Thin-film electronics on active substrates: review of materials, technologies and applications

Minimally invasive surgery attracts more and more attention because of the advantages of minimal trauma, less bleeding and pain and low complication rate. However, minimally invasive surgery for beating hearts is still a challenge. Our goal is to develop a soft robot surgical system for single-port minimally invasive surgery on a beating heart. The soft robot described in this paper is inspired by the octopus arm. Although the octopus arm is soft and has more degrees of freedom (DOFs), it can be controlled flexibly. The soft robot is driven by cables that are embedded into the soft robot manipulator and can control the direction of the end and middle of the soft robot manipulator. The forward, backward and rotation movement of the soft robot is driven by a propulsion plant. The soft robot can move freely by properly controlling the cables and the propulsion plant. The soft surgical robot system can perform different thoracic operations by changing surgical instruments. To evaluate the flexibility, controllability and reachability of the designed soft robot surgical system, some testing experiments have been conducted in vivo on a swine. Through the subxiphoid, the soft robot manipulator could enter into the thoracic cavity and pericardial cavity smoothly and perform some operations such as biopsy, ligation and ablation. The operations were performed successfully and did not cause any damage to the surrounding soft tissues. From the experiments, the flexibility, controllability and reachability of the soft robot surgical system have been verified. Also, it has been shown that this system can be used in the thoracic and pericardial cavity for different operations. Compared with other endoscopy robots, the soft robot surgical system is safer, has more DOFs and is more flexible for control. When performing operations in a beating heart, this system maybe more suitable than traditional endoscopy robots.

A fluidic relaxation oscillator for reprogrammable sequential actuation in soft robots

Soft robotic systems are promising for diverse space applications due to their embedded compliance, promising locomotion methods, and efficient use of mass and volume. Space environments are harsher and more varied than those on Earth; extreme temperature, pressure, and radiation may impact the performance and robustness of soft robots. Cryogenic temperatures on celestial bodies such as the Moon or Europa pose significant challenges to the flexibility and actuation performance of conventional soft systems. We present a soft robotic design methodology using novel metallic-based soft robotic structures specifically tailored to extreme space environments. Structures are presented as tunable, reconfigurable modules for soft systems. Module behavior under compression is characterized while submerged in liquid nitrogen, and structural changes are investigated using scanning electron microscopy (SEM). The structures retained flexibility at -196 °C, with a limited 5% increase in peak stiffness over 100 cycles while maintaining a full range of motion. A soft robotic limb was constructed from these modules and demonstrated successful 2D manipulation and grasping of objects at -196 °C. SEM analysis showed no physical signs of microfracture or deformation after cryogenic cycling, indicating changes to the underlying grain structure consistent with properties observed in cold-working stainless steels at cryogenic temperatures in the literature. Our findings demonstrate that metallic soft robotic structures maintain flexibility and exhibit promising performance in cryogenic, analogue space environments. This metal-based cable structure design approach provides a foundation for the development of functional, robust, and reconfigurable soft robots capable of operating in extreme space environments.

Modular or multi-cellular robots hold the promise to adapt their morphology to task and environment. However, research in modular robotics has traditionally been limited to mechanically non-adaptive systems due to hard building blocks and rigid connection mechanisms. To improve adaptation and global flexibility, we suggest the use of modules made of soft materials. Thanks to recent advances in fabrication techniques the development of soft robots without spatial or material constraints is now possible. In order to exploit this vast design space, computer simulations are a time and cost-efficient tool. However, there is currently no framework available that allows studying the dynamics of soft multi-cellular systems. In this work, we present our simulation framework named Soft Cell Simulator (SCS) that enables to study both mechanical design parameters as well as control problems of soft multi-cellular systems in an time-efficient yet globally accurate manner. Its main features are: (i) high simulation speed to test systems with a large number of cells (real-time up to 100 cells), (ii) large non-linear deformations without module self-penetration, (iii) tunability of module softness (0-500 N/m), (iv) physics-based module connectivity, (v) variability of module shape using internal actuators. We present results that validate the plausibility of the simulated soft cells, the scalability as well as the usability of the simulator. We suggest that this simulator helps to master and leverage the potential of the vast design space to generate novel soft multi-cellular robots.

