Thematische Bibliographien / Soft hands

Auswahl der wissenschaftlichen Literatur zum Thema „Soft hands“

Autor: Grafiati

Veröffentlicht am 14. März 2023

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Zeitschriftenartikel zum Thema "Soft hands":

Hirai, Shinichi, und Zhongkui Wang. „Object Manipulation by Soft Hands“. Journal of the Robotics Society of Japan 40, Nr. 5 (2022): 369–74. http://dx.doi.org/10.7210/jrsj.40.369.

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Watanabe, Tetsuyou. „Manipulation with Soft Robotic Hands“. Journal of the Robotics Society of Japan 37, Nr. 1 (2019): 30–33. http://dx.doi.org/10.7210/jrsj.37.30.

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Gilday, Kieran, und Fumiya Iida. „Intelligent Soft Hands and Benchmarking towards General-Purpose Robotic Manipulation“. IOP Conference Series: Materials Science and Engineering 1261, Nr. 1 (01.10.2022): 012010. http://dx.doi.org/10.1088/1757-899x/1261/1/012010.

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Abstract In order to progress the development of intelligent soft hands for general-purpose use in humanoid robots, social assistive robots, adaptive manufacturing, prosthetics and more, we need to rethink our approach to benchmarking. Where previously, hands are compared by their performance in a limited set of tasks, resulting in performance optimisations in the subjective, most common tasks. Instead, we must focus on increasing the hand’s potential at the lowest level, by improving the underlying passive behaviours, in terms of increased behavioural diversity and cheap control.

Andrade, Guilherme Neves Lourenço, Adham do Amaral e Castro, Paulo Eduardo Daruge Grando, Eduardo Baptista, Frederico Celestino Miranda, Viviane Sayuri Yamachira, Erina Megumi Nagaya Fukamizu et al. „Hands on Hands! Soft-Tissue Tumors and Bone Tumors Involving the Hand“. Contemporary Diagnostic Radiology 45, Nr. 17 (15.08.2022): 1–7. http://dx.doi.org/10.1097/01.cdr.0000854592.69523.ac.

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Hirai, Shinichi, und Zhongkui Wang. „Soft Robotic Hands for Food Material Handling“. Journal of the Robotics Society of Japan 37, Nr. 6 (2019): 489–94. http://dx.doi.org/10.7210/jrsj.37.489.

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Choi, Changhyun, Wilko Schwarting, Joseph DelPreto und Daniela Rus. „Learning Object Grasping for Soft Robot Hands“. IEEE Robotics and Automation Letters 3, Nr. 3 (Juli 2018): 2370–77. http://dx.doi.org/10.1109/lra.2018.2810544.

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Zhou, Xuance, Carmel Majidi und Oliver M. O’Reilly. „Soft hands: An analysis of some gripping mechanisms in soft robot design“. International Journal of Solids and Structures 64-65 (Juli 2015): 155–65. http://dx.doi.org/10.1016/j.ijsolstr.2015.03.021.

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UMLAS, M. E., R. J. BISCHOFF und R. H. GELBERMAN. „Predictors of Neurovascular Displacement in Hands with Dupuytren’s Contracture“. Journal of Hand Surgery 19, Nr. 5 (Oktober 1994): 664–66. http://dx.doi.org/10.1016/0266-7681(94)90140-6.

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A prospective study of hands with Dupuytren’s contracture was designed to test the association of three variables, the presence of an interdigital soft tissue mass, the presence of flexion contractures at each digital joint, and the duration of contracture, with the formation of spiral nerves. 66 digits in 37 hands affected by Dupuytren’s disease were examined intra-operatively. Of the 34 digits (52%) with spiral nerves, 28 had soft tissue masses (42%). The sensitivity of a soft tissue mass alone as a predictor of a spiral nerve was 59% and the specificity 75%. The presence of a flexion contracture at the PIP joint had a sensitivity of 88% and a specificity of 62% for the presence of a spiral nerve. The combination of a soft tissue mass and a PIP joint contracture was a very specific (94%) but not a particularly sensitive (50%) test for spiral nerve formation. The formation of a spiral nerve is progressive, occurring most often in hands with significant PIP joint contractures with or without soft tissue interdigital masses.

