Soft Robotics最新文献

This article presents the design and fabrication of a variable stiffness soft gripper based on layer jamming. Traditional layer jamming units have some limitations, such as complicated multistep fabrication, difficulties in system integration, and diminishing in stiffen effect. In this article, a variable stiffness soft gripper is proposed based on the rotational jamming layers to reduce the slippery phenomenon between layers. To fabricate the proposed complex design, a two-step fabrication method is presented. First, multimaterial 3D printing is applied to directly print out the soft finger body with jamming layers. Second, mold casting is used to fabricate the outer vacuum chamber. The proposed gripper contains a main framework and three identical variable stiffness soft fingers. To demonstrate the effectiveness of the design, the soft gripper is mounted on a robotic arm to test its ability of grasping heavy objects while following complex grasping trajectory. The gripper can successfully grasp an object up to 360 g. Grasping robustness of the proposed gripper can be guaranteed when the robotic arm is moving at acceleration up to 7 m/s². The results prove that the proposed design of the soft gripper can improve the grippers grasping robustness during high-speed movement.

For decades, it has been difficult for small-scale legged robots to conquer challenging environments. To solve this problem, we propose the introduction of a bioinspired soft spine into a small-scale legged robot. By capturing the motion mechanism of rat erector spinae muscles and vertebrae, we designed a cable-driven centrally symmetric soft spine under limited volume and integrated it into our previous robotic rat SQuRo. We called this newly updated robot SQuRo-S. Because of the coupling compliant spine bending and leg locomotion, the environmental adaptability of SQuRo-S significantly improved. We conducted a series of experiments on challenging environments to verify the performance of SQuRo-S. The results demonstrated that SQuRo-S crossed an obstacle of 1.07 body height, thereby outperforming most small-scale legged robots. Remarkably, SQuRo-S traversed a narrow space of 0.86 body width. To the best of our knowledge, SQuRo-S is the first quadruped robot of this scale that is capable of traversing a narrow space with a width smaller than its own width. Moreover, SQuRo-S demonstrated stable walking on mud-sand, pipes, and slopes (20°), and resisted strong external impact and repositioned itself in various body postures. This work provides a new paradigm for enhancing the flexibility and adaptability of small-scale legged robots with spine in challenging environments, and can be easily generalized to the design and development of legged robots with spine of different scales.

Origami provides an opportunity to construct a wide range of 3D functional structures by folding a flat sheet. It can be used to develop various soft functional robots by combining soft smart actuators. However, a simple and an effective model that can address the challenging problem of designing origami patterns to connect origami design with robotics is lacking, thereby greatly increasing the threshold of soft origami robots and hindering its development. This study proposes an easy-to-use inverse origami design model to generate the flat crease pattern from the desired folded shape automatically while simulating origami morphing by simply providing the shape parameters or 2D shape graphics. This method overcomes the difficulty of origami design and enables a close connection between origami and robotics. Through this method, various soft origami robots can be developed with low design complexity and time cost to achieve different functions, thereby promoting the development of soft origami robots.

Soft and continuum robots present the opportunity for extremely large ranges of motion, which can enable dexterous, adaptive, and multimodal locomotion behaviors. However, as the number of degrees of freedom (DOF) of a robot increases, the number of actuators should also increase to achieve the full actuation potential. This presents a dilemma in mobile soft robot design: physical space and power requirements restrict the number and type of actuators available and may ultimately limit the movement capabilities of soft robots with high-DOF appendages. Restrictions on actuation of continuum appendages ultimately may limit the various movement capabilities of soft robots. In this work, we demonstrate multimodal behaviors in an underwater robot called "Hexapus." A hierarchical actuation design for multiappendage soft robots is presented in which a single high-power motor actuates all appendages for locomotion, while smaller low-power motors augment the shape of each appendage. The flexible appendages are designed to be capable of hyperextension for thrust, and flexion for grasping with a peak pullout force of 32 N. For propulsion, we incorporate an elastic membrane connected across the base of each tentacle, which is stretched slowly by the high-power motor and released rapidly through a slip-gear mechanism. Through this actuation arrangement, Hexapus is capable of underwater locomotion with low cost of transport (COT = 1.44 at 16.5 mm/s) while swimming and a variety of multimodal locomotion behaviors, including swimming, turning, grasping, and crawling, which we demonstrate in experiment.

The pneumatic and hydraulic dual actuation of pressure-driven soft actuators (PSAs) is promising because of their potential to develop novel practical soft robots and expand the range of soft robot applications. However, the physical characteristics of air and water are largely different, which makes it challenging to quickly adapt to a selected actuation method and achieve method-independent accurate control performance. Herein, we propose a novel LAtent Representation-based Feedforward Neural Network (LAR-FNN) for dual actuation. The LAR-FNN consists of an autoencoder (AE) and a feedforward neural network (FNN). The AE generates a latent representation of a PSA from a 30-s stairstep response. Subsequently, the FNN provides an individual inverse model of the target PSA and calculates feedforward control input by using the latent representation. The experimental results with PSAs demonstrate that the LAR-FNN can meet the requirements of dual actuation control (i.e., accurate control performance regardless of the actuation method with a short adaptation time) with a single neural network. The results suggest that a LAR-FNN can contribute to soft dual-actuation robot development and the field of soft robotics.

