Intelligent Gripper Research Articles

Coiled Carbon Nanotube Fibers Sheathed by a Reinforced Liquid Crystal Elastomer for Strong and Programmable Artificial Muscles.

Fibers of liquid crystal elastomers (LCEs) as promising artificial muscle show ultralarge and reversible contractile strokes. However, the contractile force is limited by the poor mechanical properties of the LCE fibers. Herein, we report high-strength LCE fibers by introducing a secondary network into the single-network LCE. The double-network LCE (DNLCE) shows considerable improvements in tensile strength (313.9%) and maximum actuation stress (342.8%) compared to pristine LCE. To facilitate the controllability and application, a coiled artificial muscle fiber consisting of DNLCE-coated carbon nanotube (CNT) fiber is prepared. When electrothermally driven, the artificial muscle fiber outputs a high actuation performance and programmable actuation. Furthermore, by knitting the artificial muscle fibers into origami structures, an intelligent gripper and crawling inchworm robot have been demonstrated. These demonstrations provide promising application scenarios for advanced intelligent systems in the future.

Ultrarobust Actuator Comprising High-Strength Carbon Fibers and Commercially Available Polycarbonate with Multi-Stimulus Responses and Programmable Deformation.

Polymer-based actuators have gained extensive attention owing to their potential applications in aerospace, soft robotics, etc. However, poor mechanical properties, the inability of multi-stimuli response and programmable deformation, and the costly fabrication procedure have significantly hindered their practical application. Herein, these issues are overcome via a simple and scalable one-step molding method. The actuator is fabricated by hot-pressing commercial unidirectional carbon fiber/epoxy prepregs with a commodity PC membrane. Notable CTE differences between the CF and PC layers endow the bilayer actuator with fast and reliable actuation deformation. Benefiting from the high strength of CF, the actuator exhibits excellent mechanical performance. Moreover, the anisotropy of CF endows the actuator with design flexibility. Furthermore, the multifunction of CF makes the actuator capable of responding to thermal, optical, and electrical stimulation simultaneously. Based on the bilayer actuator, we successfully fabricated intelligent devices such as light-driven biomimetic flowers, intelligent grippers, and gesture-simulating apparatuses, which further validate the programmability and multi-stimuli response characteristics of this actuator. Strikingly, the prepared gripper possesses a grasping capacity approximately 31.2 times its own weight. It is thus believed that the concept presented paves the way for building next-generation robust robotics.

A Novel Hybrid Gripper Capable of Grasping and Throwing Manipulation

Throwing motion is known for phenomenally fast rearrangement, sorting tasks, and placing the object outside the limited workspace with less effort. However, in the robotics domain, despite many simple yet versatile, mechanically intelligent grippers reported earlier, they focus primarily on achieving robust grasping and dexterous manipulation. This article presents a novel design of a single actuator driven hybrid gripper with mechanically coupled rigid links and elastic gripping surface; this arrangement provides the dual function of versatile grasping and throwing manipulation. The gripper comprises a latching mechanism (LM) that drives two passive rigid fingers by elongating/releasing the coupled elastic strip. Elongating the gripping surface enables the gripper to adapt to objects with different geometries, vary surface contact force characteristics, and store the energy in the form of elastic potential. A mechanism to discharge the stored potential energy gradually or instantaneously is essential when the intended task is to place the object free from impact or away from the limited reachable workspace. The proposed LM can swiftly shift from a quick release to a gradual release of the stored elastic potential for greater object's acceleration during throwing and no acceleration while placing. By doing so, the object can be placed at the desired location even farther than the manipulator's reachable workspace. We report the proposed gripper's design details, development, and experimentally demonstrate the versatile grasping, impact-free placing, and throwing capabilities.

