Journal articles: 'Soft robotic finger'

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Teeple, Clark B., Theodore N. Koutros, Moritz A. Graule, and Robert J. Wood. "Multi-segment soft robotic fingers enable robust precision grasping." International Journal of Robotics Research 39, no. 14 (March 13, 2020): 1647–67. http://dx.doi.org/10.1177/0278364920910465.

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In this work, we discuss the design of soft robotic fingers for robust precision grasping. Through a conceptual analysis of the finger shape and compliance during grasping, we confirm that antipodal grasps are more stable when contact with the object occurs on the side of the fingers (i.e., pinch grasps) instead of the fingertips. In addition, we show that achieving such pinch grasps with soft fingers for a wide variety of objects requires at least two independent bending segments each, but only requires actuation in the proximal segment. Using a physical prototype hand, we evaluate the improvement in pinch-grasping performance of this two-segment proximally actuated finger design compared to more typical, uniformly actuated fingers. Through an exploration of the relative lengths of the two finger segments, we show the tradeoff between power grasping strength and precision grasping capabilities for fingers with passive distal segments. We characterize grasping on the basis of the acquisition region, object sizes, rotational stability, and robustness to external forces. Based on these metrics, we confirm that higher-quality precision grasping is achieved through pinch grasping via fingers with the proximally actuated finger design compared to uniformly actuated fingers. However, power grasping is still best performed with uniformly actuated fingers. Accordingly, soft continuum fingers should be designed to have at least two independently actuated serial segments, since such fingers can maximize grasping performance during both power and precision grasps through controlled adaptation between uniform and proximally actuated finger structures.

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Ponraj Joseph Vedhagiri, Godwin, Avataram Venkatavaradan Prituja, Changsheng Li, Guoniu Zhu, Nitish V. Thakor, and Hongliang Ren. "Pinch Grasp and Suction for Delicate Object Manipulations Using Modular Anthropomorphic Robotic Gripper with Soft Layer Enhancements." Robotics 8, no. 3 (August 6, 2019): 67. http://dx.doi.org/10.3390/robotics8030067.

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This paper is an extension of our previous work about a modular anthropomorphic robotic hand with soft enhancements focusing on simultaneous pinch grasp and suction-based object manipulations. The base structure is a tendon-driven robotic hand comprising five fingers and a palm. Each finger consists of two rigid links covered with soft enhancements. The soft enhancements are like the skin and tissues of the robotic hand. The tip of the finger is equipped with a suction module which can be actuated by regulating negative pressure to the soft layers. While our previous work dealt with the rationale behind and the structure of the modular design with kinematic analysis, this paper focuses on analyzing two specific capabilities of the gripper—pinch grasp and suction modality. Experiments validate that the proposed gripper together with the soft enhancement layers is capable of performing delicate single finger suction-based manipulation tasks and two-finger pinch grasp tasks.

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Liu, Mingfang, Lina Hao, Wei Zhang, and Zhirui Zhao. "A novel design of shape-memory alloy-based soft robotic gripper with variable stiffness." International Journal of Advanced Robotic Systems 17, no. 1 (January 1, 2020): 172988142090781. http://dx.doi.org/10.1177/1729881420907813.

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Soft robotic grippers with compliance have great superiority in grabbing objects with irregular shape or fragility compared with traditional rigid grippers. The main limitations of such systems are small grasping force resulted from properties of soft actuators and lacking variable stiffness of soft robotic grippers, which prevent them from a larger wide range of applications. This article proposes a shape-memory alloy (SMA)-based soft gripper with variable stiffness composed of three robotic fingers for grasping compliantly at low stiffness and holding robustly at high stiffness. Each robotic finger mainly consisted of stiff parts and two variable stiffness joints is installed on the base with a specific angle. The paraffin as a variable stiffness material in the joint can be heated or cooled to change the stiffness of the robotic fingers. Results of experiments have shown that a single robotic finger can approximately achieve 18-fold stiffness enhancement. Each finger with two joints can actively achieve multiple postures by both changing the corresponding stiffness of joints and actuating the SMA wire. Based on these principles, the gripper can be applied to grasp objects with different shapes and a large range of weights, and the maximum grasping force of the gripper is increased to about 10 times using the variable stiffness joints. The final experiment is conducted to validate variable stiffness of the proposed soft grippers grasping an object.

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Khurshid, A., A. Ghafoor, and M. A. Malik. "Modeling and Analysis of Soft Contact in Robotic Grasping Using Bond Graph Methods." Advanced Materials Research 189-193 (February 2011): 1786–92. http://dx.doi.org/10.4028/www.scientific.net/amr.189-193.1786.

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Soft fingers contribute to dexterous grasping on account of the area contact and high friction involved. This paper presents a novel approach in modeling of soft contacts between soft fingertip and object using viscoelastic material and analyses its characteristics employing BondGraph Methods (BGM). The fingers are made viscoelastic by using springs and dampers. Detailed bond graph modeling of the contact phenomenon with two soft-finger contacts considered to be placed against each other on the opposite sides of the grasped object as is generally the case in a manufacturing environment is presented. The stiffness of the springs is exploited in order to achieve the stability in the soft-grasping which includes friction between the soft finger contact surfaces and the object. It is shown in the paper that the system stability depends on the viscoelastic material properties of the soft interface. Method of root locus is used to analyze this phenomenon. The paper shows how the weight of the object moving downward is controlled by the friction between the fingers and the object during the application of contact forces by varying the damping and the stiffness in the soft finger.

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Zhao, Shumi, Yisong Lei, Ziwen Wang, Jie Zhang, Jianxun Liu, Pengfei Zheng, Zidan Gong, and Yue Sun. "Biomimetic Artificial Joints Based on Multi-Material Pneumatic Actuators Developed for Soft Robotic Finger Application." Micromachines 12, no. 12 (December 20, 2021): 1593. http://dx.doi.org/10.3390/mi12121593.

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To precisely achieve a series of daily finger bending motions, a soft robotic finger corresponding to the anatomical range of each joint was designed in this study with multi-material pneumatic actuators. The actuator as a biomimetic artificial joint was developed on the basis of two composite materials of different shear modules, and the pneumatic bellows as expansion parts was restricted by frame that made from polydimethylsiloxane (PDMS). A simplified mathematical model was used for the bending mechanism description and provides guidance for the multi-material pneumatic actuator fabrication (e.g., stiffness and thickness) and structural design (e.g., cross length and chamber radius), as well as the control parameter optimization (e.g., the air pressure supply). An actuation pressure of over 70 kPa is required by the developed soft robotic finger to provide a full motion range (MCP = 36°, PIP = 114°, and DIP = 75°) for finger action mimicking. In conclusion, a multi-material pneumatic actuator was designed and developed for soft robotic finger application and theoretically and experimentally demonstrated its feasibility in finger action mimicking. This study explored the mechanical properties of the actuator and could provide evidence-based technical parameters for pneumatic robotic finger design and precise control of its dynamic air pressure dosages in mimicking actions. Thereby, the conclusion was supported by the results theoretically and experimentally, which also aligns with our aim to design and develop a multi-material pneumatic actuator as a biomimetic artificial joint for soft robotic finger application.

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Phung, Van Binh. "SIMULATION RESEARCH ON THE GRASPING PROCESSOF THE SOFT ROBOT GRIPPER." Journal of Science and Technique 17, no. 4 (September 27, 2022): 54–69. http://dx.doi.org/10.56651/lqdtu.jst.v17.n04.403.