Soft robots, which leverage flexible, stretchable, and smart materials, are relevant to numerous applications that traditional robots struggle with, such as search-and-rescue, human-robot interaction, and exploration. Since soft robots are composed of soft materials, they are inherently more robust to impacts and falls than their rigid counterparts. Additionally, soft structures are inherently safer for human-robot interaction. While clever use of soft materials offers many advantages, it complicates the control of soft robotic systems. Many of the control strategies that have been established for traditional robotic systems cannot be readily used for soft systems due to the difficulties in modeling soft systems. These control strategies require sensory feedback that can reliably provide the state of the system. However, obtaining sensory feedback from soft robotic systems is non-trivial. It has only been in the past few years that soft sensor technology has begun integrating with soft structures to try to provide the proprioceptive data needed to implement control strategies. This thesis focuses on the use of sensory feedback to compensate for the complex behavior of a soft system. In order to accomplish sensory feedback, multiple soft sensor types were investigated and integrated into soft robotic systems. Simplified analytical models were developed to help design soft systems and to interpret the state from the collected sensory data for use in feedback controllers. These simplified models also allowed the implementation of feedforward controllers. Additionally, this body of work demonstrates how sensory feedback can be used to inform feedforward controllers of certain model parameters.

Since its beginnings in the 1960s, soft robotics has been a steadily growing field that has enjoyed recent growth with the advent of rapid prototyping and the provision of new flexible materials. These two innovations have enabled the development of fully flexible and untethered soft robotic systems. The integration of novel sensors enabled by new manufacturing processes and materials shows promise for enabling the production of soft systems with ‘embodied intelligence’. Here, four experts present their perspectives for the future of the field of soft robotics based on these past innovations. Their focus is on finding answers to the questions of: how to manufacture soft robots, and on how soft robots can sense, move, and think. We highlight industrial production techniques, which are unused to date for manufacturing soft robots. They discuss how novel tactile sensors for soft robots could be created to enable better interaction of the soft robot with the environment. In conclusion this article highlights how embodied intelligence in soft robots could be used to make soft robots think and to make systems that can compute, autonomously, from sensory inputs.

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.

Soft robotics, an emerging field at the intersection of robotics and materials science, has gained significant attention in recent years due to its potential for creating highly adaptable and versatile robotic systems. Unlike traditional rigid robots, soft robotics focuses on designing and controlling flexible mechatronic systems that can mimic the natural movements and interactions of living organisms. This paper presents an overview of the recent innovations in soft robotics, specifically focusing on the design and control aspects of flexible mechatronic systems.The design of soft robots involves the integration of advanced materials and mechanisms that enable compliance and flexibility in the robot's body structure. Various materials, such as elastomers, hydrogels, and shape-memory polymers, have been explored for constructing soft robotic components that can deform and recover their shape. These materials exhibit unique properties, such as stretchability, elasticity, and self-healing capabilities, allowing soft robots to adapt to complex and dynamic environments. Additionally, the design of soft robotic systems often incorporates pneumatic or hydraulic actuation mechanisms to achieve locomotion and manipulation.In conclusion, this paper provides an overview of the recent innovations in soft robotics, focusing on the design and control of flexible mechatronic systems. Soft robots have the potential to revolutionize various fields by providing adaptive and versatile robotic systems. The integration of advanced materials, novel actuation mechanisms, and innovative control strategies has paved the way for the development of soft robots with remarkable capabilities. However, further research is needed to address the existing challenges and unlock the full potential of soft robotics in practical applications.

