity and adaptability very similar to the creatures of the natural world. However, owing to the continuum and soft bodies, their performance in payload and spatial movements is limited. In this paper, we investigate the influence of key design parameters on robotic performance. It is verified that a larger workspace, lateral stiffness, payload, and bending moment could be achieved with adjustments to soft materials' hardness, the height of module segments, and arrayed radius of actuators. Especially, a 55% increase in arrayed radius would enhance the lateral stiffness by 25% and a bending moment by 55%. An 80% increase in segment height would enlarge 112% of the elongation range and 70 % of the bending range. Around 200% and 150% increments in the segment's lateral stiffness and payload forces, respectively, could be obtained by tuning the hardness of soft materials. These relations enable the design customization of trunk-like soft arms, in which this tapering structure ensures stability via the stocky base for an impact reduction of 50% compared to that of the tip and ensures dexterity of the long tip for a relatively larger bending range of over 400% compared to that of the base. The complete methodology of the design concept, analytical models, simulation, and experiments is developed to offer comprehensive guidelines for trunk-like soft robotic design and enable high performance in robotic manipulation.

Vibration of a Liquid Crystal Elastomer Spring Oscillator under Periodic Electrothermal Drive.

The oscillations of electrically actuated thermally-responsive liquid crystal elastomer (LCE) microfibers under cyclic electric actuation have been discovered in recent experiments. Periodic electric actuation is a common method of active control with potential applications in the fields of micro-actuators. In this paper, the vibration behavior of LCE spring oscillator under periodic electrothermal drive is studied theoretically. Based on the dynamic LCE model, the dynamic governing equation of the LCE spring oscillator is established, and the time history curves of the vibration are obtained by numerical calculations. The results show that the periodic electrothermal drive can cause periodic vibration of the LCE spring oscillator. With the increase of time rate, the vibration amplitude increases first and then decreases. In a small damping system, there exist optimal sets of electrothermal drive period and electrothermal drive time rate to maximize the system amplitude. For the optimum periodic mode, the vibration amplitude of the spring oscillator is affected by the current heat, damping coefficient, gravital acceleration, spring constant and shrinkage coefficient, but not by the initial velocity. The application examples of LCE materials show that periodic electrothermally driven LCEs have promising applications. The results of this study are instructive for the design of soft robots and LCE-based electric locomotives.

Pangolin-inspired untethered magnetic robot for on-demand biomedical heating applications

Untethered magnetic miniature soft robots capable of accessing hard-to-reach regions can enable safe, disruptive, and minimally invasive medical procedures. However, the soft body limits the integration of non-magnetic external stimuli sources on the robot, thereby restricting the functionalities of such robots. One such functionality is localised heat generation, which requires solid metallic materials for increased efficiency. Yet, using these materials compromises the compliance and safety of using soft robots. To overcome these competing requirements, we propose a pangolin-inspired bi-layered soft robot design. We show that the reported design achieves heating > 70 °C at large distances > 5 cm within a short period of time <30 s, allowing users to realise on-demand localised heating in tandem with shape-morphing capabilities. We demonstrate advanced robotic functionalities, such as selective cargo release, in situ demagnetisation, hyperthermia and mitigation of bleeding, on tissue phantoms and ex vivo tissues.

Spiral‐Shape Fast‐Moving Soft Robots

AbstractSoft robots typically exhibit limited agility due to inherent properties of soft materials. The structural design of soft robots is one of the key elements to improve their mobility. Inspired by the Archimedean spiral geometry in nature, here, a fast‐moving spiral‐shaped soft robot made of a piezoelectric composite with an amorphous piezoelectric vinylidene fluoride film and a layer of copper tape is presented. The soft robot demonstrates a forward locomotion speed of 76 body length per second under the first‐order resonance frequency and a backward locomotion speed of 11.26 body length per second at the third‐order resonance frequency. Moreover, the multitasking capabilities of the soft robot in slope climbing, step jumping, load carrying, and steering are demonstrated. The soft robot can escape from a relatively confined space without external control and human intervention. An untethered robot with a battery and a flexible circuit (a payload of 1.665 g and a total weight of 1.815 g) can move at an absolute speed of 20 mm s−1 (1 body length per second). This study opens a new generic design paradigm for next‐generation fast‐moving soft robots that are applicable for multifunctionality at small scales.

Motion Analysis and Experiment of Multiple Magnetic Small-Scale Soft Robots

Since magnetic field is penetrating and harmless to human body, magnetic soft robots driven by magnetic field have great potential in medical fields. Thus, magnetic soft robots have attracted wide attention. However, the current researches mainly focus on the design of a single magnetic soft robot. Multiple magnetic soft robots also deserve to be studied due to their applications in collaborative operation. This paper presents a new design and fabrication method of multiple magnetic small-scale soft robots with different magnetic strength, size, and length-width ratio. The robots can be controlled to move in different motion modes and motion states under identical magnetic field. By analyzing their magnetic response property, which is the switching conditions between the two motion modes, and analyzing their states of the walking motion, two robots are selected from a batch of fabricated robots to carry out experiment. The results show that the two robots can move in different motion modes in the identical magnetic field.

