Log in

Relevant bibliographies by topics / Deformable Object Manipulation

Academic literature on the topic 'Deformable Object Manipulation'

Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Contents

Journal articles
Dissertations / Theses
Books
Book chapters
Conference papers

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Deformable Object Manipulation.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Deformable Object Manipulation"

1

Hirai, Shinichi. "Deformable Object Manipulation." Journal of the Robotics Society of Japan 16, no. 2 (1998): 136–39. http://dx.doi.org/10.7210/jrsj.16.136.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Ono, Eiichi. "Deformable Object Manipulation. Fabric Manipulation." Journal of the Robotics Society of Japan 16, no. 2 (1998): 149–53. http://dx.doi.org/10.7210/jrsj.16.149.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Hou, Yew Cheong, Khairul Salleh Mohamed Sahari, and Dickson Neoh Tze How. "A review on modeling of flexible deformable object for dexterous robotic manipulation." International Journal of Advanced Robotic Systems 16, no. 3 (May 1, 2019): 172988141984889. http://dx.doi.org/10.1177/1729881419848894.

Full text

Abstract:

In this article, we present a review on the recent advancement in flexible deformable object modeling for dexterous manipulation in robotic system. Flexible deformable object is one of the most research topics in computer graphic, computer vision, and robotic literature. The deformable models are known as the construction of object with material parameters in virtual environment to describe the deformation behavior. Existing modeling techniques and different types of deformable model are described. Various approaches of deformable object modeling have been used in robotic recognition and manipulation in order to reduce the time and cost to obtain more accurate result. In robotic manipulation, object detection, classification, and recognition of deformable objects are always a challenging problem and required as a first step to imbue the robot to able handle these deformable objects. Furthermore, the dexterity of robot control is also another essential key in handling of deformable object which its manipulation strategies need to plan intelligently for each sequence process. We also discuss some deserving direction for further research based on most current contribution.

APA, Harvard, Vancouver, ISO, and other styles

4

Wakamatsu, Hidefumi, and Takahiro Wada. "Deformable Object Manipulation. Modeling of String Objects for Their Manipulation." Journal of the Robotics Society of Japan 16, no. 2 (1998): 145–48. http://dx.doi.org/10.7210/jrsj.16.145.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Fujiura, Tateshi. "Deformable Object Manipulation. Manipulation of Agricultural Crops." Journal of the Robotics Society of Japan 16, no. 2 (1998): 168–71. http://dx.doi.org/10.7210/jrsj.16.168.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Higashimori, Mitsuru, Ixchel Georgina Ramirez Alpizar, and Makoto Kaneko. "Modeling and Handling of Deformable Object by Nonprehensile Dynamic Manipulation." Abstracts of the international conference on advanced mechatronics : toward evolutionary fusion of IT and mechatronics : ICAM 2010.5 (2010): 427–32. http://dx.doi.org/10.1299/jsmeicam.2010.5.427.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Hisada, Toshiaki. "Deformable Object Manipulation. Finite Element Modeling." Journal of the Robotics Society of Japan 16, no. 2 (1998): 140–44. http://dx.doi.org/10.7210/jrsj.16.140.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Salleh, Khairul, Hiroaki Seki, Yoshitsugu Kamiya, and Masatoshi Hikizu. "Tracing Manipulation in Clothes Spreading by Robot Arms." Journal of Robotics and Mechatronics 18, no. 5 (October 20, 2006): 564–71. http://dx.doi.org/10.20965/jrm.2006.p0564.

Full text

Abstract:

Edge tracing is important in manipulating deformable objects to reveal their original shape. In this paper, we propose a unique and improved tracing manipulation for towel spreading, an example of a deformable object using two robot arms with sensors-equipped grippers and a CCD camera. Tracing in this paper context involves tracing the towel’s edge. Robot arm movement is based on feedback from sensors and from images from the CCD camera. Our proposed tracing manipulation ensures that both corners grasped by robot are adjacent and not across, enabling the towel to be successfully spread. Experimental results from spreading rectangular towels with different thickness, stiffness, smoothness, and color using our improved tracing manipulation demonstrated that our proposal is also robust.