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Thisarticlepresents a method to simulate the dynamics of the grasping process of a soft robotic gripper that is made of silicon. The pneumatically actuated soft fingers are composed of interconnecting hollow chambers. Each soft finger is modeled as a series of line-segment links using a multibody dynamics approach. Numerical simulations using Abaqus/CAE software are used to determine the system's dynamic parameters. The soft gripper’s model is then integrated into the robotic manipulators that are built on MSC Adams software. The interaction between soft grippers and objects is modeled according to the Hertz contact theory. The proposed model allows for the investigation of soft gripper gripping capacity with various types of objects and different moving velocities and accelerations. The simulation shows that the soft gripper can hold a spherical object and a cylindrical object with the same mass of 300 g at a maximum acceleration of 9.9 m/s2and 3.6 m/s2respectively. The results of the study are being used to improve the design of the robot's soft gripper.

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Ramirez Arias, Rubiano Fonseca, and Castiblanco Moreno. "Soft Driving Epicyclical Mechanism for Robotic Finger." Actuators 8, no. 3 (July 29, 2019): 58. http://dx.doi.org/10.3390/act8030058.

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Nowadays, the development or improvement of soft actuation mechanisms is a crucialtopic for the achievement of dexterous manipulation using. Then, a primary target of research is thedesign of actuation and driving devices. Consequently, in this paper, we introduce a soft drivingepicyclical mechanism that mimics human muscle behavior and fulfills motion requirements toachieve grasping gestures using a robotic finger. The prototype is experimentally assessed, andresults show that our approach has enough performance for the implementation in grasping tasks.Furthermore, we introduce the basis for a new soft epicyclical mechanism merger with shape memoryalloys to allow active stiffness control of the mechanism.

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Liu, Hao, Changchun Wu, Senyuan Lin, Yunquan Li, and Yonghua Chen. "Double-Acting Soft Actuator for Soft Robotic Hand: A Bellow Pumping and Contraction Approach." Biomimetics 7, no. 4 (October 20, 2022): 171. http://dx.doi.org/10.3390/biomimetics7040171.

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When compressing a soft bellow, the bellow will contract and pump out the fluid inside the bellow. Utilizing this property, we propose a novel actuation method called compressing bellow actuation (CBA), which can output fluidic power and tendon-driven force simultaneously. Based on the CBA method, a double-acting soft actuator (DASA) combining fluidic elastomer actuator (FEA) and tendon-driven metacarpophalangeal (MCP) joint is proposed for robotic finger design. The proposed DASA exhibits both compliance and adaptiveness of FEAs, and controllability and large output force of the tendon-driven methods. The fluid in the bellow can be either air or water or even integration of the two, thus constituting three different actuation modes. Mathematical modeling of the relationship between bellow compression displacement and DASA’s bending angle is developed. Furthermore, experimental characterizations of DASA’s bending angle and blocking force are conducted at different actuation modes. The double-acting method can availably promote the bending angle of an FEA by up to 155%, and the blocking force by up to 132% when the FEA is water-filled. A soft robotic hand with a forearm prototype based on the DASA fingers is fabricated for the demonstration of finger motion and gripping applications.

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Kladovasilakis, Nikolaos, Ioannis Kostavelis, Paschalis Sideridis, Eleni Koltzi, Konstantinos Piliounis, Dimitrios Tzetzis, and Dimitrios Tzovaras. "A Novel Soft Robotic Exoskeleton System for Hand Rehabilitation and Assistance Purposes." Applied Sciences 13, no. 1 (December 30, 2022): 553. http://dx.doi.org/10.3390/app13010553.

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During the last decade, soft robotic systems, such as actuators and grippers, have been employed in various commercial applications. Due to the need to integrate robotic mechanisms into devices operating alongside humans, soft robotic systems concentrate increased scientific interest in tasks with intense human–robot interaction, especially for human-exoskeleton applications. Human exoskeletons are usually utilized for assistance and rehabilitation of patients with mobility disabilities and neurological disorders. Towards this direction, a fully functional soft robotic hand exoskeleton system was designed and developed, utilizing innovative air-pressurized soft actuators fabricated via additive manufacturing technologies. The CE-certified system consists of a control glove that copies the motion from the healthy hand and passes the fingers configuration to the exoskeleton applied on the affected hand, which consists of a soft exoskeleton glove (SEG) controlled with the assistance of one-axis flex sensors, micro-valves, and a proportional integral derivative (PID) controller. Each finger of the SEG moves independently due to the finger-dedicated motion control system. Furthermore, the real-time monitoring and control of the fabricated SEG are conducted via the developed software. In addition, the efficiency of the exoskeleton system was investigated through an experimental validation procedure with the involvement of healthy participants (control group) and patients, which evaluated the efficiency of the system, including safety, ergonomics, and comfort in its usage.

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Zhao, Shumi, Ziwen Wang, Yisong Lei, Jie Zhang, Yuyao Li, Zeji Sun, and Zidan Gong. "3D-Printed Soft Pneumatic Robotic Digit Based on Parametric Kinematic Model for Finger Action Mimicking." Polymers 14, no. 14 (July 7, 2022): 2786. http://dx.doi.org/10.3390/polym14142786.

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A robotic digit with shape modulation, allowing personalized and adaptable finger motions, can be used to restore finger functions after finger trauma or neurological impairment. A soft pneumatic robotic digit consisting of pneumatic bellows actuators as biomimetic artificial joints is proposed in this study to achieve specific finger motions. A parametric kinematic model is employed to describe the tip motion trajectory of the soft pneumatic robotic digit and guide the actuator parameter design (i.e., the pressure supply, actuator material properties, and structure requirements of the adopted pneumatic bellows actuators). The direct 3D printing technique is adopted in the fabrication process of the soft pneumatic robotic digit using the smart material of thermoplastic polyurethane. Each digit joint achieves different ranges of motion (ROM; bending angles of distal, proximal, and metacarpal joint are 107°, 101°, and 97°, respectively) under a low pressure of 30 kPa, which are consistent with the functional ROM of a human finger for performing daily activities. Theoretical model analysis and experiment tests are performed to validate the effectiveness of the digit parametric kinematic model, thereby providing evidence-based technical parameters for the precise control of dynamic pressure dosages to achieve the required motions.

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Batsuren, Khulan, and Dongwon Yun. "Soft Robotic Gripper with Chambered Fingers for Performing In-Hand Manipulation." Applied Sciences 9, no. 15 (July 24, 2019): 2967. http://dx.doi.org/10.3390/app9152967.

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In this work, we present a soft robotic gripper for grasping various objects by mimicking in-hand manipulation. The soft robotic gripper consists of three fingers. Each finger contains three air chambers: Two chambers (side chambers) for twisting in two different directions and one chamber (middle chamber) for grasping. The combination of these air chambers makes it possible to grasp an object and rotate it. We fabricated the soft finger using 3D-printed molds. We used the finite element method (FEM) method to design the most effective model, and later these results were compared with results from experiments. The combined experimental results were used to control the range of movement of the whole gripper. The gripper could grasp objects weighing from 4 g to 300 g just by inflating the middle chamber, and when air pressure was subsequently applied to one of the side chambers, the gripper could twist the object by 35°.

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Jović, Srđjan, Amir Seyed Danesh, Emran Younesi, Obrad Aničić, Dalibor Petković, and Shahaboddin Shamshirband. "Forecasting of Underactuated Robotic Finger Contact Forces by Support Vector Regression Methodology." International Journal of Pattern Recognition and Artificial Intelligence 30, no. 07 (May 25, 2016): 1659019. http://dx.doi.org/10.1142/s0218001416590199.