Self-sensing magnetic actuators of bilayer hydrogels

ABSTRACT Hard magnetic soft robots have been widely used in biomedical engineering. In these applications, it is crucial to sense the movement of soft robots and their interaction with target objects. Here, we propose a strategy to fabricate a self-sensing bilayer actuator by combining magnetic and ionic conductive hydrogels. The magnetic hydrogel containing NdFeB particles exhibits rapid response to magnetic field and achieve bending deformation. Meanwhile, the polyacrylamide (PAAm) hydrogel with lithium chloride (LiCl) allows for the sensing of deformation. The bending behavior of the bilayer under magnetic field is well captured by theoretical and simulated models. Additionally, the bilayer strain sensor shows good sensitivity, stability and can endure a wide-range cyclic stretching (0–300%). These merits qualify the self-sensing actuator to monitor the motion signals, such as bending of fingers and grasping process of an intelligent gripper. When subject to an external magnetic field, the gripper can grab a cube and sense the resistance change simultaneously to detect the object size. This work may provide a versatile strategy to integrate actuating and self-sensing ability in soft robots.

그리퍼 내에서 물체의 위치를 인지하기 위한 그리퍼의 5축 힘/모멘트센서 개발

In this paper, we describe the development of a 5-axis force/moment sensor of an intelligent gripper designed to grasp the weight of an unknown object and the position of the object in the gripper. The 5-axis force/moment sensor consists of an Fx force sensor, Fy force sensor, and Fz force sensor to measure weight, along with an Mx moment sensor and Mz moment sensor to determine the position of an object in the gripper. These sensors are all built within a single body. Each sensor sensing part of the 5-axis force/moment sensor was newly modeled and custom designed using software, and each sensor was manufactured by attaching a strain gauge. The results of the characteristic test of the fabricated 5-axis force/moment sensor showed that the rated output error was within 0.1%, the reproducibility error was within 0.05%, and the nonlinearity error was within 0.04%. Therefore, the 5-axis force/moment sensor developed in this paper can be attached to an intelligent gripper and be used to grasp the weight of an unknown object as well as the position of the object in the gripper.

Bioinspired multi-stimulus responsive MXene-based soft actuator with self-sensing function and various biomimetic locomotion

Although a series of outstanding achievements have been realized so far, developing soft actuators that can respond to various stimuli and simulate biological versatility (e.g., self-sensing function, diverse locomotion, etc.) is still a great challenge. Here, by utilizing internal stress generated spontaneously during the preparation process, an originally rolled MXene/polydimethylsiloxane (PDMS) bimorph soft actuator has been designed and fabricated. Based on the outstanding photothermal/electrothermal conversion efficiency and adjustable interlayer d-spacing change of Ti3C2Tx MXene, and the large thermal/chemical vapor expansion of crosslinked PDMS, this actuator can produce reversible large deformation under various forms of stimulus, including heat, light, electric, and n-hexane vapor. More importantly, microcracks can be formed spontaneously on the surface of MXene layer during the fabrication process of the actuator, which causes the resistance of MXene layer to be very sensitive to mechanical deformation. Based on this, a light-driven artificial tongue is fabricated, which not only mimic the ejection motion and catching prey behavior of the frog’s tongue, but also perceive the touching object. Moreover, a series of sophisticated biomimetic locomotion such as jumping, crawling, and self-oscillation all can be realized by using this soft actuator. Besides, the actuator with rolled initial structure can also be an intelligent gripper with low energy consumption. By doping Fe3O4 nanoparticles in PDMS matrix, the composite actuator can carry object to through complex maze in adjustable magnetic field without additional stimulation. This MXene-based actuator provides new insights in design of next generation of smart actuators with multi-functions and multiform motions.