APA, Harvard, Vancouver, ISO, and other styles

9

Zaidi, Lazher, Juan Antonio Corrales Ramon, Laurent Sabourin, Belhassen Chedli Bouzgarrou, and Youcef Mezouar. "Grasp Planning Pipeline for Robust Manipulation of 3D Deformable Objects with Industrial Robotic Hand + Arm Systems." Applied Sciences 10, no. 23 (December 6, 2020): 8736. http://dx.doi.org/10.3390/app10238736.

Full text

Abstract:

In the grasping and manipulation of 3D deformable objects by robotic hands, the physical contact constraints between the fingers and the object have to be considered in order to validate the robustness of the task. Nevertheless, previous works rarely establish contact interaction models based on these constraints that enable the precise control of forces and deformations during the grasping process. This paper considers all steps of the grasping process of deformable objects in order to implement a complete grasp planning pipeline by computing the initial contact points (pregrasp strategy), and later, the contact forces and local deformations of the contact regions while the fingers close over the grasped object (grasp strategy). The deformable object behavior is modeled using a nonlinear isotropic mass-spring system, which is able to produce potential deformation. By combining both models (the contact interaction and the object deformation) in a simulation process, a new grasp planning method is proposed in order to guarantee the stability of the 3D grasped deformable object. Experimental grasping experiments of several 3D deformable objects with a Barrett hand (3-fingered) and a 6-DOF industrial robotic arm are executed. Not only will the final stable grasp configuration of the hand + object system be obtained, but an arm + hand approaching strategy (pregrasp) will also be computed.

APA, Harvard, Vancouver, ISO, and other styles

10

A.Ayub, Muhammad, Rabiatul A.Jaafar, Amir Abdul Latif, and . "Tactile Sensor for Manipulation of Deformable Object." International Journal of Engineering & Technology 7, no. 4.27 (November 30, 2018): 101. http://dx.doi.org/10.14419/ijet.v7i4.27.22492.

Full text

Abstract:

The variable physical property of deformable objects, which are very flexible, soft and viscoelastic, causes the design of reliable automated handling system relatively difficult. In fact, most of these objects tend to be handled manually during the handling process. Therefore, a new optical tactile sensor for an intelligent handling of the non-rigid materials is presented in this paper. Mathematical modelling and control algorithm are developed and the tactile sensor is calibrated in this research. Based on the results that have been recorded, the surface characterization with the respect to normal force applied to the object is attained. A gripper handling system is used to accommodate variable physical properties of the deformable materials, which are very flexible, soft and viscoelastic. In addition to that, the gripper needs to handle the materials with the minimum deformation so that less distortion, and higher accuracy of manipulation can be achieved. Efficient and accurate modelling of deformations is crucial for grasping analysis.

APA, Harvard, Vancouver, ISO, and other styles

More sources

Dissertations / Theses on the topic "Deformable Object Manipulation"

1

Boonvisut, Pasu. "Active Exploration of Deformable Object Boundary Constraints and Material Parameters Through Robotic Manipulation Data." Case Western Reserve University School of Graduate Studies / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=case1369078402.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Caporali, Alessio. "Robotic manipulation of cloth-like deformable objects." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019.