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Robotic manipulators have very strong nonlinearities. Analytical modeling of the robotic gripper is very challenging task. Therefore in this paper soft computing methods is applied in order to estimate contact forces of the robotic finger. Support vector regression (SVR) with radial and polynomial basis functions and the soft computing methods were used. The primary purpose of this study are in clarification of kinetostatic examining of a new finger mechanism utilizing pseudo-unbending body model. The results show the better prediction accuracy with SVR methodology with radial basis function (RBF).

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Wang, Yuanyuan, Shota Kokubu, Shaoying Huang, Ya-Hsin Hsueh, and Wenwei Yu. "Towards an Extensive Thumb Assist: A Comparison between Whole-Finger and Modular Types of Soft Pneumatic Actuators." Applied Sciences 12, no. 8 (April 7, 2022): 3735. http://dx.doi.org/10.3390/app12083735.

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Soft pneumatic actuators used in robotic rehabilitation gloves are classified into two types: whole-finger actuators with air chambers that cover the entire finger and modular actuators with chambers only above the finger joints. Most existing prototypes provide enough finger flexion support, but insufficient independent thumb abduction or opposition support. Even the latest modular soft actuator realized thumb abduction with a sacrifice of range of motion (RoM). Moreover, the advantages and disadvantages of using the two types of soft actuators for thumb assistance have not been made clear. Without an efficient thumb assist, patients’ options for hand function rehabilitation are very limited. Therefore, the objective of this study was to design a modular actuator (M-ACT) that could support multiple degrees of freedom, compare it with a whole-finger type of thumb actuator with three inner chambers (3C-ACT) in terms of the RoM, force output of thumb flexion, and abduction, and use an enhanced Kapandji test to measure both the kinematic aspect of the thumb (Kapandji score) and thumb-tip pinch force. Our results indicated superior single-DoF support capability of the M-ACT and superior multi-DoF support capability of the 3C-ACT. The use of the 3C-ACT as the thumb actuator and the M-ACT as the four-finger actuator may be the optimal solution for the soft robotic glove. This study will aid in the progression of soft robotic gloves for hand rehabilitation towards real rehabilitation practice.

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KURUMAYA, Shunichi, and Taro NAKAMURA. "Prototype of Soft Robotic Finger with Flexible Exoskeleton." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2021 (2021): 2P3—H11. http://dx.doi.org/10.1299/jsmermd.2021.2p3-h11.

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Ghafoor, Abdul, Jian S. Dai, and Joseph Duffy. "Stiffness Modeling of the Soft-Finger Contact in Robotic Grasping." Journal of Mechanical Design 126, no. 4 (July 1, 2004): 646–56. http://dx.doi.org/10.1115/1.1758255.

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This paper investigates the soft-finger contact by presenting the contact with a set of line springs based on screw theory, reveals the rotational effects, and identifies the stiffness properties of the contact. An elastic model of a soft-finger contact is proposed and a generalized contact stiffness matrix is developed by applying the congruence transformation and by introducing stiffness mapping of the line springs in translational directions and rotational axes. The effective stiffnesses along these directions and axes are hence obtained and the rotational stiffnesses are revealed. This helps create a screw representation of a six-dimensional soft-finger contact and produce an approach of analyzing and synthesizing a robotic grasp without resorting to the point contact representation. The correlation between the rotational stiffness, the number of equivalent point contacts and the number of equivalent contours is given and the stiffness synthesis is presented with both modular and direct approaches. The grasp thus achieved from the stiffness analysis contributes to both translational and rotational restraint and the stiffness matrix so developed is proven to be symmetric and positive definite. Case studies are presented with a two-soft-finger grasp and a three-soft-finger grasp. The grasps are analyzed with a general stiffness matrix which is used to control the fine displacements of a grasped object by changing the preload on the contact.

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Proulx, Camille E., Myrka Beaulac, Mélissa David, Catryne Deguire, Catherine Haché, Florian Klug, Mario Kupnik, Johanne Higgins, and Dany H. Gagnon. "Review of the effects of soft robotic gloves for activity-based rehabilitation in individuals with reduced hand function and manual dexterity following a neurological event." Journal of Rehabilitation and Assistive Technologies Engineering 7 (January 2020): 205566832091813. http://dx.doi.org/10.1177/2055668320918130.

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Despite limited scientific evidence, there is an increasing interest in soft robotic gloves to optimize hand- and finger-related functional abilities following a neurological event. This review maps evidence on the effects and effectiveness of soft robotic gloves for hand rehabilitation and, whenever possible, patients’ satisfaction. A systematized search of the literature was conducted using keywords structured around three areas: technology attributes, anatomy, and rehabilitation. A total of 272 titles, abstracts, and keywords were initially retrieved, and data were extracted out of 13 articles. Six articles investigated the effects of wearing a soft robotic glove and eight studied the effect or effectiveness of an intervention with it. Some statistically significant and meaningful beneficial effects were confirmed with the 29 outcome measures used. Finally, 11 articles also confirmed users’ satisfaction with regard to the soft robotic glove, while some articles also noticed an increased engagement in the rehabilitation program with this technology. Despite the heterogeneity across studies, soft robotic gloves stand out as a safe and promising technology to improve hand- and finger-related dexterity and functional performance. However, strengthened evidence of the effects or effectiveness of such devices is needed before their transition from laboratory to clinical practice.

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Anwar, Muddasar, Toufik Al Khawli, Irfan Hussain, Dongming Gan, and Federico Renda. "Modeling and prototyping of a soft closed-chain modular gripper." Industrial Robot: the international journal of robotics research and application 46, no. 1 (January 21, 2019): 135–45. http://dx.doi.org/10.1108/ir-09-2018-0180.

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Purpose This paper aims to present a soft closed-chain modular gripper for robotic pick-and-place applications. The proposed biomimetic gripper design is inspired by the Fin Ray effect, derived from fish fins physiology. It is composed of three axisymmetric fingers, actuated with a single actuator. Each finger has a modular under-actuated closed-chain structure. The finger structure is compliant in contact normal direction, with stiff crossbeams reorienting to help the finger structure conform around objects. Design/methodology/approach Starting with the design and development of the proposed gripper, a consequent mathematical representation consisting of closed-chain forward and inverse kinematics is detailed. The proposed mathematical framework is validated through the finite element modeling simulations. Additionally, a set of experiments was conducted to compare the simulated and prototype finger trajectories, as well as to assess qualitative grasping ability. Findings Key Findings are the presented mathematical model for closed-loop chain mechanisms, as well as design and optimization guidelines to develop controlled closed-chain grippers. Research limitations/implications The proposed methodology and mathematical model could be taken as a fundamental modular base block to explore similar distributed degrees of freedom (DOF) closed-chain manipulators and grippers. The enhanced kinematic model contributes to optimized dynamics and control of soft closed-chain grasping mechanisms. Practical implications The approach is aimed to improve the development of soft grippers that are required to grasp complex objects found in human–robot cooperation and collaborative robot (cobot) applications. Originality/value The proposed closed-chain mathematical framework is based on distributed DOFs instead of the conventional lumped joint approach. This is to better optimize and understand the kinematics of soft robotic mechanisms.

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Shan, Xiaowei, and Lionel Birglen. "Modeling and analysis of soft robotic fingers using the fin ray effect." International Journal of Robotics Research 39, no. 14 (April 13, 2020): 1686–705. http://dx.doi.org/10.1177/0278364920913926.

