Soft robotics最新文献

The myocardial contracting ratio is approximately 20%, whereas ejection fraction exceeds 60%. Understanding the structure and kinetic mechanisms of the heart that enable this high ejection fraction is crucial in both basic and clinical medicine. However, these mechanisms remain incompletely elucidated. The authors have developed a functional model based on the unique myocardial band theory, which posits that the ventricle is formed by a single myocardial band winding into a spiral. According to this theory, a muscle band, which incorporated thin McKibben artificial muscles embedded within a soft elastomer, was formed, and it was subsequently rolled to replicate the ventricle's structure. Thin McKibben muscles are well-suited for mimicking cardiac muscles due to their longitudinal contraction, radial expansion, and ability to operate in a curved position. In general, animal hearts exhibit approximately 20% myocardial contracting ratio, a 1.2-fold change in myocardial band thickness, and an ejection fraction in the range 50-70%. In comparison, soft robotic hearts demonstrated values of 17.3%, a 1.28-fold thickness change, and a 47.8% ejection fraction, respectively, which closely approximated those of real hearts. Water ejection experiments conducted using a soft robotic heart revealed that the maximum pressure during contraction reached 200 mmHg, generating a pressure-volume loop similar to that observed in the human heart. Thus, soft robotic hearts hold the potential for a wide range of clinical applications, including the elucidation of heart failure pathophysiology and the development of surgical treatments.

The inherent challenges of robotic underwater exploration, such as hydrodynamic effects, the complexity of dynamic coupling, and the necessity for sensitive interaction with marine life, call for the adoption of soft robotic approaches in marine exploration. To address this, we present a novel prototype, ZodiAq, a soft underwater drone inspired by prokaryotic bacterial flagella. ZodiAq's unique dodecahedral structure, equipped with 12 flagella-like arms, ensures design redundancy and compliance, ideal for navigating complex underwater terrains. The prototype features a central unit based on a Raspberry Pi, connected to a sensory system for inertial, depth, and vision detection, and an acoustic modem for communication. Combined with the implemented control law, it renders ZodiAq an intelligent system. This article details the design and fabrication process of ZodiAq, highlighting design choices and prototype capabilities. Based on the strain-based modeling of Cosserat rods, we have developed a digital twin of the prototype within a simulation toolbox to simplify analysis and control. To optimize its operation in dynamic aquatic conditions, a simplified model-based controller has been developed and implemented, facilitating intelligent and adaptive movement in the hydrodynamic environment. Extensive experimental demonstrations highlight the drone's potential, showcasing its design redundancy, embodied intelligence, crawling gait, and practical applications in diverse underwater settings. This research contributes significantly to the field of underwater soft robotics, offering a promising new avenue for safe, efficient, and environmentally conscious underwater exploration.

The high degree of freedom (DoF) shape morphing widely exists in biology for mimicry, camouflage, and locomotion. Currently, a lot of bionic soft/flexible actuators and robots with shape-morphing functions have been developed to realize conformity, grasp, and movement. Among these solutions, two-dimensional responsive materials and structures that can shape morph into different three-dimensional configurations are valuable for creating reversible high DoF shape morphing. However, most existing methods are predetermined through the fabrication process and cannot reprogram their shape, facing limitations on multifunction. Besides, the achievable geometries are very limited due to the device's low integrated level of actuator elements. Here, we develop a polyvinylidene fluoride flexible piezoelectric actuator array based on a row/column addressing (RCA) scheme for reprogrammable high DoF shape morphing and locomotion. The specially designed row/column electrodes form a 6 × 6 array, which contains 36 actuator elements. By developing a high-voltage RCA control system, we can individually control all the elements in the array, leading to a highly reprogrammable array with various sophisticated high DoF shape morphing. We also demonstrate that the array is capable of propelling a robotic fish with various locomotions. This research provides a new method and approach for biomimetic robotics with better mimicry, aero/hydrodynamic efficiency, and maneuverability, as well as haptic display and object manipulation.

Data-driven calibration methods have shown promising results for accurate proprioception in soft robotics. This process can be greatly benefited by adopting numerical simulation for computational efficiency. However, the gap between the simulated and real domains limits the accurate, generalized application of the approach. Herein, we propose an unsupervised domain adaptation framework as a data-efficient, generalized alignment of these heterogeneous sensor domains. A dual cross-modal autoencoder was designed to match the sensor domains at a feature level without any extensive labeling process, facilitating the computationally efficient transferability to various tasks. Moreover, our framework integrates domain adaptation with anomaly detection, which endows robots with the capability for external collision detection. As a proof-of-concept, the methodology was adopted for the famous soft robot design, a multigait soft robot, and two fundamental perception tasks for autonomous robot operation, involving high-fidelity shape estimation and collision detection. The resulting perception demonstrates the digital-twinned calibration process in both the simulated and real domains. The proposed design outperforms the existing prevalent benchmarks for both perception tasks. This unsupervised framework envisions a new approach to imparting embodied intelligence to soft robotic systems via blending simulation.

Small-scale soft robots, despite their potential for adaptability in unknown environments, often encounter performance constraints due to inherent limitations within soft actuators and compact bodies. To address this problem, we proposed a fast-moving soft robot driven by electroactive materials. The robot combines the advantages of dielectric elastomer actuators (DEAs) and shape memory alloy (SMA) spring actuators, enabling its high-performance multi-modal locomotion in a small and lightweight design. Theoretical models were constructed for both DEAs and SMA spring actuators to analyze the performance of the designed robot. The robot's design parameters were optimized based on these models to improve its running and jumping performance. The designed robot has a size of 40 × 45 × 25 mm and a weight of 3.5 g. The robot can achieve a running speed of 91 mm/s, ascend a 9° slope, and execute turning motions via an asymmetrical actuation of SMA spring actuators. The robot also demonstrates high-performance jumping motions with a maximum jumping height of 80 mm and the ability to jump over a 40 mm high obstacle. This work introduces a novel approach to designing small-scale soft terrestrial robots, enhancing their agility and mobility in obstacle-laden environments.