This paper presents the computational design, fabrication, and control of a novel 3-degrees-of-freedom (DOF) soft parallel robot. The design is inspired by a delta robot structure. It is engineered to overcome the limitations of traditional soft serial robot arms, which are typically low in structural stiffness and blocking force. Soft robotic systems are becoming increasingly popular due to their inherent compliance match to that of human body, making them an efficient solution for applications requiring direct contact with humans. The proposed soft robot consists of three soft closed-loop kinematic chains, each of which includes a soft actuator and a compliant four-bar arm. The complex nonlinear dynamics of the soft robot are numerically modeled, and the model is validated experimentally using a 6-DOF electromagnetic position sensor. This research contributes to the growing body of literature in the field of soft robotics, providing insights into the computational design, fabrication, and control of soft parallel robots for use in a variety of complex applications.

Increasing amounts of attention are being paid to the study of Soft Sensors and Soft Systems. Soft Robotic Systems require input from advances in the field of Soft Sensors. Soft sensors can help a soft robot to perceive and to act upon its immediate environment. The concept of integrating sensing capabilities into soft robotic systems is becoming increasingly important. One challenge is that most of the existing soft sensors have a requirement to be hardwired to power supplies or external data processing equipment. This requirement hinders the ability of a system designer to integrate soft sensors into soft robotic systems. In this article, we design, fabricate, and characterize a new soft sensor, which benefits from a combination of radio-frequency identification (RFID) tag design and microfluidic sensor fabrication technologies. We designed this sensor using the working principle of an RFID transporter antenna, but one whose resonant frequency changes in response to an applied strain. This new microfluidic sensor is intrinsically stretchable and can be reversibly strained. This sensor is a passive and wireless device, and as such, it does not require a power supply and is capable of transporting data without a wired connection. This strain sensor is best understood as an RFID tag antenna; it shows a resonant frequency change from approximately 860 to 800 MHz upon an applied strain change from 0% to 50%. Within the operating frequency, the sensor shows a standoff reading range of >7.5 m (at the resonant frequency). We characterize, experimentally, the electrical performance and the reliability of the fabrication process. We demonstrate a pneumatic soft robot that has four microfluidic sensors embedded in four of its legs, and we describe the implementation circuit to show that we can obtain movement information from the soft robot using our wireless soft sensors.

SUMMARYWhen generating gaits for soft robots (those with no explicit joints), it is not evident that undulating control schemes are the most efficient. In considering alternative control schemes, however, the computational costs of evaluating continuum mechanic models of soft robots represent a significant bottleneck. We consider the use of lumped dynamic models for soft robotic systems. Such models have not been employed previously to design gaits for soft robotic systems, though they are widely used to simulate robots with compliant joints. A major question is whether these methods are accurate enough to be representations of soft robots to enable gait design and optimization. This paper addresses the potential “reality gap” between simulation and experiment for the particular case of a soft caterpillar-like robot. Experiments with a prototype soft crawler demonstrate that the lumped dynamic model can capture essential soft-robot mechanics well enough to enable gait optimization. Significantly, experiments verified that a prototype robot achieved high performance for control patterns optimized in simulation and dramatically reduced performance for gait parameters perturbed from their optimized values.

The field of soft intelligent robots has rapidly developed, revealing extensive potential of these robots for real-world applications. By mimicking the dexterities of organisms, robots can handle delicate objects, access remote areas, and provide valuable feedback on their interactions with different environments. For autonomous manipulation of soft robots, which exhibit nonlinear behaviors and infinite degrees of freedom in transformation, innovative control systems integrating flexible and highly compliant sensors should be developed. Accordingly, sensor-actuator feedback systems are a key strategy for precisely controlling robotic motions. The introduction of material magnetism into soft robotics offers significant advantages in the remote manipulation of robotic operations, including touch or touchless detection of dynamically changing shapes and positions resulting from the actuations of robots. Notably, the anisotropies in the magnetic nanomaterials facilitate the perception and response with highly selective, directional, and efficient ways used for both sensors and actuators. Accordingly, this review provides a comprehensive understanding of the origins of magnetic anisotropy from both intrinsic and extrinsic factors and summarizes diverse magnetic materials with enhanced anisotropy. Recent developments in the design of flexible sensors and soft actuators based on the principle of magnetic anisotropy are outlined, specifically focusing on their applicabilities in soft robotic systems. Finally, this review addresses current challenges in the integration of sensors and actuators into soft robots and offers promising solutions that will enable the advancement of intelligent soft robots capable of efficiently executing complex tasks relevant to our daily lives.