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Soft grasping of random objects in unstructured environments has been a research topic of predilection both in academia and in industry because of its complexity but great practical relevance. However, accurate modeling of soft hands and fingers has proven a difficult challenge to tackle. Focusing on this issue, this article presents a detailed mathematical modeling and performance analysis of parallel grippers equipped with soft fingers taking advantage of the fin ray effect (FRE). The FRE, based on biomimetic principles, is most commonly found in the design of grasping soft fingers, but despite their popularity, finding a convenient model to assess the grasp capabilities of these fingers is challenging. This article aims at solving this issue by providing an analytic tool to better understand and ultimately design this type of soft fingers. First, a kinetostatic model of a general multi-crossbeam finger is established. This model will allow for a fast yet accurate estimation of the contact forces generated when the fingers grasp an arbitrarily shaped object. The obtained mathematical model will be subsequently validated by numerically to ensure the estimations of the overall grasp strength and individual contact forces are indeed accurate. Physical experiments conducted with 3D-printed fingers of the most common architecture of FRE fingers will also be presented and shown to support the proposed model. Finally, the impact of the relative stiffness between different areas of the fingers will be evaluated to provide insight into further refinement and optimization of these fingers.

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Cheng, Xiao, Fan Zhang, and Wentao Dong. "Soft Conductive Hydrogel-Based Electronic Skin for Robot Finger Grasping Manipulation." Polymers 14, no. 19 (September 20, 2022): 3930. http://dx.doi.org/10.3390/polym14193930.

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Electronic skin with human-like sensory capabilities has been widely applied to artificial intelligence, biomedical engineering, and the prosthetic hand for expanding the sensing ability of robots. Robotic electronic skin (RES) based on conductive hydrogel is developed to collect strain and pressure data for improving the grasping capability of the robot finger. RES is fabricated and assembled by the soft functional materials through a sol–gel process for guaranteeing the overall softness. The strain sensor based on piezoresistive hydrogel (gauge factor ~9.98) is integrated onto the back surface of the robot finger to collect the bending angle of the robot finger. The capacitive pressure sensor based on a hydrogel electrode (sensitivity: 0.105 kPa−1 below 3.61 kPa, and 0.0327 kPa−1 in the range from 4.12 to 15 kPa.) is adhered onto the fingertip to collect the pressure data when touching the objects. A robot-finger-compatible RES with strain and pressure sensing function is designed for finger gesture detection and grasping manipulation. The negative force feedback control framework is built to improve grasping manipulation of the robot finger with RES, which would provide a self-adaptive control method to determine whether the objects are grasped successfully or not. Robot fingers integrated with soft sensors would promote the development of sensing and grasping abilities of the robot finger and interaction with human beings.

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Psomopoulou, Efi, Daiki Karashima, Zoe Doulgeri, and Kenji Tahara. "Stable pinching by controlling finger relative orientation of robotic fingers with rolling soft tips." Robotica 36, no. 2 (August 14, 2017): 204–24. http://dx.doi.org/10.1017/s0263574717000303.

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SUMMARYThere is a large gap between reality and grasp models that are currently available because of the static analysis that characterizes these approaches. This work attempts to fill this need by proposing a control law that, starting from an initial contact state which does not necessarily correspond to an equilibrium, achieves dynamically a stable grasp and a relative finger orientation in the case of pinching an object with arbitrary shape via rolling soft fingertips. Controlling relative finger orientation may improve grasping force manipulability and allow the appropriate shaping of the composite object consisted of the distal links and the object, for facilitating subsequent tasks. The proposed controller utilizes only finger proprioceptive measurements and is not based on the system model. Simulation and experimental results demonstrate the performance of the proposed controller with objects of different shapes.

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Yan, Yadong, Chang Cheng, Mingjun Guan, Jianan Zhang, and Yu Wang. "Texture Identification and Object Recognition Using a Soft Robotic Hand Innervated Bio-Inspired Proprioception." Machines 10, no. 3 (February 25, 2022): 173. http://dx.doi.org/10.3390/machines10030173.

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In this study, we innervated bio-inspired proprioception into a soft hand, facilitating a robust perception of textures and object shapes. The tendon-driven soft finger with three joints, inspired by the human finger, was detailed. With tension sensors embedded in the tendon that simulate the Golgi tendon organ of the human body, 17 types of textures can be identified under uncertain rotation angles and actuator displacements. Four classifiers were used and the highest identification accuracy was 98.3%. A three-fingered soft hand based on the bionic finger was developed. Its basic grasp capability was tested experimentally. The soft hand can distinguish 10 types of objects that vary in shape with top grasp and side grasp, with the highest accuracies of 96.33% and 96.00%, respectively. Additionally, for six objects with close shapes, the soft hand obtained an identification accuracy of 97.69% with a scan-grasp method. This study offers a novel bionic solution for the texture identification and object recognition of soft manipulators.

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Georgopoulou, Antonia, Silvain Michel, and Frank Clemens. "Sensorized Robotic Skin Based on Piezoresistive Sensor Fiber Composites Produced with Injection Molding of Liquid Silicone." Polymers 13, no. 8 (April 10, 2021): 1226. http://dx.doi.org/10.3390/polym13081226.

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Soft robotics and flexible electronics are rising in popularity and can be used in many applications. However, there is still a need for processing routes that allow the upscaling in production for functional soft robotic parts in an industrial scale. In this study, injection molding of liquid silicone is suggested as a fabrication method for sensorized robotic skin based on sensor fiber composites. Sensor fibers based on thermoplastic elastomers with two different shore hardness (50A and 70A) are combined with different silicone materials. A mathematical model is used to predict the mechanical load transfer from the silicone matrix to the fiber and shows that the matrix of the lowest shore hardness should not be combined with the stiffer fiber. The sensor fiber composites are fixed on a 3D printed robotic finger. The sensorized robotic skin based on the composite with the 50A fiber in combination with pre-straining gives good sensor performance as well as a large elasticity. It is proposed that a miss-match in the mechanical properties between fiber sensor and matrix should be avoided in order to achieve low drift and relaxation. These findings can be used as guidelines for material selection for future sensor integrated soft robotic systems.

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Myers, Andrea, Anthony Gunderman, Renee Threlfall, and Yue Chen. "Determining Hand-harvest Parameters and Postharvest Marketability Impacts of Fresh-market Blackberries to Develop a Soft-robotic Gripper for Robotic Harvesting." HortScience 57, no. 5 (May 2022): 592–94. http://dx.doi.org/10.21273/hortsci16487-22.

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Hand-harvesting parameters and postharvest marketability attributes of fresh-market blackberries (Rubus L. subgenus Rubus Watson) were characterized to develop a prototype for a soft-robotic gripper for robotic harvesting. A custom-made, force-sensing apparatus attached to the thumb and fingers of a person hand-harvesting blackberries was developed to quantify forces used to harvest and to identify appendages for harvesting. Four cultivars of blackberries grown in Arkansas were harvested at optimal ripeness and stored at 2 °C for 21 days to determine the impact on marketability attributes (leakage, decay, and red drupelet reversion). The forces during harvest imparted by the thumb and middle finger were greatest (0.77 N and 0.37 N, respectively), whereas the index and ring fingers used lower forces (0.16 N and 0.06 N, respectively), primarily to stabilize the blackberry. The forces applied to grab, stabilize, and harvest blackberries caused minimal marketability damage (leakage, <10%; decay, <2%; and red drupelet reversion, <8%) after postharvest storage. This project quantified harvest and postharvest parameters, allowing data-driven design of a three-prong soft-robotic gripper for harvest of fresh-market blackberries.