AgNWs/Ti3C2Tx MXene-based multi-responsive actuators for programmable smart devices

Thermal bimorph actuators have important applications in artificial muscles, switches, and microsensors for robotics and biomimetic devices. To broaden the adaptability of environments, it is essential to fabricate thermal actuators with multiple stimulus responses, including electricity, near-infrared (NIR) light, and ultraviolet (UV) light, with fast and large deformations. Herein, a thermal actuator with programmable stimuli response was designed by combining silver nanowires (AgNWs) with Ti3C2Tx MXene. Due to the synergistic effect of AgNWs with high plasmonic properties and electrical conductivity as well as Ti3C2Tx MXene with good flexibility and photothermal properties, the obtained actuator can roll up for 2200° at a low driving voltage (2 V) and shows a fast response speed of 0.4 s for a bending angle of 360° under NIR light. More remarkably, the obtained thermal actuator can curl 360° in 1.2s under UV light which has never been reported before. We believe that such thermal actuators are attractive for a wide range of innovative technologies involving soft-bodied robots, intelligent grippers, bionic worms, and information cryptography.

Aerogels Meet Phase Change Materials: Fundamentals, Advances, and Beyond.

Benefiting from the inherent properties of ultralight weight, ultrahigh porosity, ultrahigh specific surface area, adjustable thermal/electrical conductivities, and mechanical flexibility, aerogels are considered ideal supporting alternatives to efficiently encapsulate phase change materials (PCMs) and rationalize phase transformation behaviors. The marriage of versatile aerogels and PCMs is a milestone in pioneering advanced multifunctional composite PCMs. Emerging aerogel-based composite PCMs with high energy storage density are accepted as a cutting-edge thermal energy storage (TES) concept, enabling advanced functionality of PCMs. Considering the lack of a timely and comprehensive review on aerogel-based composite PCMs, herein, we systematically retrospect the state-of-the-art advances of versatile aerogels for high-performance and multifunctional composite PCMs, with particular emphasis on advanced multiple functions, such as acoustic-thermal and solar-thermal-electricity energy conversion strategies, mechanical flexibility, flame retardancy, shape memory, intelligent grippers, and thermal infrared stealth. Emphasis is also given to the versatile roles of different aerogels in composite PCMs and the relationships between their architectures and thermophysical properties. This review also showcases the discovery of an interdisciplinary research field combining aerogels and 3D printing technology, which will contribute to pioneering cutting-edge PCMs. This review aims to arouse wider research interests among interdisciplinary fields and provide insightful guidance for the rational design of advanced multifunctional aerogel-based composite PCMs, thus facilitating the significant breakthroughs in both fundamental research and commercial applications.

Modular Origami Soft Robot with the Perception of Interaction Force and Body Configuration

Bio‐inspired soft robots provide a promising solution for robots working in human‐centered scenarios and interacting with unstructured environments. However, the functional versatility and multimodal sensing of soft robots still need improvements. On one hand, the configuration of a soft robot is predefined during manufacturing; on the other hand, the multimodal perception of the deformable soft actuator is challenging. In this work, a reconfigurable and proprioceptive soft origami module is presented, where two kinds of basic actuation modes (i.e., extension and bending) are realized, and multimodal perception is enabled using a novel foldable self‐inductance sensor. As a result, the origami module can be reconfigured to assemble multifunctional robots that can measure interaction force, body configuration, and other environmental information. Dedicated experiments are performed to validate the performance of the proposed origami module. An intelligent gripper assembled using three origami modules is designed with the capabilities of grasping mode adjustment, grasping force measurement, and the grasping target's size measurement. An intelligent jellyfish is assembled using five origami modules, and equipped with buoyancy adjustment and underwater grasping capabilities. The proposed proprioceptive modular soft origami provides an effective solution for versatile and intelligent soft robot design.

미지물체를 안전하게 잡는 지능형 그리퍼의 3축 힘센서 개발

In this study, we designed and manufactured a 3-axis force sensor for an intelligent gripper that safely grips an unknown object. The 3-axis force sensor consists of an Fx force sensor, an Fy force sensor, and an Fz force sensor in one body, and is manufactured by attaching a strain gauge. The characteristics evaluation showed that the rated output error was within 0.2, the nonlinearity error was within 0.05, and the reproducibility error was within 0.06%. Therefore, the 3-axis force sensor designed and manufactured in this study can be used to measure weight and control the force used to grip an unknown object by attaching it to the intelligent gripper.