Modeling of soft fluidic actuators using fluid–structure interaction simulations with underwater applications

Soft robots have been developed for a variety of applications including gripping, locomotion, wearables and medical devices. For the majority of soft robots, actuation is performed using pneumatics or hydraulics. Many previous works have addressed the modeling of these fluid-driven soft robots using static finite element simulations where the pressure inside the actuator is assumed to be constant and uniform. The assumption of constant internal pressure is a useful simplification but introduces significant errors during events such as pressurization, depressurization, and transient loads from a liquid environment. Applications that use soft actuators for locomotion or propulsion operate using a sequence of transient events, so accurate simulation of these events is critical to optimizing performance. To improve the simulation of soft fluidic actuators and enable the modeling of both internal and external fluid flow in underwater applications, this work describes a fully-coupled, three-dimensional fluid–structure interaction simulation approach, where the pressure and flow dynamics are explicitly solved. This approach provides a realistic simulation of soft actuators in fluid environments, and permits the optimization of transient responses, which may be due to a combination of environmental fluid loads and non-uniform pressurization. The proposed methods are demonstrated in a number of case studies and experiments for a range of actuation and both internal and external inlet flow configurations, including bending actuators, a soft robotic fish fin for propulsion, and experimental results of a bending actuator in a high-speed fluid, which correlate closely with simulations. The proposed approach is expected to assist in the design, modeling, and optimization of bioinspired soft robots in underwater applications.

Kinematic modeling and design of untethered soft mobile magnetic robots with multiple support sections

Kinematic modeling and design of untethered soft mobile magnetic robots with multiple support sections

Kinetostatic Modeling of Soft Robots: Energy-Minimization Approach and 99-Line MATLAB Implementation.

Soft robots have received a great deal of attention from both academia and industry due to their unprecedented adaptability in unstructured environment and extreme dexterity for complicated operations. Due to the strong coupling between the material nonlinearity due to hyperelasticity and the geometric nonlinearity due to large deflections, modeling of soft robots is highly dependent on commercial finite element software packages. An approach that is accurate and fast, and whose implementation is open to designers, is in great need. Considering that the constitutive relation of the hyperelastic materials is commonly expressed by its energy density function, we present an energy-based kinetostatic modeling approach in which the deflection of a soft robot is formulated as a minimization problem of its total potential energy. A fixed Hessian matrix of strain energy is proposed and adopted in the limited memory Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm, which significantly improves its efficiency for solving the minimization problem of soft robots without sacrificing prediction accuracy. The simplicity of the approach leads to an implementation of MATLAB with only 99-line codes, which provides an easy-to-use tool for designers who are designing and optimizing the structures of soft robots. The efficiency of the proposed approach for predicting kinetostatic behaviors of soft robots is demonstrated by seven pneumatic-driven and cable-driven soft robots. The capability of the approach for capturing buckling behaviors in soft robots is also demonstrated. The energy-minimization approach, as well as the MATLAB implementation, could be easily tailored to fulfill various tasks, including design, optimization, and control of soft robots.

Liquid Manipulator with Printed Electrode Patterns for Soft Robotic Systems

AbstractSoft robots are able to safely operate in a dynamically evolving or highly unstructured environment by virtue of their inherited compliance. Among the available actuation methods for soft robotics, fluid‐driven is frequently preferred due to holistic design considerations that enable multipurpose yet straightforward mechanical solutions to complicated issues. The motion of a soft fluid‐driven robotic system usually relies on the flow of its internal fluid, however, existing fluid pumps only enable a single linear flow, which severely hinders the integrated multifunctional design of soft robots. Herein, a class of liquid manipulator is proposed based on electrohydrodynamic (EHD) effect, which consists of a flexible substrate with a printed planar electrode pattern. By streamlining the electric field distribution via electrode pattern, the liquid manipulator can manipulate the fluid flow, allowing fluid to perform multiple movement behaviors, including tangential, radial, and linear motions. These liquid manipulators are fabricated by printing planar electrode patterns onto flexible substrates using the digital printing method, in which both the printed electrodes and substrate are flexible and bendable. These liquid manipulators are flexible, fast‐response, thin, lightweight, and scalable, which can be easily embedded into soft fluidic systems with insignificant footprint and weight and actuate their rapid movements. Three liquid manipulators are embedded into a continuously rotating motor, focus‐tunable liquid lens, and soft linear actuator to achieve their multiple motions, i.e., continuous rotation, radial motion, and linear motion, illustrating broad potential of liquid manipulators in soft robotic systems.

Design and Modeling of a Hybrid Soft Robotic Manipulator With Compliant Mechanism

The recent surge of interest in soft robotics has prompted many interesting soft robotic manipulator designs to be proposed. However, current soft robotic manipulators mainly focus on bending and rotation, while elongation has not received attention due to the limited extension/contraction range or the inextensibility of the backbone. This will adversely affect the application of soft robotic manipulators. In this letter, we introduce a hybrid soft robotic manipulator capable of controllable elongation and give a modeling method based on equilibrium principles and assuming a priori deformed configuration. The hybrid soft manipulator consists of a multi-chamber soft body and a rod-driven compliant mechanism, wherein the compliant mechanism provides a push-pull drive to constrain the motion of the manipulator. The model is a modeling framework for a multi-chamber soft robotic manipulator that depicts the relationship between pressures, bending, rotation, and elongation. We experimentally verify the model and demonstrate the potential of the hybrid soft manipulator for point tracking, by comparing it with the soft manipulator without driving rods.