Meso- or micro-scale(or insect-scale) robots that are capable of realizing flexible locomotion and/or carrying on complex tasks in a remotely controllable manner hold great promise in diverse fields, such as biomedical applications, unknown environment exploration, in situ operation in confined spaces, and so on. However, the existing design and implementation approaches for such multifunctional, on-demand configurable insect-scale robots are often focusing on their actuation or locomotion, while matched design and implementation with synergistic actuation and function modules under large deformation targeting varying task/target demands are rarely investigated. In this study, through systematical investigations on synergistical mechanical design and function integration, we developed a matched design and implementation method for constructing multifunctional, on-demand configurable insect-scale soft magnetic robots. Based on such a method, we report a simple approach to construct soft magnetic robots by assembling various modules from the standard part library together. Moreover, diverse soft magnetic robots with desirable motion and function can be (re)configured. Finally, we demonstrated (re)configurable soft magnetic robots shifting into different modes to adapt and respond to varying scenarios. The customizable physical realization of complex soft robots with desirable actuation and diverse functions can pave a new way for constructing more sophisticated insect-scale soft machines that can be applied to practical applications soon.

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.

The art of origami has gained traction in various fields such as architecture, the aerospace industry, and soft robotics, owing to the exceptional versatility of flat sheets to exhibit complex shape transformations. Despite the promise that origami robots hold, their use in high-capacity environments has been limited due to the lack of rigidity. This article introduces novel, origami-inspired, self-locking pneumatic modular actuators (SPMAs), enabling them to operate in such environments. Our innovative approach is based on origami patterns that allow for various types of shape morphing, including linear and rotational motion. We have significantly enhanced the stiffness of the actuators by embedding magnets in composite sheets, thus facilitating their application in real-world scenarios. In addition, the embedded self-adjustable valves facilitate the control of sequential origami actuations, making it possible to simplify the pneumatic system for actuating multimodules. With just one actuation source and one solenoid valve, the valves enable efficient control of our SPMAs. The SPMAs can control robotic arms operating in confined spaces, and the entire system can be modularized to accomplish various tasks. Our results demonstrate the potential of origami-inspired designs to achieve more efficient and reliable robotic systems, thus opening up new avenues for the development of robotic systems for various applications.

Industrial robots are widely deployed to perform pick-and-place tasks at high speeds to minimize manufacturing time and boost productivity. When dealing with delicate or fragile goods, soft robotic grippers are better end effectors than rigid grippers due to their softness and safe interaction. However, high-speed motion causes the soft robotic gripper to vibrate, leading to damage of the objects or failed grasping. Soft grippers with variable stiffness are considered to be effective in suppressing vibrations by adding damping devices, but it is quite challenging to compromise between stiffness and compliance. In this article, a controller based on deep reinforcement learning is proposed to control the stiffness of the soft robotic gripper, which can accurately suppress the vibration with only a minor influence on its compliance and softness. The proposed controller is a real-time vibration control strategy, which estimates the output of the controller based on the current operating environment. To demonstrate the effectiveness of the proposed controller, experiments were done with a UR5 robotic arm. For different situations, experimental results show that the proposed controller responds quickly and reduces the amplitude of the oscillation substantially.

There has been a growing need for soft robots operating various force-sensitive tasks due to their environmental adaptability, satisfactory controllability, and nonlinear mobility unique from rigid robots. It is of desire to further study the system instability and strongly nonlinear interaction phenomenon that are the main influence factors to the actuations of lightweight soft actuators. In this study, we present a design principle on lightweight pneumatically elastic backbone structure (PEBS) with the modular construction for soft actuators, which contains a backbone printed as one piece and a common strip balloon. We build a prototype of a lightweight (<80 g) soft actuator, which can perform bending motions with satisfactory output forces (∼20 times self-weight). Experiments are conducted on the bending effects generated by interactions between the hyperelastic inner balloon and the elastic backbone. We investigated the nonlinear interaction and system instability experimentally, numerically, and parametrically. To overcome them, we further derived a theoretical nonlinear model and a numerical model. Satisfactory agreements are obtained between the numerical, theoretical, and experimental results. The accuracy of the numerical model is fully validated. Parametric studies are conducted on the backbone geometry and stiffness, balloon stiffness, thickness, and diameter. The accurate controllability, operation safety, modularization ability, and collaborative ability of the PEBS are validated by designing PEBS into a soft laryngoscope, a modularized PEBS library for a robotic arm, and a PEBS system that can operate remote surgery. The reported work provides a further applicability potential of soft robotics studies.