KANOJIA, R. K., N. SHARMA und S. K. KAPOOR. „Preliminary Soft Tissue Distraction Using External Fixator in Radial Club Hand“. Journal of Hand Surgery (European Volume) 33, Nr. 5 (Oktober 2008): 622–27. http://dx.doi.org/10.1177/1753193408093809.

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Preliminary soft tissue distraction using an external fixator before centralisation and tendon transfer of the flexor and extensor carpi ulnaris to the little finger metacarpal was used to treat Bayne’s type III and IV deformities in 18 hands of 14 patients with radial club hands. Treatment with external fixator was started at a mean age of 8 (range 3–30) months. In 16 of 18 hands, the surgical treatment was completed before 10 months of age. Adequate soft tissue stretching was achieved before centralisation using fractional distraction with the external fixator in the majority of hands. After an average follow-up period of 31 months, there were seven good, eight satisfactory and one unsatisfactory result.

Tian, Li, Jianmin Zheng, Nadia Magnenat Thalmann, Hanhui Li, Qifa Wang, Jialin Tao und Yiyu Cai. „Design of a Single-Material Complex Structure Anthropomorphic Robotic Hand“. Micromachines 12, Nr. 9 (18.09.2021): 1124. http://dx.doi.org/10.3390/mi12091124.

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In the field of robotic hand design, soft body and anthropomorphic design are two trends with a promising future. Designing soft body anthropomorphic robotic hands with human-like grasping ability, but with a simple and reliable structure, is a challenge that still has not been not fully solved. In this paper, we present an anatomically correct robotic hand 3D model that aims to realize the human hand’s functionality using a single type of 3D-printable material. Our robotic hand 3D model is combined with bones, ligaments, tendons, pulley systems, and tissue. We also describe the fabrication method to rapidly produce our robotic hand in 3D printing, wherein all parts are made by elastic 50 A (shore durometer) resin. In the experimental section, we show that our robotic hand has a similar motion range to a human hand with substantial grasping strength and compare it with the latest other designs of anthropomorphic robotic hands. Our new design greatly reduces the fabrication cost and assembly time. Compared with other robotic hand designs, we think our robotic hand may induce a new approach to the design and production of robotic hands as well as other related mechanical structures.

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Dissertationen zum Thema "Soft hands":

Pozzi, Maria. „Grasping and Manipulation with Soft Robotic Hands“. Doctoral thesis, Università di Siena, 2019. http://hdl.handle.net/11365/1073188.

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As robots get closer to humans, their ability to safely interact with unstructured environments proves to be essential, and the adoption of soft, or compliant, end-effectors becomes necessary. Robotic hands and grippers can exhibit a soft behaviour both by passive compliant elements embedded in their hardware design, and by active stiffness control strategies. The work presented in this Thesis dealt with both aspects and was aimed at finding answers to the growing need of mathematical models and shared standards in the emerging field of soft manipulation. Starting from the classical modelling tools provided by the kinematic analysis of robotic manipulators and the quasi-static analysis of grasping, a new simulation framework for intrinsically soft fingers was defined, together with new grasp quality indices suitable for underactuated and compliant hands. Then, the closure signature model was devised. Such model cut ties with the traditional models introducing a completely new way of representing robotic hands, that focused more on their capabilities, rather than their kinematic structure. The information provided by the closure signature was found to be useful for planning power grasps with soft robotic hands. Regarding active stiffness control strategies, methods that allow to regulate the grasp stiffness of fully-actuated, torque-controlled rigid hands were conceived with a bio-inspired approach and were extensively tested. Models and control paradigms presented in this Thesis are general enough to be used with different robotic setups with respect to those that were already tested. Future work will focus on both, the further application of the achieved results, and their theoretical extension to address other open questions, including environmental constraints exploitation in grasping and benchmarking of soft manipulation.

Marullo, Sara. „Modelling and Controlling Soft Interactions“. Doctoral thesis, Università di Siena, 2022. http://hdl.handle.net/11365/1196028.