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Lin, Keng-Yu, Arturo Gamboa-Gonzalez, and Michael Wehner. "Soft Robotic Sensing, Proprioception via Cable and Microfluidic Transmission." Electronics 10, no. 24 (December 19, 2021): 3166. http://dx.doi.org/10.3390/electronics10243166.

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Current challenges in soft robotics include sensing and state awareness. Modern soft robotic systems require many more sensors than traditional robots to estimate pose and contact forces. Existing soft sensors include resistive, conductive, optical, and capacitive sensing, with each sensor requiring electronic circuitry and connection to a dedicated line to a data acquisition system, creating a rapidly increasing burden as the number of sensors increases. We demonstrate a network of fiber-based displacement sensors to measure robot state (bend, twist, elongation) and two microfluidic pressure sensors to measure overall and local pressures. These passive sensors transmit information from a soft robot to a nearby display assembly, where a digital camera records displacement and pressure data. We present a configuration in which one camera tracks 11 sensors consisting of nine fiber-based displacement sensors and two microfluidic pressure sensors, eliminating the need for an array of electronic sensors throughout the robot. Finally, we present a Cephalopod-chromatophore-inspired color cell pressure sensor. While these techniques can be used in a variety of soft robot devices, we present fiber and fluid sensing on an elastomeric finger. These techniques are widely suitable for state estimation in the soft robotics field and will allow future progress toward robust, low-cost, real-time control of soft robots. This increased state awareness is necessary for robots to interact with humans, potentially the greatest benefit of the emerging soft robotics field.

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Ahmed, Yahya, Auns Al-Neami, and Saleem Lateef. "Robotic Glove for Rehabilitation Purpose: Review." 3D SCEEER Conference sceeer, no. 3d (July 1, 2020): 86–92. http://dx.doi.org/10.37917/ijeee.sceeer.3rd.12.

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Rehabilitation robots have become one of the main technical instruments that Treat disorder patients in the biomedical engineering field. The robotic glove for the rehabilitation is basically made of specialized materials which can be designed to help the post-stroke patients. In this paper, a review of the different types of robotic glove for Rehabilitation have been discussed and summarized. This study reviews a different mechanical system of robotic gloves in previous years. The selected studies have been classified into four types according to the Mechanical Design: The first type is a tendon-driven robotic glove. The second type of robotic glove works with a soft actuator as a pneumatic which is operated by air pressure that passes through a plastic pipe, pressure valves, and air compressor. The third type is the exoskeleton robotic gloves this type consists of a wearable mechanical design that can used a finger-based sensor to measure grip strength or is used in interactive video applications. And the fourth type is the robotic glove with a liner actuator this type consists of a tape placed on the fingers and connected to linear actuators to open and close the fingers during the rehabilitation process.

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Duanmu, Dehao, Xiaojun Wang, Xiaodong Li, Zheng Wang, and Yong Hu. "Design of Guided Bending Bellows Actuators for Soft Hand Function Rehabilitation Gloves." Actuators 11, no. 12 (November 25, 2022): 346. http://dx.doi.org/10.3390/act11120346.

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This study developed a soft pneumatic glove actuated by elliptical cross-sectional guided bending bellows to augment finger-knuckle rehabilitation for patients with hand dysfunction. The guided bending bellows actuators (GBBAs) are made of thermoplastic elastomer (TPE) materials, demonstrating the necessary air tightness as a pneumatic actuator. The GBBAs could produce different moments of inertia when increasing internal air pressure drives the GBBAs bending along distinct symmetry planes and exhibits anisotropic kinematic bending performance. Actuated by GBBAs, wearable soft rehabilitation gloves can be used for daily rehabilitation training of hand dysfunction to enhance the range of motion of the finger joint. To control each finger of the gloves independently to achieve the function of manipulating gestures, a multi-channel pneumatic control system is designed, and each air circuit is equipped with an air-pressure sensor to make adjustments based on feedback. Compared with general soft robotic exoskeleton gloves currently used for hand dysfunction, the GBBAs actuated soft gloves have the advantage of enhancing the rehabilitation strength, finger movement range, and multi-action coordination applied with guided bending bellows actuators.

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Liu, Chih-Hsing, Fu-Ming Chung, Yang Chen, Chen-Hua Chiu, and Ta-Lun Chen. "Optimal Design of a Motor-Driven Three-Finger Soft Robotic Gripper." IEEE/ASME Transactions on Mechatronics 25, no. 4 (August 2020): 1830–40. http://dx.doi.org/10.1109/tmech.2020.2997743.

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ZHU, Mingzhu, Yoshiki MORI, Akira WADA, and Sadao KAWAMURA. "Development of passive elements with variable stiffiness for soft robotic finger." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2018 (2018): 1P2—I10. http://dx.doi.org/10.1299/jsmermd.2018.1p2-i10.

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Rieger, Claire, and Jaydip Desai. "A Preliminary Study to Design and Evaluate Pneumatically Controlled Soft Robotic Actuators for a Repetitive Hand Rehabilitation Task." Biomimetics 7, no. 4 (September 20, 2022): 139. http://dx.doi.org/10.3390/biomimetics7040139.

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A stroke is an infarction in the cortical region of the brain that often leads to isolated hand paresis. This common side effect renders individuals compromised in their ability to actively flex or extend the fingers of the affected hand. While there are currently published soft robotic glove designs, this article proposed a unique design that allows users to self-actuate their therapy due to the ability to re-extend the hand using a layer of resistive flexible steel. The results showed a consistently achieved average peak of 75° or greater for each finger while the subjects’ hands were at rest during multiple trials of pneumatic assisted flexion. During passive assisted testing, human subject testing on 10 participants showed that these participants were able to accomplish 80.75% of their normal active finger flexion range with the steel-layer-lined pneumatic glove and 87.07% with the unlined pneumatic glove on average when neglecting outliers. An addition of the steel layer lowered the blocked tip force by an average of 18.13% for all five fingers. These data show strong evidence that this glove would be appropriate to advance to human subject testing on those who do have post stroke hand impairments.

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Raessa, Mohamed, Weiwei Wan, Keisuke Koyama, and Kensuke Harada. "Planning to Flip Heavy Objects Considering Soft-Finger Contacts." International Journal of Automation Technology 15, no. 2 (March 5, 2021): 158–67. http://dx.doi.org/10.20965/ijat.2021.p0158.

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In this study, we implemented a constrained motion planner that enables robot manipulators to flip large and heavy objects without slippage while continuously holding them. Based on the soft-finger maximum friction torque, we developed a constraint relaxation method to estimate the critical rotation angle that a robot end effector can rotate while avoiding in-hand slippage. The critical rotation angle was used in a motion planner to sample safe configurations and generate slippage-free motion. The proposed planner was implemented using a 6-degree-of-freedom robot arm and a 2-finger robotic gripper with rubber pads attached to the fingertips. Experiments were performed with several objects to examine and demonstrate the performance of the planner. The results indicated satisfying planning time and the elimination of object slippage.

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Bakhy, Sadeq Hussein. "Modeling of contact pressure distribution and friction limit surfaces for soft fingers in robotic grasping." Robotica 32, no. 7 (January 2, 2014): 1005–15. http://dx.doi.org/10.1017/s0263574713001215.