Find full text

Abstract:

The manipulation of cloth-like deformable objects represents a challenging problem. Clothes are characterized by having shape, appearance, and other mechanical and visual properties to vary due to previous manipulations or external effects. In this thesis the problem of grasping cloth-like objects is addressed. This dissertation is part of a project where a mobile robot is involved in the loading and unloading of clothes for the end-of-line tests of washing machines. In particular, the thesis focuses on estimating target poses that would result in reliable grasping operations for a robotic arm. The processing of input pointclouds coming from a 3D camera is performed in order to develop strategies and algorithms for grasping clothes both from a bin randomly placed nearby the robot but also for clothes placed inside a drum or across its opening door. The structure of the developed algorithms is organized into three layers. In addition, the problem of avoiding collisions is analyzed, in particular inside the drum where the plastic paddles are identified with this purpose. The PointCloud library along with the Eigen library are utilized to perform the processing of the pointclouds. Chapter 2 focuses on the grasping of clothes from an external bin while Chapter 3 describes how the paddles in the washing machine are localized. Chapter 4 provides solutions for the grasping of clothes placed inside the drum. Chapter 5 addresses the problem of detecting cloths along the drum opening. Chapter 6 shows a possible application of the algorithms described in Chapter 2 and 5 on a real robot employing tools like ROS, Moveit! and a behavior three as task manger.

APA, Harvard, Vancouver, ISO, and other styles

3

Zhu, Jihong. "Vision-based robotic manipulation of deformable linear objects." Thesis, Montpellier, 2020. http://www.theses.fr/2020MONTS008.

Full text

Abstract:

En robotique, la manipulation d'objets déformables reçoit moins d'attention que celle d'objets rigides. Pourtant, de nombreux objets dans la vie réelle sont déformables. La recherche sur la manipulation d'objets déformables est indispensable pour doter les robots d'une dextérité de manipulation totale. La difficulté majeure de ce problème est que déformation de l'objet a un espace de configurations de dimensions infinie, tandis que les entrées du robots sont limitées. Dans le cadre de VERSATILE, un projet H2020 axé sur l'automatisation industrielle à l'aide de robots, nous avons axé nos recherches sur la manipulation d'objets déformables linéaires (câbles) par retour visuel.Une caractéristique de la manipulation des objets déformables est que la forme de l'objet change pendant la manipulation. Par conséquent, un problème important consiste à contrôler la forme de l'objet pendant la manipulation. Nous avons abordé le problème du contrôle de forme en exploitant le retour visuel.Dans un premier temps, nous avons représenté la forme de l'objet avec une série de Fourier. Nous estimons et mettons à jour la matrice d'interaction en ligne, puis nous concevons le contrôleur pour contrôler la forme.Ensuite, au lieu d'utiliser une caractéristique définie par l'humain pour le paramétrage, nous avons laissé le robot apprendre automatiquement les vecteurs de caractéristiques à partir des données visuelles. Nous proposons une méthode qui permet au robot de générer simultanément - et à partir des mêmes données - un vecteur de caractéristiques ainsi que la matrice d'interaction. Cette méthode nécessite un minimum de données pour l'initialisation. L'apprentissage et le contrôle peuvent être effectués en ligne de manière adaptative. Nous pouvons appliquer la même méthode à la manipulation d'objets rigides, directement et sans modification.Ces deux travaux ne requièrent aucune calibration de la caméra et ont été validés avec des expérimentations de robotique réelle.Un autre domaine d'importance dans la manipulation d'objets déformables est l'utilisation de contacts externes pour contrôler la forme de l'objet. Les contacts externes peuvent et doivent être utilisés pour la manipulation d'objets déformables. Nous considérons un scénario fréquent dans l'industrie - l'acheminement de câbles avec des contacts externes comme processus à automatiser avec notre robot. Nous proposons un algorithme de planification qui permet au robot d'utiliser des contacts pour déformer le câble et pour obtenir la configuration souhaitée. Des expériences robotiques réelles avec différents scénarios de placement de contacts permettent de valider nos algorithmes
In robotics, the area of deformable object manipulation receives far less attention than that of rigid object manipulation. However, many objects in real life are deformable. Research on deformable object manipulation is indispensable to equip robots with full manipulation dexterity. Deformable linear object (DLO) is one type of deformable objects that commonly presents in the industry and households, for instance, electrical cables for power transfer, USB cables for data transfer, or ropes for dragging and lifting equipment. In the context of H2020 VERSATILE, a project focusing on industrial automation using robots, we focus our research on DLO manipulation via visual feedback.One characteristic of deformable object manipulation is that the object shape changes while being manipulated. Consequently, a research direction is to control the shape of the object during manipulation. We tackle the shape control problem by using vision. Initially, we parameterize the shape with Fourier series, estimate and update the interaction matrix online, and finally control the DLO shape.In the subsequent research, instead of using human-defined features for parameterization, we let the robot automatically learn feature vectors from visual data. We propose a method that allows the robot to simultaneously generate a feature vector and the interaction matrix from the same data. Our approach requires minimum data for initialization. Learning and control can be done online in an adaptive manner. We can also apply the method to rigid object manipulation directly without modification.Neither of the two frameworks requires camera calibration, and both are verified with simulation and real robotic experiments.Another area of importance in deformable object manipulation is the utilization of external contacts. The object deformation is defined in a configuration space of infinite dimension. Nonetheless, the inputs from robots are limited. External contacts can and should be used for manipulating deformable objects. We take a practical scenario in the industry -- cable routing with external contacts as the process to automate with our robot. We propose a planning algorithm that allows the robot to use contacts for shaping the cable and achieving the desired cable configuration. Real robotic experiments with different contact placement scenarios further validate the algorithms