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Compliance is a key factor during physical interactions between agents and objects, allowing delicate and robust manipulation. Such a compliance can reside in human and robotic hands, as well as in objects present in the environment. This Thesis arose from the quest for mechanical conditions fostering object manipulation, and shaped as an investigation on techniques to model and control the compliance in soft interactions. Human and robotic hands are considered, functional and biomechanical models are discussed, devised and validated. To deal with unpredictable configurations assumed by intrinsically and passively-compliant underactuated robotic hands, a solution based on magnetic actuation is proposed. The exploitation of small magnetic elements allows also to simplify the robotic end-effector design by relying on local interactions to manipulate extremely deformable objects like garments. Moreover, mechanical forces exchanged during physical interactions are used to devise a control strategy for human-robot cooperative grasping, relying on a novel contact model exploiting linear elastic patches to ensure the contact permanence. The Research work contained in this Thesis shows that developing techniques for implementing robotic soft interactions is feasible and can significantly broaden the spectrum of robotic applications in real-world scenarios. An extensive experimental validation of the theoretic work supports the discussion.

Deimel, Raphael [Verfasser], Oliver [Akademischer Betreuer] Brock, Kaspar [Gutachter] Althoefer und Sami [Gutachter] Haddadin. „Soft robotic hands for compliant grasping / Raphael Deimel ; Gutachter: Kaspar Althoefer, Sami Haddadin ; Betreuer: Oliver Brock“. Berlin : Technische Universität Berlin, 2017. http://d-nb.info/1156179505/34.

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Seiger, Cronfalk Berit. „Being in safe hands : the experiences of soft tissue massage as a complement in palliative care. Intervention studies concerning patients, relatives and nursing staff“. Doctoral thesis, Ersta Sköndal högskola, Enheten för forskning om vård i livets slutskede, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:esh:diva-602.

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Homberg, Bianca (Bianca S. ). „Robust proprioceptive grasping with a soft robot hand“. Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/106123.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 85-88).
This work presents a soft hand capable of robustly grasping and identifying objects based on internal state measurements along with a combined system which autonomously performs grasps. A highly compliant soft hand allows for intrinsic robustness to grasping uncertainties; the addition of internal sensing allows the configuration of the hand and object to be detected. The hand can be configured in different ways using finger unit modules. The finger module includes resistive force sensors on the fingertips for contact detection and resistive bend sensors for measuring the curvature profile of the finger. The curvature sensors can be used to estimate the contact geometry and thus to distinguish between a set of grasped objects. With one data point from each finger, the object grasped by the hand can be identified. A clustering algorithm to find the correspondence for each grasped object is presented for both enveloping grasps and pinch grasps. This hand is incorporated into a full system with vision and motion planning on the Baxter robot to autonomously perform grasps of objects placed on a table. This hand is a first step towards proprioceptive soft grasping.
by Bianca Homberg.
M. Eng.

Rubiano, Fonseca Astrid. „Smart control of a soft robotic hand prosthesis“. Thesis, Paris 10, 2016. http://www.theses.fr/2016PA100189/document.

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Le sujet principal de cette thèse est le développement d’un contrôle commande intelligentpour une prothèse de main robotique avec des parties souples qui comporte: (i) uneinterface homme–machine permettant de contrôler notre prothèse, (ii) et des stratégiesde contrôle améliorant les performances de la main robotique. Notre approche tientcompte : 1. du développement d’une interaction intuitive entre l'homme et la prothèse facilitantl'utilisation de la main, d'un système d’interaction entre l’utilisateur et la mainreposant sur l'acquisition de signaux ElectroMyoGrammes superficiels (sEMG) aumoyen d'un dispositif placé sur l'avant-bras du patient. Les signaux obtenus sontensuite traités avec un algorithme basé sur l'intelligence artificielle, en vued'identifier automatiquement les mouvements désirés par le patient.2. du contrôle de la main robotique grâce à la détection du contact avec l’objet et de lathéorie du contrôle hybride.Ainsi, nous concentrons notre étude sur : (i) l’établissement d’une relation entre lemouvement du membre supérieur et les signaux sEMG, (ii) les séparateurs à vaste margepour classer les patterns obtenues à partir des signaux sEMG correspondant auxmouvements de préhension, (iii) le développement d'un système de reconnaissance depréhension à partir d'un dispositif portable MyoArmbandTM, (iv) et des stratégieshybrides de contrôle commande de force-position de notre main robotique souple
The target of this thesis disertation is to develop a new Smart control of a soft robotic hand prosthesis for the soft robotic hand prosthesis called ProMain Hand, which is characterized by:(i) flexible interaction with grasped object, (ii) and friendly-intuitive interaction between human and robot hand. Flexible interaction results from the synergies between rigid bodies and soft bodies, and actuation mechanism. The ProMain hand has three fingers, each one is equipped with three phalanges: proximal, medial and distal. The proximal and medial are built with rigid bodies,and the distal is fabricated using a deformable material. The soft distal phalange has a new smart force sensor, which was created with the aim to detect contact and force in the fingertip, facilitating the control of the hand. The friendly intuitive human-hand interaction is developed to facilitate the hand utilization. The human-hand interaction is driven by a controller that uses the superficial electromyographic signals measured in the forearm employing a wearable device. The wearable device called MyoArmband is placed around the forearm near the elbow joint. Based on the signals transmitted by the wearable device, the beginning of the movement is automatically detected, analyzing entropy behavior of the EMG signals through artificial intelligence. Then, three selected grasping gesture are recognized with the following methodology: (i) learning patients entropy patterns from electromyographic signals captured during the execution of selected grasping gesture, (ii) performing a support vector machine classifier, using raw entropy data extracted in real time from electromyographic signals