This paper reports on Simscape modeling and experimental validation of compliant mechanisms and soft robotic systems. During the past decade, there has been a lot of advancements in terms of the development of novel soft robotic systems, actuators, and sensors. However, efficient modeling of these systems is still a challenge for researchers. This is due to the existence of nonlinearities such as large deformation in the structure of soft robotic systems and compliant mechanisms. While analytical models can be used for conventional rigid robots, the application of these models for soft robots is limited. Simscape is an efficient tool for modeling soft robotic systems and compliant mechanisms as it can take into account large deformation. To validate the developed Simscape models we used a 6 DOF electromagnetic position sensor for each of the example systems such as a compliant bistable mechanism, compliant linear actuator, and a soft Delta robot.

Soft robots can revolutionize tailored therapy. Personalized medicine tailors a patient's treatment to their genetics, lifestyle, and medical history. Soft robotics in personalized medicine gives a unique potential to build safe, efficient, and tailored medical treatments. Soft robots employ soft, flexible materials that fit the human body. They are ideal for surgery, rehabilitation, and medicine administration, where precision and safety are critical. Soft robots are safe and can interact with people, making them ideal for healthcare. Surgical soft robotics may be employed in personalized medicine. Soft robots can do less invasive surgeries with fewer incisions and tissue damage. This may help people heal faster and with fewer issues. Soft robots can also perform surgery in hard-toreach areas without traditional surgical equipment. Rehabilitation institutions may use soft robots to help patients recover. Soft robots may help those with mobility issues. Soft robots may also provide patients feedback during rehabilitation, improving range of motion and functioning. Drug delivery, surgery, and rehabilitation may be conducted using soft robotics. Soft robots can administer drugs to tumors and other harmful regions. This may reduce drug side effects and boost efficacy. Soft robotics may be beneficial in personalized medicine, but several challenges must be overcome before this technology can be extensively employed in clinical settings. One of the biggest challenges is creating soft robots that can work reliably in the complex human body. Soft robots must do their duties precisely and correctly while enduring physiological stress. Soft robot control systems are also tricky. Conventional control methods struggle to govern soft robots due to their great flexibility and deformability. Soft robots need novel control techniques to move and behave in real-time. Finally, soft robotics in personalized medicine provides a unique opportunity to build highly tailored, least invasive, and secure medical interventions. Soft robots might revolutionize medication delivery, rehabilitation, and surgery. Before soft robots are extensively employed in healthcare, various challenges must be overcome. Soft robots need additional study and development to fully fulfill their promise in tailored medicine.

Soft continuum system-based robots which can interact with different environment are becoming a novel mechatronic system in varied fields. Many soft continuum robot can easily crawl, roll, steer, and climb. These innovatively designed systems are safe, effective and easy to control. In this study, two different soft continuum robotic prototypes are developed for locomotion in pipeline inspections. The motions of these soft robots were inspired from the locomotion behavior of the caterpillar. Unlike other types of soft robotic systems, the developed soft robots do not rely on pneumatic or hydraulic actuators, but can be operated electrically using nickel-titanium (NiTi)-based shape memory alloy (SMA) springs. These soft robot systems are fabricated via casting process using silicone elastomers. The linear locomotion profile of the soft robots are investigated carefully. Prismatic and tubular forms are used for designing of the soft robots to move within the pipelines via actuation of the NiTi shape memory alloy springs. The soft body of the robot systems are made of RTV-2 grade silicone rubber due to its hyperelastic response. A thermo-mechanical training process is applied on the NiTi SMA springs for achieving the linear motion inside of the silicone-based body. A microprocessor is used for creating the locomotion sequence of the soft robotic system. The periodic optimal locomotion sequence of the soft robots is determined by means of experimental investigations.