APA, Harvard, Vancouver, ISO, and other styles

4

Sanchez, Loza Jose Manuel. "Shape sensing of deformable objects for robot manipulation." Thesis, Université Clermont Auvergne‎ (2017-2020), 2019. http://www.theses.fr/2019CLFAC012/document.

Full text

Abstract:

Les objets déformables sont omniprésents dans notre vie quotidienne. Chaque jour, nous manipulons des vêtements dans des configurations innombrables pour nous habiller, nouons les lacets de nos chaussures, cueillons des fruits et des légumes sans les endommager pour notre consommation et plions les reçus dans nos portefeuilles. Toutes ces tâches impliquent de manipuler des objets déformables et peuvent être exécutées sans problème par une personne. Toutefois, les robots n'ont pas encore atteint le même niveau de dextérité. Contrairement aux objets rigides, que les robots sont maintenant capables de manipuler avec des performances proches de celles des humains; les objets déformables doivent être contrôlés non seulement pour les positionner, mais aussi pour définir leur forme. Cette contrainte supplémentaire, relative au contrôle de la forme d’un objet, rend les techniques utilisées pour les objets rigides inapplicables aux objets déformables. En outre, le comportement des objets déformables diffère largement entre eux, par exemple: la forme d’un câble et des vêtements est considérablement affectée par la gravité, alors que celle-ci n’affecte pas la configuration d’autres objets déformables tels que des produits alimentaires. Ainsi, différentes approches ont été proposées pour des classes spécifiques d’objets déformables.Dans cette thèse, nous cherchons à remédier à ces lacunes en proposant une approche modulaire pour détecter la forme d'un objet pendant qu'il est manipulé par un robot. La modularité de cette approche s’inspire d’un paradigme de programmation qui s’applique de plus en plus au développement de logiciels en robotique et vise à apporter des solutions plus générales en séparant les fonctionnalités en composants. Ces composants peuvent ensuite être interchangés en fonction de la tâche ou de l'objet concerné. Cette stratégie est un moyen modulaire de suivre la forme d'objets déformables.Pour valider la stratégie proposée, nous avons implémenté trois applications différentes. Deux applications portaient exclusivement sur l'estimation de la déformation de l'objet à l'aide de données tactiles ou de données issues d’un capteur d’effort. La troisième application consistait à contrôler la déformation d'un objet. Une évaluation de la stratégie proposée, réalisée sur un ensemble d'objets élastiques pour les trois applications, montre des résultats prometteurs pour une approche qui n'utilise pas d'informations visuelles et qui pourrait donc être améliorée de manière significative par l'ajout de cette modalité
Deformable objects are ubiquitous in our daily lives. On a given day, we manipulate clothes into uncountable configurations to dress ourselves, tie the shoelaces on our shoes, pick up fruits and vegetables without damaging them for our consumption and fold receipts into our wallets. All these tasks involve manipulating deformable objects and can be performed by an able person without any trouble, however robots have yet to reach the same level of dexterity. Unlike rigid objects, where robots are now capable of handling objects with close to human performance in some tasks; deformable objects must be controlled not only to account for their pose but also their shape. This extra constraint, to control an object's shape, renders techniques used for rigid objects mainly inapplicable to deformable objects. Furthermore, the behavior of deformable objects widely differs among them, e.g. the shape of a cable and clothes are significantly affected by gravity while it might not affect the configuration of other deformable objects such as food products. Thus, different approaches have been designed for specific classes of deformable objects.In this thesis we seek to address these shortcomings by proposing a modular approach to sense the shape of an object while it is manipulated by a robot. The modularity of the approach is inspired by a programming paradigm that has been increasingly been applied to software development in robotics and aims to achieve more general solutions by separating functionalities into components. These components can then be interchanged based on the specific task or object at hand. This provides a modular way to sense the shape of deformable objects.To validate the proposed pipeline, we implemented three different applications. Two applications focused exclusively on estimating the object's deformation using either tactile or force data, and the third application consisted in controlling the deformation of an object. An evaluation of the pipeline, performed on a set of elastic objects for all three applications, shows promising results for an approach that makes no use of visual information and hence, it could greatly be improved by the addition of this modality