Ramirez, Arias José Luis. „Development of an artificial muscle for a soft robotic hand prosthesis“. Thesis, Paris 10, 2016. http://www.theses.fr/2016PA100190/document.

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Le thème central de cette thèse est la conception d’actionneurs doux à partir de matériaux intelligents et d’une prothèse de main robotique souple. Notre approche prends en compte les différents points qui peuvent influer sur le développement d’une stratégie d’actionnement ou d’un muscle artificiel : i) Les mécanismes et la fonctionnalité de la main humaine afin d’identifier les exigences fonctionnelles pour une prothèse de main robotique en matière de préhension. ii) L’analyse et l’amélioration des mécanismes de la main robotique pour intégrer un comportement souple dans la prothèse. iii) L’évaluation expérimentale de la prothèse de main robotique afin d’identifier les spécifications du système d’actionnement nécessaire au fonctionnement cinématique et dynamique du robot. iv) Le développement et la modélisation d’une stratégie d’actionnement utilisant des matériaux intelligents.Ces points sont abordés successivement dans les 4 chapitres de cette thèse1. Analyse du mouvement de la main humaine pour l’identification des exigences technologiques pour la prothèse de main robotique.2. Conception et modélisation de la prothèse de main robotique à comportement souple.3. Evaluation mécatronique de la prothèse de main.4. Conception d’un muscle artificiel basé sur des matériaux intelligents
In the field of robotic hand prosthesis, the use of smart and soft materials is helpful in improving flexibility, usability, and adaptability of the robots, which simplify daily living activities of prosthesis users. However, regarding the smart materials for artificial muscles, technologies are considered to be far from implementation in anthropomorphic robotic hands. Therefore, the target of this thesis dissertation is to reduce the gap between smart material technologies and robotic hand prosthesis. Five central axes address the problem: i)identification of useful grasping gestures and reformulation of the robotic hand mechanism, ii) analysis of human muscle behavior to mimic human grasping capabilities, iii) modeling robot using the hybrid model DHKK-SRQ for the kinematics and the virtual works principle for dynamics, iv) definition of actuation requirements considering the synergy between prehension conditions and robot mechanism, and v) development of a smart material based actuation system.This topics are addressed in four chapters:1. Human hand movement analysis toward the hand prosthesis requirements2. Design and modeling of the soft robotic hand ProMain-I3. Mechatronic assessment of Prosthetic hand4. Development of an artificial muscle based on smart materials

Petinari, Andrea. „Hand rehabilitation device for extension, opposition and reposition“. Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020.

