FEM-Based Nonlinear Controller for a Soft Trunk Robot

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

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

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

Continuum robots play the role of end effectors in various surgical robots and endoscopic devices. While soft continuum robots (SCRs) have proven advantages such as safety and compliance, more research and development are required to enhance their capability for specific medical scenarios. This research aims at designing a soft robot, considering the concepts of geometric and kinematic similarities. The chosen application is a semi-invasive medical application known as transesophageal echocardiography (TEE). The feasibility of fabrication of a soft endoscopic device derived from the Chorda dorsalis paragon was shown empirically by producing a three-segment pneumatic SCR. The main novelties include bioinspired design, modeling, and a navigation control strategy presented as a novel algorithm to maintain a kinematic similarity between the soft robot and the rigid counterpart. The kinematic model was derived based on the method of transformation matrices, and an algorithm based on a self-organizing map (SOM) network was developed and applied to realize kinematic similarity. The simulation results indicate that the control method forces the soft robot tip to follow the path of the rigid probe within the prescribed distance error (5 mm). The solution provides a soft robot that can surrogate and succeed the traditional rigid counterpart owing to size, workspace, and kinematics.

Soft robots are compliant and durable, and thus potentially better-suited for swimming or crawling over rough terrain than conventional rigid robots. Biomimetic locomotion strategies are often implemented on soft robots, but are difficult to tune because of the complexity of mapping nonlinear mechanical systems to specific gait patterns. We propose an approach to soft robot control in which the robot is designed to physically realize a shape space (mechanically predefined body poses) to follow a theoretically optimal gait. Specifically in this paper we present an entirely soft snake robot designed to implement the prerequisite shape space for slithering gaits. When coupled with a geometric mechanics model relating serpentine shape sequences to displacement, appropriate gait patterns can be selected analytically based on the system's Lie bracket. We developed a modular, two-link soft robot and used the geometric mechanics model to identify several cyclic gait patterns for producing forward displacement. The gait patterns were tested on the soft robot and observed with a motion capture system to measure displacement and monitor shape sequences. Relative performance of the gait patterns is consistent with the geometric “soap-bubble method” as a heuristic for gait optimization, which demonstrates the applicability of this approach to soft robot control and coordination.

Nonlinear dynamic modeling and model-based AI-driven control of a magnetoactive soft continuum robot in a fluidic environment

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

The Denavit-Hartenberg algorithm and the Lagrange-Euler method are used to derive realistic kinematics and dynamic models of a three-axis electric driven articulated planar robot with viscous, dynamic and static frictions. These robot models are further used for testing the following presented nonlinear robot control methods: fuzzy control, variable-structure control and model-reference variable-structure control. In the fuzzy-logic control method seven fuzzy sets are defined for two input variables. Triangular input membership functions and the 7x7 fuzzy rule table are chosen. The fuzzy controller output value is calculated according to the centre of gravity principle. The same fuzzy control algorithm is used in all robot servo control loops with a proper scaling of the linguistic variables. To eliminate the chattering of the variable-structure control signal and to reduce energy consumption, sign function in the original variable-structure control law is replaced with the following functions: a continuous, saturation and exponential function, all of them with a very thin boundary layer. The same modifications are also made in the original model-reference variable-structure control method. In all presented control methods controller parameters are chosen according to the principle of maximal allowed tracking error and a minimum of energy consumption. These control methods are tested by computer simulations in C programming language in the case of moving the tool of the chosen robot arm. The simulation results proved similar efficiencies of all mentioned modified nonlinear robot control methods, although modified variable structure control algorithms are the most suitable because of their simplicity and lower number of controller parameters.

This research investigates designing a continuum soft robot and proposing a kinematic matching control to enable the robot to perform a specified medical task, which in this paper is the transesophageal echocardiography (TEE). A multi-chamber soft robot was designed and fabricated based on the molding of separate layers. The method of transformation matrices was used to develop the kinematic models, and a control method using Jacobian matrices was proposed to manipulate the robot. A prototype was made based on a multi-chamber multi-layer design. The system contains three segments that can be actuated independently to mimic the active bending part of the respective probe. Kinematic models were developed. Negative pressure (vacuum) was used as actuation input. An open-loop controller inspired by a redundancy resolution technique was proposed to make the soft robot tip follow the desired path, i.e.the path of the rigid ultrasound probe. It is concluded that the soft solution can perform the required task as the reachable points of the TEEtip cover the proposed robot workspace and the proposed control can be used for maneuvering in arbitrary trajectories.

Soft robotics has recently evolved to cover a wide range of fields and applications, repeatably proving to be more valuable than previous iterations of robotics. One application is the implementation of soft continuum robots for medical applications as the form and flexibility of soft robots allow them to navigate through vessels in the human body. However, control of these soft bodied robots is difficult. We present a general control strategy for the complex kinematic control of a soft continuum robot based on learning the forward kinematics. Our results show that implementing a kinematic controller using learned forward kinematics is accurate.

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

This paper proposes a dynamic electromechanical model for dielectric elastomer actuators (DEAs) with dissipative processes. Dielectric loss of elastomers, resistance of electrodes, actuator geometry, elastomer viscoelasticity and nonlinear electromechanical coupling are considered, and a new visco-hyperelastic constitutive model with frequency-dependent parameters is developed for large-strain elastomers. The dynamic responses of DEAs at different driving frequencies are experimentally measured and comprehensively compared with those predicted results. The relative errors over the time period of 0–50 s at 5 and 7 Hz are respectively 3.6% and 3.4%, demonstrating the effectiveness of the model. The proposed dynamic model can not only predict the frequency response of DEAs but also characterize the creep and hysteresis behavior with reasonable accuracy. The power density dissipated during dielectric elastomer actuation is calculated and analyzed. The results suggest that selecting low-resistance electrodes and elastomers with short dielectric relaxation time and low viscous loss is a feasible way to achieve high energy conversion efficiency for DEAs. This work can be helpful for the design and control of DEAs, paving the way for their practical applications.