APA, Harvard, Vancouver, ISO, and other styles

5

Wang, Zhifeng. "Robotic Manipulation of Deformable Linear Objects: Modelling and Simulation." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020.

Find full text

Abstract:

With the development of materials science, deformable material objects are used in more andmore fields. Handling of deformable soft objects can be found in many industrial fields includingfood industry and recycle industry. But deformable objects are different from rigid objects. Thereis still room for development of material control, in which the use of computers to simulate controlplays an important role. In this thesis, a physical model of the cable is established based ongeometrically exact dynamic splines, and the simulink of matlab is used to develop the model ofthe cable to establish a control system. Under the action of this control system, the cable can reacha designated position and form the desired shape through a series of operations from the defaultposition and the straight starting state. In this process, the cable will contact the establishedobstacle model and will be affected by the interaction force provided by the obstacle model.At theend of the thesis, the simulation results are analyzed.

APA, Harvard, Vancouver, ISO, and other styles

6

Rowlands, Stephen. "Robotic Control for the Manipulation of 3D Deformable Objects." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/42554.

Full text

Abstract:

Robotic grasping and manipulation of three-dimensional deformable objects is a complex task that currently does not have robust and flexible solutions. Deformable objects include a wide variety of elastic and inelastic objects that change size and shape during manipulation. The development of adaptable methods for grasping and autonomously controlling the shape of three-dimensional deformable objects will benefit many commercial applications, including shaping parts for assembly in manufacturing, manipulating food for packaging and controlling tissues during robotic surgery. Controlling a deformable object to a desired shape requires first choosing contact points on the object's surface. Next, the robotic hand is positioned in the correct position and orientation to grasp and deform the object. After deformation, the object is assessed to evaluate the quality of the shape control procedure. In many cases, this process is completed without knowing the object's properties or behaviour before deformation. This work proposes and implements the framework for a robotic arm and hand system to control the shape of a previously unseen deformable object autonomously. Significant original contributions are made in developing an original algorithm to plan contact points on a three-dimensional object for grasping and shape control. This research uses a novel object representation to reduce the dimensionality of the deformable object manipulation problem. A path planning algorithm guides the robot arm to the optimal valid grasp pose to deform the object at the determined contact points. Additional contributions include developing a multi-view assessment strategy to determine the quality of the deformation towards the desired shape. The system completes the objectives using depth and colour images captured from a single point of view to locate and identify a previously unseen three-dimensional object within a robotic workspace. After estimating the unknown object's geometry, initial grasp contact points are planned to control the object to the desired shape. The grasp points are used to plan and execute a collision-free trajectory for the robot manipulator to place the robotic hand in the optimal position and orientation to grasp and deform the object. After the deformation is complete, the object is moved to a variety of assessment positions to determine the success of the shape control procedure. The system is validated experimentally on a variety of deformable three-dimensional objects.