End-to-End Deep Learning by MCU Implementation: An Intelligent Gripper for Shape Identification.

This paper introduces a real-time processing and classification of raw sensor data using a convolutional neural network (CNN). The established system is a microcontroller-unit (MCU) implementation of an intelligent gripper for shape identification of grasped objects. The pneumatic gripper has two embedded accelerometers to sense acceleration (in the form of vibration signals) on the jaws for identification. The raw data is firstly transferred into images by short-time Fourier transform (STFT), and then the CNN algorithm is adopted to extract features for classifying objects. In addition, the hyperparameters of the CNN are optimized to ensure hardware implementation. Finally, the proposed artificial intelligent model is implemented on a MCU (Renesas RX65N) from raw data to classification. Experimental results and discussions are introduced to show the performance and effectiveness of our proposed approach.

RETRACTED: An investigation of various actuation mechanisms in robot arm

Many research activities have been carried out to develop a simple mechanism for grasping irregular object shapes using two- or three-fingered robot end effectors. The idea behind this work is to develop three-fingered intelligent grippers that are capable of sensing different factors like weight, effort required, compactness, robustness, and stability of the object held during the manipulations. In this paper, five different actuation mechanisms, namely, edge-cam-operated actuation mechanism, toggle-linkage-based actuation mechanism, wedge-cam-operated gripper, sliding slotted pin–ball joint arrangement, and rack-and-pinion-operated four-bar linkage mechanism, are introduced. The actuation and grasping force of the gripper are to be determined using the analytical approach (static force analysis). Finally, the effective intelligent gripper mechanism is identified based on grasping force for grasping 1 kg weight of a prespecified object.

Intelligent robotic gripper with adaptive grasping force

The on-off control robot gripper is widely employed in pick-and-place operations in Cartesian space for handling hard objects between two positions. Without contact force monitoring, it can not be applied in fragile or soft objects handling. Although, an appropriate grasping force or gripper opening for each target could be searched by trial-and-error process, it needs expensive force/torque sensor or an accurate gripper position controller. It has too expensive and complex control strategy disadvantages for most of industrial applications. In addition, it can not overcome the target slip problem due to mass uncertainty and dynamic factor. Here, an intelligent gripper is designed with embedded distributed control structure for overcoming the uncertainty of object’s mass and soft/hard features. A communication signal is specified to integrate both robot arm and gripper control kernels for executing the robotic position control and gripper force control functions in sequence. An efficient model-free intelligent fuzzy sliding mode control strategy is employed to design the position and force controllers of gripper, respectively. Experimental results of pick-and-place soft and hard objects with grasping force auto-tuning and anti-slip control strategy are shown by pictures to verify the dynamic performance of this distributed control system. The position and force tracking errors are less than 1 mm and 0.1 N, respectively.

Intelligent gripper technology for the handling of carbon fiber material

Nowadays, the serial production of Carbon Fiber-Reinforced Polymers remains a challenge for the industry. Their production and application have been limited by the intensive manual work required to produce them and the resulting elevated manufacturing costs. Moreover, the production handling tasks are fulfilled to a limited extent by the gripping systems currently available in the market. The delicate process and specific material requirements of these polymers compromise the feasibility and use of automated gripper systems. An innovative solution for the automated material handling of carbon fiber textiles developed by the wbk Institute for Production Science in cooperation with J. Schmalz GmbH will be presented in this paper. The main focus of this study deals with measuring principles to increase energy efficiency, process reliability and adaptability of a gripping system using low pressure grippers. This study presents suitable solutions for the implementation of low pressure grippers in a production environment.

Distributed Control Intelligent Robotic Gripper

An intelligent gripper is designed with embedded distributed control structure for overcoming the uncertainty of grasped object mass and soft/hard features. An efficient model-free intelligent fuzzy sliding mode control strategy is employed to design the position and force controllers of gripper, respectively. Experimental results of pick-and-place soft and hard objects with grasping force auto-tuning and anti-slip control strategy are shown by pictures to verify this distributed system performance. The position and force tracking errors are less than 1 mm and 0.1 N, respectively.