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In this paper, the research focused on the development of a hand rehabilitation device which could perform extension, opposition and reposition movements. Firstly, the anatomy of the hand is analyzed and studied to understand where the problem resides; since the mechanism will be applied to post-stroke patients, it is necessary to comprehend the structure and the articulations of the hand, the muscles involved in the mentioned movements and how a healthy hand works. Then, the causes of the problem are studied, what are the consequences on the hand and how to solve every issue. Brunnström Approach is taken as reference for the rehabilitation therapy steps. After the performance target is defined and which function has the priority, a brief research on the state of the art is made. Six different devices are analyzed, taking into account their strengths and weaknesses, evaluating them and trying to find possible lacks to solve. An evaluation of possible solutions is done, in order to find the optimal solution for the problem. Various types of actuation and structure of the mechanism are considered. Defined which are the best choices between the ones proposed, the next step is to design a first prototype with the purpose of bringing together the solutions selected. The CAD used is PTC Creo Parametric. Once the first prototype was designed, it was partially printed with 3D technique (additive manufacturing) and tested; tests were made on the actuation and on the device to evaluated its efficacy. The results are visible in this paper. Finally, a conclusion is discussed with a short resume of the experiments made and the results obtained. Furthermore, remaining problems and future works are analyzed and debated.

Kibria, Raihan Hassnain [Verfasser], und Hans [Akademischer Betreuer] Eveking. „Soft Computing Approaches to DPLL SAT Solver Optimization / Raihan Hassnain Kibria. Betreuer: Hans Eveking“. Darmstadt : Universitäts- und Landesbibliothek Darmstadt, 2011. http://d-nb.info/1105563952/34.

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Wirekoh, Jackson O. „Development of Soft Actuation Systems for Use in Human-Centered Applications“. Research Showcase @ CMU, 2017. http://repository.cmu.edu/dissertations/1124.

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In recent years, soft materials have seen increased prevalence in the design of robotic systems and wearables capable of addressing the needs of individuals living with disabilities. In particular, pneumatic artificial muscles (PAMs) have readily been employed in place of electromagnetic actuators due to their ability to produce large forces and motions, while still remaining lightweight, compact, and flexible. Due to the inherent nonlinearity of PAMs however, additional external or embedded sensors must be utilized in order to effectively control the overall system. In the case of external sensors, the bulkiness of the overall system is increased, which places limits on the system’s design. Meanwhile, the traditional cylindrical form factor of PAMs limits their ability to remain compact and results in overly complex fabrication processes when embedded fibers and/or sensing elements are required to provide efficient actuation and control. In order to overcome these limitations, this thesis proposed the design of flat pneumatic artificial muscles (FPAMs) capable of being fabricated using a simple layered manufacturing process, in which water-soluble masks were utilized to create collapsed air chambers. Furthermore, hyperelastic deformation models were developed to approximate the mechanical performance of the FPAMs and were verified through experimental characterization. The feasibility of these design techniques to meet the requirements of human centered applications, including the suppression of hand tremors and catheter ablation procedures, was explored and the potential for these soft actuation systems to act as solutions in other real world applications was demonstrated. We expect the design, fabrication, and modeling techniques developed in this thesis to aid in the development of future wearable devices and motivate new methods for researchers to employ soft pneumatic systems as solutions in human-centered applications.

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Bücher zum Thema "Soft hands":

Ward, B. J. Landing in New Jersey with soft hands. Berkeley, CA: North Atlantic Books, 1994.

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Inoue, Takahiro. Mechanics and control of soft-fingered manipulation. London: Springer, 2009.

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Inoue, Takahiro. Mechanics and control of soft-fingered manipulation. London: Springer, 2009.

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Inoue, Takahiro. Mechanics and control of soft-fingered manipulation. London: Springer, 2009.

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Inoue, Takahiro. Mechanics and control of soft-fingered manipulation. London: Springer, 2009.

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Xiaohoulaoshi. Si ji shou zuo yang mao zhan =: Oh! two hands four seasons wool felt. 8. Aufl. Taibei Shi: Tai shi wen hua shi ye gu fen you xian gong si, 2012.

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Araujo, Ana. Felt from the heart: How to hand-stitch cute and cuddly felt stuffies. East Petersburg, PA: Design Originals, 2013.

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Chen, Cheng-Hung, und Desineni Subbaram Naidu. Fusion of Hard and Soft Control Strategies for the Robotic Hand. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2017. http://dx.doi.org/10.1002/9781119273622.

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B, MacDonald Robert, und United States. National Aeronautics and Space Administration., Hrsg. In the soft-to-hand technical spectrum: Where is software engineering? [Houston, Tex.?]: Research Institute for Computing and Information Systems, University of Houston-Clear Lake, 1992.