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SUMMARYA new theory in contact pressure distribution and friction limit surfaces for modeling of hemicylindrical soft fingertips is introduced, to define the relationship between friction force and the moment with respect to the normal axis of contact. A general pressure-distribution function is proposed to capture material properties and contact geometry with various pressure profiles, and the coefficient of pressure distribution over the rectangular contact area is found between π and π/2. Combining the results of the contact mechanics model with the contact pressure distribution, the normalized friction limit surface can be derived for anthropomorphic soft fingers. The numerical friction limit surface of hemicylindrical soft-finger contact can be approximated by an ellipse, with the major and minor axes as the maximum friction force and the maximum moment with respect to the normal axis of contact, respectively. The results show that the friction limit surfaces are improved (13%–17%), if hemicylindrical fingertips are used rather than hemispherical fingertips at the same radius of fingertip, shape factor of the pressure profile, and applied load. Furthermore, the results of the contact mechanics model and the pressure distribution for soft fingers facilitate the construction of numerical friction limit surfaces, enabling to analyze and simulate the contact behaviors of grasping and manipulation in humanoid robots, prosthetic hands, and robotic hands.

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Huang, Haiming, Junhao Lin, Linyuan Wu, Zhenkun Wen, and Mingjie Dong. "Trigger-Based Dexterous Operation with Multimodal Sensors for Soft Robotic Hand." Applied Sciences 11, no. 19 (September 26, 2021): 8978. http://dx.doi.org/10.3390/app11198978.

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This paper focuses on how to improve the operation ability of a soft robotic hand (SRH). A trigger-based dexterous operation (TDO) strategy with multimodal sensors is proposed to perform autonomous choice operations. The multimodal sensors include optical-based fiber curvature sensor (OFCS), gas pressure sensor (GPS), capacitive pressure contact sensor (CPCS), and resistance pressure contact sensor (RPCS). The OFCS embedded in the soft finger and the GPS series connected in the gas channel are used to detect the curvature of the finger. The CPCS attached on the fingertip and the RPCS attached on the palm are employed to detect the touch force. The framework of TDO is divided into sensor detection and action operation. Hardware layer, information acquisition layer, and decision layer form the sensor detection module; action selection layer, actuator drive layer, and hardware layer constitute the action operation module. An autonomous choice decision unit is used to connect the sensor detecting module and action operation module. The experiment results reveal that the TDO algorithm is effective and feasible, and the actions of grasping plastic framework, pinching roller ball pen and screwdriver, and handshake are executed exactly.

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Mohd Faudzi, Ahmad Athif, Junichiro Ooga, Tatsuhiko Goto, Masashi Takeichi, and Koichi Suzumori. "Index Finger of a Human-Like Robotic Hand Using Thin Soft Muscles." IEEE Robotics and Automation Letters 3, no. 1 (January 2018): 92–99. http://dx.doi.org/10.1109/lra.2017.2732059.

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Figliolini, Giorgio, and Pierluigi Rea. "Mechatronic design and experimental validation of a novel robotic hand." Industrial Robot: An International Journal 41, no. 1 (January 14, 2014): 98–108. http://dx.doi.org/10.1108/ir-04-2013-344.

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Purpose – The subject of the paper is the mechatronic design of a novel robotic hand, cassino-underactuated-multifinger-hand (Ca.U.M.Ha.), along with its prototype and the experimental analysis of its grasping of soft and rigid objects with different shapes, sizes and materials. The paper aims to discuss these issues. Design/methodology/approach – Ca.U.M.Ha. is designed with four identical underactuated fingers and an opposing thumb, all joined to a rigid palm and actuated by means of double-acting pneumatic cylinders. In particular, each underactuated finger with three phalanxes and one actuator is able to grasp cylindrical objects with different shapes and sizes, while the common electropneumatic operation of the four underactuated fingers gives an additional auto-adaptability to grasp objects with irregular shapes. Moreover, the actuating force control is allowed by a closed-loop pressure control within the pushing chambers of the pneumatic cylinders of the four underactuated fingers, because of a pair of two-way/two-position pulse-width-modulation (PWM) modulated pneumatic digital valves, which can also be operated under ON/OFF modes. Findings – The grasping of soft and rigid objects with different shapes, sizes and materials is a very difficult task that requires a complex mechatronic design, as proposed and developed worldwide, while Ca.U.M.Ha. offers these performances through only a single ON/OFF or analogue signal. Practical implications – Ca.U.M.Ha. could find several practical applications in industrial environments since it is characterized by a robust and low-cost mechatronic design, flexibility and easy control, which are based on the use of easy-running components. Originality/value – Ca.U.M.Ha. shows a novel mechatronic design that is based on a robust mechanical design and an easy operation and control with high dexterity and reliability to perform a safe grasp of objects with different shapes, sizes and materials.

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Chen, Kaiwen, Tao Li, Tongjie Yan, Feng Xie, Qingchun Feng, Qingzhen Zhu, and Chunjiang Zhao. "A Soft Gripper Design for Apple Harvesting with Force Feedback and Fruit Slip Detection." Agriculture 12, no. 11 (October 29, 2022): 1802. http://dx.doi.org/10.3390/agriculture12111802.

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This research presents a soft gripper for apple harvesting to provide constant-pressure clamping and avoid fruit damage during slippage, to reduce the potential danger of damage to the apple pericarp during robotic harvesting. First, a three-finger gripper based on the Fin Ray structure is developed, and the influence of varied structure parameters during gripping is discussed accordingly. Second, we develop a mechanical model of the suggested servo-driven soft gripper based on the mappings of gripping force, pulling force, and servo torque. Third, a real-time control strategy for the servo is proposed, to monitor the relative position relationship between the gripper and the fruit by an ultrasonic sensor to avoid damage from the slip between the fruit and fingers. The experimental results show that the proposed soft gripper can non-destructively grasp and separate apples. In outdoor orchard experiments, the damage rate for the grasping experiments of the gripper with the force feedback system turned on was 0%; while the force feedback system was turned off, the damage rate was 20%, averaged for slight and severe damage. The three cases of rigid fingers and soft fingers with or without slip detection under the gripper structure of this study were tested by picking 25 apple samples for each set of experiments. The picking success rate for the rigid fingers was 100% but with a damage rate of 16%; the picking success rate for soft fingers with slip detection was 80%, with no fruit skin damage; in contrast, the picking success rate for soft fingers with slip detection off increased to 96%, and the damage rate was up to 8%. The experimental results demonstrated the effectiveness of the proposed control method.

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Singh, Rippudaman, Sanjana Mohapatra, Pawandeep Singh Matharu, and Yonas Tadesse. "Twisted and coiled polymer muscle actuated soft 3D printed robotic hand with Peltier cooler for drug delivery in medical management." ACTA IMEKO 11, no. 3 (September 30, 2022): 1. http://dx.doi.org/10.21014/acta_imeko.v11i3.1269.