APA, Harvard, Vancouver, ISO, and other styles

7

Valencia, Angel. "3D Shape Deformation Measurement and Dynamic Representation for Non-Rigid Objects under Manipulation." Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/40718.

Full text

Abstract:

Dexterous robotic manipulation of non-rigid objects is a challenging problem but necessary to explore as robots are increasingly interacting with more complex environments in which such objects are frequently present. In particular, common manipulation tasks such as molding clay to a target shape or picking fruits and vegetables for use in the kitchen, require a high-level understanding of the scene and objects. Commonly, the behavior of non-rigid objects is described by a model. Although, well-established modeling techniques are difficult to apply in robotic tasks since objects and their properties are unknown in such unstructured environments. This work proposes a sensing and modeling framework to measure the 3D shape deformation of non-rigid objects. Unlike traditional methods, this framework explores data-driven learning techniques focused on shape representation and deformation dynamics prediction using a graph-based approach. The proposal is validated experimentally, analyzing the performance of the representation model to capture the current state of the non-rigid object shape. In addition, the performance of the prediction model is analyzed in terms of its ability to produce future states of the non-rigid object shape due to the manipulation actions of the robotic system. The results suggest that the representation model is able to produce graphs that closely capture the deformation behavior of the non-rigid object. Whereas, the prediction model produces visually plausible graphs when short-term predictions are required.

APA, Harvard, Vancouver, ISO, and other styles

8

Shah, Ankit Jayesh. "Planning for manipulation of interlinked deformable linear objects with applications to aircraft assembly." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/105640.

Full text

Abstract:

Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2016.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 83-87).
Manipulation of deformable linear objects (DLO) has potential applications in the fields of aerospace and automotive assembly. In this paper, we introduce a problem formulation for attaching a set of interlinked DLOs to a support structure using a set of clamping points. The formulation describes the manipulation planning problem in terms of known clamping locations; pre-determined ideal clamping locations on the cables, called "reference points", and a set of finite gripping points on the DLOs. We also present a prototype algorithm that generates a solution in terms of primitive manipulation actions. The algorithm guarantees that no interlink constraints are violated at any stage of manipulation. We incorporate gravity in the computation of a DLO shape and propose a property linking geometrically similar cable shapes across the space of cable length and stiffness. This property allows for the computation of solutions for unit length and scaling of these solutions to appropriate length, potentially resulting in faster shape computation.
by Ankit Jayesh Shah.
S.M.

APA, Harvard, Vancouver, ISO, and other styles

9

Phillips-Grafflin, Calder. "Enabling Motion Planning and Execution for Tasks Involving Deformation and Uncertainty." Digital WPI, 2017. https://digitalcommons.wpi.edu/etd-dissertations/307.