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D'Cruze, Shani. Our time in God's hands: Religion and the middling sort in eighteenth century Colchester. [Chelmsford, Essex]: Essex Record Office in collaboration with the Local History Centre, University of Essex, 1991.

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Buchteile zum Thema "Soft hands":

Deimel, Raphael, und Oliver Brock. „Soft Hands for Reliable Grasping Strategies“. In Soft Robotics, 211–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-44506-8_18.

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Nagy, Zsolt. „Your Future Is in Your Hands“. In Soft Skills to Advance Your Developer Career, 275–90. Berkeley, CA: Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-5092-1_8.

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Chen, Wei. „Retrospection and Consideration of Competitive Taiji Push Hands“. In Advances in Intelligent and Soft Computing, 111–17. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25538-0_17.

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Parab, Jivan S., Rajendra S. Gad und G. M. Naik. „Building Embedded Systems Using Soft IP Cores“. In Hands-on Experience with Altera FPGA Development Boards, 73–78. New Delhi: Springer India, 2017. http://dx.doi.org/10.1007/978-81-322-3769-3_4.

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Li, Bowen, Jiangxia Shi und Wenzeng Zhang. „MESA Finger: A Multisensory Electronic Self-Adaptive Unit for Humanoid Robotic Hands“. In Advances in Intelligent and Soft Computing, 395–400. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27951-5_59.

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Tavakoli, Mahmoud, Rui Pedro Rocha, João Lourenço, Tong Lu und Carmel Majidi. „Soft Bionics Hands with a Sense of Touch Through an Electronic Skin“. In Soft Robotics: Trends, Applications and Challenges, 5–10. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46460-2_2.

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Mossakowski, Krzysztof, und Jacek Mańdziuk. „Neural Networks and the Estimation of Hands’ Strength in Contract Bridge“. In Artificial Intelligence and Soft Computing – ICAISC 2006, 1189–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11785231_124.

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Choi, Changhyun, Joseph Del Preto und Daniela Rus. „Using Vision for Pre- and Post-grasping Object Localization for Soft Hands“. In Springer Proceedings in Advanced Robotics, 601–12. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-50115-4_52.

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Rosen, Alyx, Shino Bay Aguilera, Drew Taylor und Eduardo Weiss. „Soft Tissue Augmentation (Temporary Injectable Fillers) on the Trunk and Extremities (Hands, Feet, Trunk)“. In Evidence-Based Procedural Dermatology, 679–702. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-02023-1_40.

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Yoshikawa, Tsuneo, Masanao Koeda und Hiroshi Fujimoto. „Shape Recognition and Optimal Grasping of Unknown Objects by Soft-Fingered Robotic Hands with Camera“. In Experimental Robotics, 537–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00196-3_62.

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Konferenzberichte zum Thema "Soft hands":

Bonilla, M., E. Farnioli, C. Piazza, M. Catalano, G. Grioli, M. Garabini, M. Gabiccini und A. Bicchi. „Grasping with Soft Hands“. In 2014 IEEE-RAS 14th International Conference on Humanoid Robots (Humanoids 2014). IEEE, 2014. http://dx.doi.org/10.1109/humanoids.2014.7041421.

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Salvietti, G., Z. Iqbal, M. Malvezzi, T. Eslami und D. Prattichizzo. „Soft Hands with Embodied Constraints: The Soft ScoopGripper“. In 2019 International Conference on Robotics and Automation (ICRA). IEEE, 2019. http://dx.doi.org/10.1109/icra.2019.8793563.

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Zhao, Longchao, und Satyandra K. Gupta. „Design, Manufacturing, and Characterization of a Pneumatically-Actuated Soft Hand“. In ASME 2018 13th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/msec2018-6622.

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Soft robotic hands can be used to manipulate delicate parts. The use of under-actuated fingers can significantly reduce the number of actuators and the complexity of the hand structure. This in turn can lower the cost of realizing robotic hands. This paper presents a new design for a multi-fingered soft hand for robotic applications. We adapt the fusible core molding process to realize complex inner cavities needed in pneumatically-actuated fingers. We also introduce a method for predicting the finger motion using pseudo-rigid-body model. We demonstrate that the soft hand can achieve the desired shapes and apply the required forces in tasks such as handling, grasping, pinching, clipping, and fastening.