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Many robotic hands have been proposed to have unique designs and capabilities, focusing on sensing, actuation, and control. This paper presents experimental studies on a soft 3D-printed robotic hand whose fingers are actuated by twisted and coiled polymer (TCPFL) muscles, driven by resistive heating, and cooled by water and Peltier mechanism (thermoelectric cooling) for increasing the actuation frequency. The hand can be utilized for pick and place applications of drugs in clinical settings, which may be repetitive for humans. A combination of ABS plastic and thermoplastic polyurethane material is used to additively manufacture the robotic hand. The hand along with a housing tank for the muscles and Peltier coolers has a length of 380 mm and weighs 560 gm. The fabrication process of the TCPFL actuators coiled with 160 µm diameter nichrome wires is presented. The actuation frequency in the air for TCPFL is around 0.01 Hz. This study shows the effect of water and Peltier cooling on improving the actuation frequency of the muscles to 0.056 Hz. Experiments have been performed with a flex sensor integrated at the back of each finger to calculate its bend-extent while being actuated by the TCPFL muscles. All these experiments are also used to optimize the TCPFL actuation. Overall, a low-cost and lightweight 3D printed robotic hand is presented in this paper, which significantly increases the actuation performance with the help of cooling methods, that can be used in applications in medical management.

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Jović, Srđan, Nebojša Arsić, Ljubomir M. Marić, and Dalibor Petković. "RETRACTED ARTICLE: Estimation of contact forces of underactuated robotic finger using soft computing methods." Journal of Intelligent Manufacturing 30, no. 2 (January 5, 2017): 891–903. http://dx.doi.org/10.1007/s10845-016-1292-0.

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Elsherif, AR, M. I. Awad, S. A. Maged, and A. Ramzy. "Design and development of dual-acting soft actuator for assistance and rehabilitation of finger flexion and extension." Journal of Physics: Conference Series 2299, no. 1 (July 1, 2022): 012012. http://dx.doi.org/10.1088/1742-6596/2299/1/012012.

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Abstract The powerfulness of Soft robotic systems is relied to the safe performance. In addition to other advantages: the flexibility and deformability. Developing an assistive tool for Hand rehabilitation through soft pneumatic actuated hand gloves is an improved and suitable way for helping post stroke subjects. The Pneumatic network (Pneu-Net) actuators are soft actuators composed of pneumatic chambers actuates when pressurised with air. Dual acting soft pneumatic Pneu-Net actuator is developed as a part for building the glove, the actuator is designed for assisting both finger flexion and extension motions. Pneumatic network (Pneu-net) actuator is developed and design geometry effect is studied, mainly the influence of the dual actuators on each other in addition to the effect of the number of air chambers per each actuator. Design selection based on the finite element analysis and experimental testing, bending angle and energy efficiency parameters in addition to comfort and safe performance are the main criteria of concern.

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Tiziani, Lucas, Alexander Hart, Thomas Cahoon, Faye Wu, H. Harry Asada, and Frank L. Hammond. "Empirical characterization of modular variable stiffness inflatable structures for supernumerary grasp-assist devices." International Journal of Robotics Research 36, no. 13-14 (July 2, 2017): 1391–413. http://dx.doi.org/10.1177/0278364917714062.

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This paper presents the design, fabrication, and experimental characterization of modular, variable stiffness inflatable components for pneumatically actuated supernumerary robotic (SR) grasp-assist devices. The proposed SR grasp-assist devices are comprised of soft rigidizable finger phalanges and variable stiffness pneumatic bending actuators that are manufactured using soft lithography fabrication methods. The mechanical and kinematic properties of these modular, inflatable components are characterized experimentally under various loading conditions and over a range of geometric design parameters. The resulting data-driven properties are then used to predict the grasp strengths and motion patterns of SR grasp-assist device configurations designed to accommodate the manipulation of daily living objects. Experimental results demonstrate the ability to program grasp synergies into SR fingers by strategic inflation of the bending actuator antagonist chambers (varying mechanical stiffness), without the need for complicated, high-power mechanisms or precise, low-level motion control. The results also demonstrate the underactuated grasp adaptations enabled by modular inflatable components and the ability to predict mechanical grasping capabilities of wearable pneumatic SR grasp-assist devices using insights from empirical data.

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Jović, Srđan, Nebojša Arsić, Ljubomir M. Marić, and Dalibor Petković. "Retraction Note to: Estimation of contact forces of underactuated robotic finger using soft computing methods." Journal of Intelligent Manufacturing 31, no. 3 (January 13, 2020): 797. http://dx.doi.org/10.1007/s10845-019-01529-1.

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Wang, Yaofeng, Fan Wang, Yang Kong, Lei Wang, and Qinchuan Li. "Novel ionic bioartificial muscles based on ionically crosslinked multi-walled carbon nanotubes-mediated bacterial cellulose membranes and PEDOT:PSS electrodes." Smart Materials and Structures 31, no. 2 (January 4, 2022): 025023. http://dx.doi.org/10.1088/1361-665x/ac4576.

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Abstract High-performance bioartificial muscles with low-cost, large bending deformation, low actuation voltage, and fast response time have drawn extensive attention as the development of human-friendly electronics in recent years. Here, we report a high-performance ionic bioartificial muscle based on the bacterial cellulose (BC)/ionic liquid (IL)/multi-walled carbon nanotubes (MWCNT) nanocomposite membrane and PEDOT:PSS electrode. The developed ionic actuator exhibits excellent electro-chemo-mechanical properties, which are ascribed to its high ionic conductivity, large specific capacitance, and ionically crosslinked structure resulting from the strong ionic interaction and physical crosslinking among BC, IL, and MWCNT. In particular, the proposed BC-IL-MWCNT (0.10 wt%) nanocomposite exhibited significant increments of Young’s modulus up to 75% and specific capacitance up to 77%, leading to 2.5 times larger bending deformation than that of the BC-IL actuator. More interestingly, bioinspired applications containing artificial soft robotic finger and grapple robot were successfully demonstrated based on high-performance BC-IL-MWCNT actuator with excellent sensitivity and controllability. Thus, the newly proposed BC-IL-MWCNT bioartificial muscle will offer a viable pathway for developing next-generation artificial muscles, soft robotics, wearable electronic products, flexible tactile devices, and biomedical instruments.

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FASOULAS, J., and Z. DOULGERI. "ACTIVE CONTROL OF ROLLING MANOEUVRES OF A ROBOTIC FINGER WITH HEMISPHERICAL TIP." International Journal of Humanoid Robotics 07, no. 01 (March 2010): 183–212. http://dx.doi.org/10.1142/s0219843610002039.

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In this paper we are concerned with the problem of sensory motor coordination of a robotic finger in order to evoke rolling maneuvers in a force-positioning task on a flat rigid surface. We use two different approaches to modeling the reaction of the soft fingertip with the contacted surface. Firstly, we assume that the environment imposes a purely kinematic rolling constraint on the end-effector motion in the tangent direction of the contacted surface. This implies no energy transfer or dissipation between the fingertip and the environment due to frictional forces. On the other hand, we assume that it is feasible for the fingertip to slip in which case pure rolling motion could be disturbed. The two different models are subsequently used to show by simulation that control laws, which have been designed on a rolling constraint dynamic model for frictional forces, fail to perform rolling in various environments. An extra control input that uses a reference rolling trajectory that is state dependent is proposed, which, if superimposed on a conventional force-position control law, can achieve rolling even on a surface with low friction characteristics. The proposed feedback signal does not utilize the modeling information in the control formulation, and thus permits easy implementation. Finally, the total controller is shown to achieve asymptotic convergence to the desired force-positioning task by simultaneously evoking pure rolling motion for the fingertip.

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Stuart, Hannah, Shiquan Wang, Oussama Khatib, and Mark R. Cutkosky. "The Ocean One hands: An adaptive design for robust marine manipulation." International Journal of Robotics Research 36, no. 2 (February 2017): 150–66. http://dx.doi.org/10.1177/0278364917694723.