Intelligent Robotic Gripper Control Strategy

Although, on-off control robot gripper is widely employed in pick-and-place operations, it can not be applied in fragile or soft objects handling. Here, an intelligent gripper is designed with embedded distributed control structure for overcoming the uncertainty of grasped object mass and soft/hard features. An efficient model-free intelligent fuzzy sliding mode control strategy is employed to design the position and force controllers of gripper, respectively. Experimental results of pick-and-place soft and hard objects with grasping force auto-tuning and anti-slip control strategy are shown by pictures to verify this distributed system performance. The position and force tracking errors are less than 1 mm and 0.1 N, respectively.

Problem of Biomechanical Grippers Identifications Et’s Properties

The specific group grippers are biomechanical grippers, whose shape and construction are analogical to biological model (human hand). These constructions are arranged into category of “intelligent grippers” recently. The analysis of gripping the objects by biomechanical grippers and consequently setting of the model identification of related characteristics and parameter are possible to base on the principles shown. It is possible to secure reliable and safe clamping of manipulated objects in the period of gripper design. This paper gives knowledge from the solution of system problems of manipulated object gripping in the realisation of elements “gripper – manipulated object application requirements” in the period of gripper design.

Sequence trajectory generation for garment handling systems

This paper presents a novel generic approach to the planning strategy of garment handling systems. An assumption is proposed to separate the components of such systems into a component for intelligent gripper techniques and a component for handling planning strategies. Researchers can concentrate on one of the two components first, then merge the two problems together. An algorithm is addressed to generate the trajectory position and a clothes handling sequence of clothes partitions, which are outlined by garment folding creases. The trajectory positions are derived using configuration transformations. The handling sequence is calculated based on the analysis of the adjacency matrix of the graph description of the garment. A case study of the handling procedure of a female shirt is explained through the paper.

Development of a three-axis gripper force sensor and the intelligent gripper using it

This paper describes the development of a three-axis gripper force sensor that measure forces F x , F y and F z simultaneously, and the intelligent gripper using two three-axis gripper force sensors for grasping an unknown object stably. In order to grasp an unknown object using an intelligent gripper safely, it should measure the forces in the grasping direction and in the gravity direction, and perform the force control with the measured forces. Thus, the intelligent gripper should be composed of two three-axis gripper force sensors that measure forces F x , F y and F z at the same time. In this paper, two three-axis gripper force sensors for measuring forces F x , F y and F z simultaneously were newly modeled using five parallel plate-beams, designed, and fabricated. The characteristic tests of the manufactured sensors were carried out, and their interference errors of the developed sensors were less than 3%. Also, the intelligent gripper was manufactured using two three-axis gripper force sensors, and their characteristic tests were carried out. It was conformed that the developed gripper could grasp an unknown object stably.

로봇의 지능형 손을 위한 3축 손가락 힘센서 개발

This paper describes the development of a 3-axis finger force sensor to grasp an unknown object safely in an intelligent robot`s hand. In order to safely grasp an unknown object, robot`s hand should measure the weight of an object and the force of grasping direction simultaneous. But, in the published papers, the grippers and hands equippd with the force sensor that could only measure the force of grasping direction, and grasped objects using their sensors. These grippers and hands can`t safely grasp unknown objects, because they can`t measure the weight of it. Thus, it is necessary to develop 3-axis force sensor that can measure the weight of an object and the force of grasping direction for an intelligent gripper. In this paper, 3-axis finger force sensor to grasp an unknown object safely in an intelligent robot`s hand was developed. In order to fabricate a 3-axis finger force sensor, the sensing elements were modeled using parallel plate beams, and the theoretical analysis was performed to determine the size of sensing elements, then the 3-axis finger force sensor was fabricated. Also, the characteristic test of the developed 3-axis finger force sensor was performed.