Schlagenhauf, Cornelia, Dominik Bauer, Kai-Hung Chang, Jonathan P. King, Daniele Moro, Stelian Coros und Nancy Pollard. „Control of Tendon-Driven Soft Foam Robot Hands“. In 2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids). IEEE, 2018. http://dx.doi.org/10.1109/humanoids.2018.8624937.

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Grbic und Nordholm. „Soft constrained subband beamforming for hands-free speech enhancement“. In IEEE International Conference on Acoustics Speech and Signal Processing ICASSP-02. IEEE, 2002. http://dx.doi.org/10.1109/icassp.2002.1005882.

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Grbic, Nedelko, und Sven Nordholm. „Soft constrained subband beamforming for hands-free speech enhancement“. In Proceedings of ICASSP '02. IEEE, 2002. http://dx.doi.org/10.1109/icassp.2002.5743881.

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Harris, Sarah L., Robert Owen, Enrique Sedano und Daniel Chaver Martinez. „MIPSfpga: Hands-on learning on a commercial soft-core“. In 2016 11th European Workshop on Microelectronics Education (EWME). IEEE, 2016. http://dx.doi.org/10.1109/ewme.2016.7496470.

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Biagiotti, L., C. Melchiorri, P. Tiezzi und G. Vassura. „Modelling and identification of soft pads for robotic hands“. In 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 2005. http://dx.doi.org/10.1109/iros.2005.1545529.

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Li, Chao, und Nancy Pollard. „SoftTouch: A Sensor-Placement Framework for Soft Robotic Hands“. In 2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids). IEEE, 2022. http://dx.doi.org/10.1109/humanoids53995.2022.10000138.

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Seiji Sugiyama, M. Koeda, H. Fujimoto und T. Yoshikawa. „Measurement of grasp position by human hands and grasp criterion for two soft-fingered robot hands“. In 2009 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2009. http://dx.doi.org/10.1109/robot.2009.5152358.

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Berichte der Organisationen zum Thema "Soft hands":

Gammon, P., und S. Alpay. Aquatic soft sediment sampling methods: freeze coring and grab/hand coring. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2011. http://dx.doi.org/10.4095/288040.

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Galili, Naftali, Roger P. Rohrbach, Itzhak Shmulevich, Yoram Fuchs und Giora Zauberman. Non-Destructive Quality Sensing of High-Value Agricultural Commodities Through Response Analysis. United States Department of Agriculture, Oktober 1994. http://dx.doi.org/10.32747/1994.7570549.bard.