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Underactuated, compliant, tendon-driven robotic hands are suited for deep-sea exploration. The robust Ocean One hand design utilizes elastic finger joints and a spring transmission to achieve a variety of pinch and wrap grasps. Compliance in the fingers and transmission determines the degree of load-sharing among contacts and the hands’ ability to secure irregularly shaped objects. However, it can also decrease external grasp stiffness and acquisition reliability. SimGrasp, a flexible dynamic hand simulator, enables parametric studies of the hand for acquisition and pull-out tests with varying transmission spring rates. In the present application, we take advantage of achieving different stiffnesses by reversing the direction of tendon windup using a torsional spring-loaded winch. With this provision, the hand can be relatively soft for handling delicate objects and stiff for tasks requiring strength. Two hands were field-tested as part of the Ocean One humanoid platform, which acquired a vase from the La Lune shipwreck site at a 91 m depth in the Mediterranean Sea.

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Mishra, Anand K., Thomas J. Wallin, Wenyang Pan, Patricia Xu, Kaiyang Wang, Emmanuel P. Giannelis, Barbara Mazzolai, and Robert F. Shepherd. "Autonomic perspiration in 3D-printed hydrogel actuators." Science Robotics 5, no. 38 (January 29, 2020): eaaz3918. http://dx.doi.org/10.1126/scirobotics.aaz3918.

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In both biological and engineered systems, functioning at peak power output for prolonged periods of time requires thermoregulation. Here, we report a soft hydrogel-based actuator that can maintain stable body temperatures via autonomic perspiration. Using multimaterial stereolithography, we three-dimensionally print finger-like fluidic elastomer actuators having a poly-N-isopropylacrylamide (PNIPAm) body capped with a microporous (~200 micrometers) polyacrylamide (PAAm) dorsal layer. The chemomechanical response of these hydrogel materials is such that, at low temperatures (<30°C), the pores are sufficiently closed to allow for pressurization and actuation, whereas at elevated temperatures (>30°C), the pores dilate to enable localized perspiration in the hydraulic actuator. Such sweating actuators exhibit a 600% enhancement in cooling rate (i.e., 39.1°C minute−1) over similar non-sweating devices. Combining multiple finger actuators into a single device yields soft robotic grippers capable of both mechanically and thermally manipulating various heated objects. The measured thermoregulatory performance of these sweating actuators (~107 watts kilogram−1) greatly exceeds the evaporative cooling capacity found in the best animal systems (~35 watts kilogram−1) at the cost of a temporary decrease in actuation efficiency.

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Yang, Wentuo, Mengying Xie, Xiaoshuang Zhang, Xueyou Sun, Cheng Zhou, Ye Chang, Hainan Zhang, and Xuexin Duan. "Multifunctional Soft Robotic Finger Based on a Nanoscale Flexible Temperature–Pressure Tactile Sensor for Material Recognition." ACS Applied Materials & Interfaces 13, no. 46 (November 15, 2021): 55756–65. http://dx.doi.org/10.1021/acsami.1c17923.

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Zhu, Mingzhu, Mengying Xie, Xuanming Lu, Shima Okada, and Sadao Kawamura. "A soft robotic finger with self-powered triboelectric curvature sensor based on multi-material 3D printing." Nano Energy 73 (July 2020): 104772. http://dx.doi.org/10.1016/j.nanoen.2020.104772.

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Kladovasilakis, Nikolaos, Paschalis Sideridis, Dimitrios Tzetzis, Konstantinos Piliounis, Ioannis Kostavelis, and Dimitrios Tzovaras. "Design and Development of a Multi-Functional Bioinspired Soft Robotic Actuator via Additive Manufacturing." Biomimetics 7, no. 3 (August 3, 2022): 105. http://dx.doi.org/10.3390/biomimetics7030105.

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The industrial revolution 4.0 has led to a burst in the development of robotic automation and platforms to increase productivity in the industrial and health domains. Hence, there is a necessity for the design and production of smart and multi-functional tools, which combine several cutting-edge technologies, including additive manufacturing and smart control systems. In the current article, a novel multi-functional biomimetic soft actuator with a pneumatic motion system was designed and fabricated by combining different additive manufacturing techniques. The developed actuator was bioinspired by the natural kinematics, namely the motion mechanism of worms, and was designed to imitate the movement of a human finger. Furthermore, due to its modular design and the ability to adapt the actuator’s external covers depending on the requested task, this actuator is suitable for a wide range of applications, from soft (i.e., fruit grasping) or industrial grippers to medical exoskeletons for patients with mobility difficulties and neurological disorders. In detail, the motion system operates with two pneumatic chambers bonded to each other and fabricated from silicone rubber compounds molded with additively manufactured dies made of polymers. Moreover, the pneumatic system offers multiple-degrees-of-freedom motion and it is capable of bending in the range of −180° to 180°. The overall pneumatic system is protected by external covers made of 3D printed components whose material could be changed from rigid polymer for industrial applications to thermoplastic elastomer for complete soft robotic applications. In addition, these 3D printed parts control the angular range of the actuator in order to avoid the reaching of extreme configurations. Finally, the bio-robotic actuator is electronically controlled by PID controllers and its real-time position is monitored by a one-axis soft flex sensor which is embedded in the actuator’s configuration.

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Pagoli, Amir, Frédéric Chapelle, Juan-Antonio Corrales-Ramon, Youcef Mezouar, and Yuri Lapusta. "Large-Area and Low-Cost Force/Tactile Capacitive Sensor for Soft Robotic Applications." Sensors 22, no. 11 (May 27, 2022): 4083. http://dx.doi.org/10.3390/s22114083.

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This paper presents a novel design and development of a low-cost and multi-touch sensor based on capacitive variations. This new sensor is very flexible and easy to fabricate, making it an appropriate choice for soft robot applications. Materials (conductive ink, silicone, and control boards) used in this sensor are inexpensive and easily found in the market. The proposed sensor is made of a wafer of different layers, silicone layers with electrically conductive ink, and a pressure-sensitive conductive paper sheet. Previous approaches like e-skin can measure the contact point or pressure of conductive objects like the human body or finger, while the proposed design enables the sensor to detect the object’s contact point and the applied force without considering the material conductivity of the object. The sensor can detect five multi-touch points at the same time. A neural network architecture is used to calibrate the applied force with acceptable accuracy in the presence of noise, variation in gains, and non-linearity. The force measured in real time by a commercial precise force sensor (ATI) is mapped with the produced voltage obtained by changing the layers’ capacitance between two electrode layers. Finally, the soft robot gripper embedding the suggested tactile sensor is utilized to grasp an object with position and force feedback signals.

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Nishimura, Toshihiro, Kensuke Shimizu, Seita Nojiri, Kenjiro Tadakuma, Yosuke Suzuki, Tokuo Tsuji, and Tetsuyou Watanabe. "Soft Robotic Hand With Finger-Bending/Friction-Reduction Switching Mechanism Through 1-Degree-of-Freedom Flow Control." IEEE Robotics and Automation Letters 7, no. 2 (April 2022): 5695–702. http://dx.doi.org/10.1109/lra.2022.3157964.

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Hussain, Irfan, Gionata Salvietti, Giovanni Spagnoletti, and Domenico Prattichizzo. "The Soft-SixthFinger: a Wearable EMG Controlled Robotic Extra-Finger for Grasp Compensation in Chronic Stroke Patients." IEEE Robotics and Automation Letters 1, no. 2 (July 2016): 1000–1006. http://dx.doi.org/10.1109/lra.2016.2530793.

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Journal articles on the topic 'Soft robotic finger'

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