Soft robotics is gaining interest in rehabilitation applications, bringing new opportunities to offset the loss of upper limb motor function following neurological, neuromuscular, or traumatic injuries. Unlike conventional rigid robotics, the added softness in linkages or joints promises to make rehabilitation robots compliant, which translates into higher levels of safety, comfort, usability, and portability, opening the door for these rehabilitation technologies to be used in daily life. While several reviews documented the different technical implementations of soft rehabilitation robots, it is essential to discuss the growing clinical evidence on the feasibility and effectiveness of using this technology for rehabilitative and assistive purposes, whether softness brings the expected advantages from the perspective of end users, and how we should proceed in the future of this field. In this perspective article, we present recent clinical evidence on how 13 different upper limb devices were used in both controlled (clinical) and uncontrolled (at home) settings in more than 37 clinical studies. From these findings and our own experience, we derive recommendations for future developers and end users regarding the design, application, and evaluation of soft robotics for upper limb rehabilitation and assistance.

Based on the analysis of the structures of robots and electronics developed so far, it should be noted that a majority of them need a reservoir for electrical energy storage. Unfortunately, most off-the-shelf devices commercially available nowadays are based on rigid parts that heavily limit the possibilities of incorporating such products into soft robots and wearable electronics. To address these issues, a new type of flexible structure for electrical energy storage, which consists of small battery cells connected by liquid metal paths, was proposed. It can achieve a low value of Young's modulus (about 0.13 MPa) while maintaining electrochemical stability for large stretches (max. capacity reduction-2%). We proposed an individual layer structure as well as a sandwich structure with a granular core, which by way of granular jamming phenomena can change the stiffness (almost 300%). This article describes the concept and working principle of the proposed flexible electrical energy storage structure, followed by the mechanical and electrical characterization, electrochemical impedance spectroscopy, and galvanostatic battery cell cycling. Scanning electron microscopy and energy-dispersive X-ray spectroscopy were used to characterize the electrodes. The article also includes numerical simulations and potential applications of the studied structure.

Soft sensors integrated or attached to robots or human bodies enable rapid and accurate estimation of the physical states of the target systems, including position, orientation, and force. While the use of a number of sensors enhances precision and reliability in estimation, it may constrain the movement of the target system or make the entire system complex and bulky. This article proposes a rapid, efficient framework for determining where to place the sensors on the system given the limited number of available sensors. In particular, given $m$ candidates in location for sensor placement, the algorithm recommends $m_0$ locations that guarantee the maximal estimation performance, based on Bayesian sampling. The sampling and optimization method aims to maximize the log-likelihood in nonparametric regression between the measured values of the selected sensors and the target references. The proposed approach for the optimal sensor placement is validated through two scenarios: full-body motion sensing with a soft wearable sensor suit and fingertip position tracking with a motion-capture system. The proposed algorithm successfully determines the sensor locations close to the optimum within 20 min of learning for both cases.

High-performance eco-friendly soft actuators showing large displacement, fast response, and long-term operational capability require further development for next-generation bioinspired soft robots. Herein, we report an electro-ionic soft actuator based on carboxylated cellulose nanocrystals (CCNC) and carboxylated cellulose nanofibers (CCNF), graphene nanoplatelets (GN), and ionic liquid (IL). The actuator exhibited exceptional actuation performances, achieving large displacements ranging from 1.6 to 12.3 mm under ultralow actuation voltages of 0.25-1.5 V. It also operated stably across a broad frequency band from 0.1 to 10 Hz and displayed a significant working stability of 99.3% after up to 240 cycles. Remarkably, the electro-active actuator demonstrated a fast response (0.39 s delay under 1.0 V at 0.1 Hz), and a long lifespan (with only a minor decrease of 2% for 2 years). The enhanced actuation performances of the actuator were attributed to its superior ionic conductivity, high charge storage ability, strong ionic interaction, and physical-chemical cross-linked networks. Furthermore, we successfully demonstrated the bioinspired applications of CCNC/CCNF-IL-GN actuators including micro-grippers, spiral-structure electroactive stents, biomimetic fingers, and bionic dragonfly wings. The proposed actuator and its bioinspired robot designs could offer a significant way for the development of next-generation eco-friendly soft actuators, soft robots, and biomedical microdevices in microenvironments requiring low-voltage environment.

Tendon-driven continuum soft robots are currently applied in research and are given a promising perspective for future applications. For the routing of the tendons from the actuator to the point where the loading is demanded, two routing possibilities exist in the literature: internal routing of the tendons with the help of structurally embedded Bowden sheaths and external tendon routing where the tendon is not in contact with the soft structure. The application of the latter is a clear disadvantage for applications due to the high risk of interference with the tendon, for example, causing the tendon to break. The first option on the other hand introduces high friction forces into the tendon transmission and affects the elastic characteristic of the continuum and therefore the desired workspace of the system. This article overcomes the aforementioned problems by integrating tendon routings within tendon channels eroded from the continuum structure by a model-based design method. The channels within the continuum structure are computed a priori such that the tendons do not interact with the continuum while moving through its workspace. Overall, a new model-based method for tendon channel design is introduced and a corresponding manufacturing process is established. A continuum joint module prototype is designed to enable roll-pitch-yaw motions with a large accessible workspace. The capabilities of the system are measured in experiments using an external camera for the range of motion. Moreover, walking experiments on the ANYmal robot from ETHZ are presented.