MXenes with their unique electronic, optical, chemical, and mechanical properties have shown great promise in soft robotics. MXene-based soft actuators have been designed to display ultrafast actuations and recovery speeds as well as angle-independent structural colors in response to vapor. Several studies have developed soft actuators by combining MXenes with other materials to mimic the movement of natural organisms. Thus, MXene-based soft actuators have the potential to revolutionize the field of soft robotics and flexible electronics (e.g., wearable devices and artificial muscles). MXene-based artificial muscles have been explored for use in kinetic soft robotics as actuators in microsystems requiring exceptional compliance. MXene-based sensors and actuators have already been developed for human-like sensors and photodetection. However, there are still challenges that need to be addressed in such applications, such as the design of stretchable and compliant robotic skins with a high-level functional integration for soft robotics. The integration of various devices, such as power sources, sensors, and actuators, into soft robotics is another crucial challenge. Despite the excellent stretchability and tensile strength of MXene-based composites, there is a vital need to develop their mechanical and electrochemical features and grant them multi-functionalities. Herein, recent developments pertaining to the applications of MXenes and their composites in soft robotics are discussed with a focus on the important challenges and future perspectives.

Robots have been around us for quite some time now. Robots are machines capable of performing tasks on their own with high accuracy and precision and minimal supervision to reduce human effort. Our daily lives are touched by different forms of robots around us, be it a direct interaction in form of robotic helpers at the airport or indirectly in the case of industrial arm robots assembling the electronics and machines. Traditionally, there are several component systems to robotics and one of the prominent one is actuation, which is made from hard and rigid components in these conventional robots. However, this is responsible for their intermittent motion. A new field of research, soft robotics, makes of soft materials for their fabrication and draws inspiration from natural organisms and how they produce fluidic and complex motions. There are different ways by which these soft materials can be actuated and include techniques like applying pneumatic and hydraulic pressure, applying heat, making use of a chemical process like combustion, applying varying magnetic fields and applying electric fields. Among these, the class of actuators employing soft materials deformed by applying the electric field, known as Dielectric elastomer actuators, are preferred owing to their advantages of simple fabrication, large actuation strain and control by electrical stimulus. The architecture of these actuators resembles a variable capacitor with electrodes on either sides of the elastomer, and their performance depends on material properties like dielectric constant and mechanical stiffness. Generally, researchers have tried to modify either of these properties with addition of solid conductive or ceramic fillers, or chemical modification of the elastomer, and this has led to undesirable changes on the other material properties. Drawing inspiration from biological materials like skin, which is a soft material system filled with fluids, a novel composite is synthesized utilizing a solid polymer matrix and a high dielectric constant liquid filler, an ionic liquid. An increase in dielectric constant is observed accompanied with significant reduction in mechanical stiffness. The novel composites show significant improvement upon the actuation performance of the commonly used elastomeric system at considerably low electric fields. Owing to the judicious choice of material systems, the composites also show high stability and transparency. With emergence of new generation technologies such as display touchscreens, touchpads, virtual reality and augmented reality, human machine interaction and haptics has become ever more important. Soft actuators and dielectric elastomer actuators (in particular), owing to their inherent softness, have convincing advantage over the conventional rigid actuators. Additionally, state-of-the-art technologies for haptics primarily seek to simulate the perception of texture change with sensory manipulation. Furthermore, dielectric elastomer actuators in their current form suffer from visible obstructiveness and non-integrable architecture. A new device architecture for dielectric elastomer actuators, capable of producing on-demand surface texture change and local topographic features, is demonstrated. Owing to its unique architecture, a highly transparent, flexible and integrable configuration of the device is showed. Out-of-plane deformations and force feedback from the devices are shown to be well above the perceptual threshold of sensors, known as mechanoreceptors, present in our fingertips. Another attribute of the biological appendages in natural organisms is the ability to reversibly modulate its mechanical properties upon demand, which still eludes the field of soft robotics. One of the best examples of this is found in human body, where muscles modulate their stiffness in accordance to the load distribution and movement. Most of the current approaches mange to only demonstrate reversible stiffness and involves combination of a passive reversible stiffness component with the existing actuator. Hence, a novel low-temperature phase change material is identified for enabling reversible rigidity in the soft actuators owing to its low melting point, significant gap between melting and solidification, superior thermal stability, high mechanical strength and high dielectric constant. Thermal control is chosen the modulation of mechanical properties, owing to its lightweight design and scalability. The fabricated reversible rigidity composites show impressive variations in stretchability, bendability and hardness. Owing to its ability to melt and re-solidify, the composites also demonstrate a healing behaviour with the ability to regain complete structural integrity and mechanical strength. These novel ultra-soft, high-k liquid filler-based polymer composites, reversible rigidity composites and transparent and integrable device architectures for field-driven soft actuators could pave the way for next generation applications such as shape morphing, adaptive surfaces and transparent haptic devices.

Dielectric elastomer actuators (DEAs) stick out among explored soft actuators due to their advantages of large deformation, high energy density, fast response and low cost. However, DEAs still are far away from robotic practical applications because of the difficulty of the actuation control. This paper presents a novel control approach for control a 3D DEA control. The fabrication of the proposed soft actuator is introduced and the dynamics of the DEA is analyzed via several experiments. Furthermore, a bio-inspired cerebellum nonlinear controller for achieving accurate movements of the DEAs are designed and analyzed. Finally, the simulation and experiments have been carried out for the developed system validation.