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The objectives of this project were to develop nondestructive methods for detection of internal properties and firmness of fruits and vegetables. One method was based on a soft piezoelectric film transducer developed in the Technion, for analysis of fruit response to low-energy excitation. The second method was a dot-matrix piezoelectric transducer of North Carolina State University, developed for contact-pressure analysis of fruit during impact. Two research teams, one in Israel and the other in North Carolina, coordinated their research effort according to the specific objectives of the project, to develop and apply the two complementary methods for quality control of agricultural commodities. In Israel: An improved firmness testing system was developed and tested with tropical fruits. The new system included an instrumented fruit-bed of three flexible piezoelectric sensors and miniature electromagnetic hammers, which served as fruit support and low-energy excitation device, respectively. Resonant frequencies were detected for determination of firmness index. Two new acoustic parameters were developed for evaluation of fruit firmness and maturity: a dumping-ratio and a centeroid of the frequency response. Experiments were performed with avocado and mango fruits. The internal damping ratio, which may indicate fruit ripeness, increased monotonically with time, while resonant frequencies and firmness indices decreased with time. Fruit samples were tested daily by destructive penetration test. A fairy high correlation was found in tropical fruits between the penetration force and the new acoustic parameters; a lower correlation was found between this parameter and the conventional firmness index. Improved table-top firmness testing units, Firmalon, with data-logging system and on-line data analysis capacity have been built. The new device was used for the full-scale experiments in the next two years, ahead of the original program and BARD timetable. Close cooperation was initiated with local industry for development of both off-line and on-line sorting and quality control of more agricultural commodities. Firmalon units were produced and operated in major packaging houses in Israel, Belgium and Washington State, on mango and avocado, apples, pears, tomatoes, melons and some other fruits, to gain field experience with the new method. The accumulated experimental data from all these activities is still analyzed, to improve firmness sorting criteria and shelf-life predicting curves for the different fruits. The test program in commercial CA storage facilities in Washington State included seven apple varieties: Fuji, Braeburn, Gala, Granny Smith, Jonagold, Red Delicious, Golden Delicious, and D'Anjou pear variety. FI master-curves could be developed for the Braeburn, Gala, Granny Smith and Jonagold apples. These fruits showed a steady ripening process during the test period. Yet, more work should be conducted to reduce scattering of the data and to determine the confidence limits of the method. Nearly constant FI in Red Delicious and the fluctuations of FI in the Fuji apples should be re-examined. Three sets of experiment were performed with Flandria tomatoes. Despite the complex structure of the tomatoes, the acoustic method could be used for firmness evaluation and to follow the ripening evolution with time. Close agreement was achieved between the auction expert evaluation and that of the nondestructive acoustic test, where firmness index of 4.0 and more indicated grade-A tomatoes. More work is performed to refine the sorting algorithm and to develop a general ripening scale for automatic grading of tomatoes for the fresh fruit market. Galia melons were tested in Israel, in simulated export conditions. It was concluded that the Firmalon is capable of detecting the ripening of melons nondestructively, and sorted out the defective fruits from the export shipment. The cooperation with local industry resulted in development of automatic on-line prototype of the acoustic sensor, that may be incorporated with the export quality control system for melons. More interesting is the development of the remote firmness sensing method for sealed CA cool-rooms, where most of the full-year fruit yield in stored for off-season consumption. Hundreds of ripening monitor systems have been installed in major fruit storage facilities, and being evaluated now by the consumers. If successful, the new method may cause a major change in long-term fruit storage technology. More uses of the acoustic test method have been considered, for monitoring fruit maturity and harvest time, testing fruit samples or each individual fruit when entering the storage facilities, packaging house and auction, and in the supermarket. This approach may result in a full line of equipment for nondestructive quality control of fruits and vegetables, from the orchard or the greenhouse, through the entire sorting, grading and storage process, up to the consumer table. The developed technology offers a tool to determine the maturity of the fruits nondestructively by monitoring their acoustic response to mechanical impulse on the tree. A special device was built and preliminary tested in mango fruit. More development is needed to develop a portable, hand operated sensing method for this purpose. In North Carolina: Analysis method based on an Auto-Regressive (AR) model was developed for detecting the first resonance of fruit from their response to mechanical impulse. The algorithm included a routine that detects the first resonant frequency from as many sensors as possible. Experiments on Red Delicious apples were performed and their firmness was determined. The AR method allowed the detection of the first resonance. The method could be fast enough to be utilized in a real time sorting machine. Yet, further study is needed to look for improvement of the search algorithm of the methods. An impact contact-pressure measurement system and Neural Network (NN) identification method were developed to investigate the relationships between surface pressure distributions on selected fruits and their respective internal textural qualities. A piezoelectric dot-matrix pressure transducer was developed for the purpose of acquiring time-sampled pressure profiles during impact. The acquired data was transferred into a personal computer and accurate visualization of animated data were presented. Preliminary test with 10 apples has been performed. Measurement were made by the contact-pressure transducer in two different positions. Complementary measurements were made on the same apples by using the Firmalon and Magness Taylor (MT) testers. Three-layer neural network was designed. 2/3 of the contact-pressure data were used as training input data and corresponding MT data as training target data. The remaining data were used as NN checking data. Six samples randomly chosen from the ten measured samples and their corresponding Firmalon values were used as the NN training and target data, respectively. The remaining four samples' data were input to the NN. The NN results consistent with the Firmness Tester values. So, if more training data would be obtained, the output should be more accurate. In addition, the Firmness Tester values do not consistent with MT firmness tester values. The NN method developed in this study appears to be a useful tool to emulate the MT Firmness test results without destroying the apple samples. To get more accurate estimation of MT firmness a much larger training data set is required. When the larger sensitive area of the pressure sensor being developed in this project becomes available, the entire contact 'shape' will provide additional information and the neural network results would be more accurate. It has been shown that the impact information can be utilized in the determination of internal quality factors of fruit. Until now,