Full text

Abstract:

"A number of outstanding problems in robotic motion and manipulation involve tasks where degrees of freedom (DoF), be they part of the robot, an object being manipulated, or the surrounding environment, cannot be accurately controlled by the actuators of the robot alone. Rather, they are also controlled by physical properties or interactions - contact, robot dynamics, actuator behavior - that are influenced by the actuators of the robot. In particular, we focus on two important areas of poorly controlled robotic manipulation: motion planning for deformable objects and in deformable environments; and manipulation with uncertainty. Many everyday tasks we wish robots to perform, such as cooking and cleaning, require the robot to manipulate deformable objects. The limitations of real robotic actuators and sensors result in uncertainty that we must address to reliably perform fine manipulation. Notably, both areas share a common principle: contact, which is usually prohibited in motion planners, is not only sometimes unavoidable, but often necessary to accurately complete the task at hand. We make four contributions that enable robot manipulation in these poorly controlled tasks: First, an efficient discretized representation of elastic deformable objects and cost function that assess a ``cost of deformation' for a specific configuration of a deformable object that enables deformable object manipulation tasks to be performed without physical simulation. Second, a method using active learning and inverse-optimal control to build these discretized representations from expert demonstrations. Third, a motion planner and policy-based execution approach to manipulation with uncertainty which incorporates contact with the environment and compliance of the robot to generate motion policies which are then adapted during execution to reflect actual robot behavior. Fourth, work towards the development of an efficient path quality metric for paths executed with actuation uncertainty that can be used inside a motion planner or trajectory optimizer."

APA, Harvard, Vancouver, ISO, and other styles

10

Chandra, Rohit. "Application of Dual Quaternion for Bimanual Robotic Tasks." Thesis, Université Clermont Auvergne‎ (2017-2020), 2019. http://www.theses.fr/2019CLFAC042.

Full text

Abstract:

L'approche classique pour le contrôle coopératif dans l’espace de travail d’un manipulateur bi-bras a été revisitée. En particulier, une nouvelle approche pour la formulation symétrique de la coordination bi-bras à l'aide du concept "virtual sticks" a été proposée à l'aide d'un torseur cinématique en utilisant des quaternions duaux. Le contrôle couplé dans l'espace de travail coopératif qui est proposé, i.e. le contrôle simultané, en position et en orientation, des points de consigne de l'espace de travail relatif et absolu a été comparé à un contrôleur proportionnel découplé traitant séparément les erreurs de position et d'orientation. Le contrôleur couplé a démontré un meilleur suivi de la pose et de l'orientation en termes de précision et de stabilité comparé au contrôleur découplé pour les tâches exigeant un fonctionnement plus rapide dans l'espace de travail relatif des manipulateurs bi-bras.L'approche de modélisation et de contrôle de l'espace de travail d’une tâche coopérative, en exploitant les torseurs cinématiques et des quaternions duaux, a été étendue à la modélisation de la coopération des doigts d'une main robotique anthropomorphique. De plus, le couplage des articulations des doigts sous-actionnés de la main robotique a été représenté à l’aide de la "jacobienne couplée" du doigt. La "jacobienne couplée" du doigt robotique a été utilisée pour le contrôle cinématique inverse, tout en lui permettant une intégration facile avec un bras robotique.L'idée d'un traitement couplé des variables en position et en orientation a été capitalisée en utilisant la conception d'une trajectoire de second ordre utilisant des quaternions duaux. Le contrôleur de trajectoire ainsi conçu est capable de suivre les points de consigne en pose en vitesse et en accélération, de l'effecteur en utilisant le modèle dynamique inverse du robot. Le contrôleur couplé en taux d’accélération résolue ("resolved rate acceleration") s'est avéré capable d'un contrôle de trajectoire plus précis, particulièrement en termes d'erreurs liées à l'orientation, que le contrôleur découplé classique qui traitait séparément les points de consigne en position et en orientation et ignorait l'effet de la rotation sur le mouvement de translation. De plus, cela a également permis de réduire les oscillations de la commande du couple des articulations lorsque le contrôleur a été implémenté pour le contrôle de l'un des bras du robot bi-bras Baxter.Enfin, un cadre complet pour la coordination des systèmes robotiques bi-bras a été proposé avec l'ajout d'un planificateur de tâches coopératives. La simplicité du torseur cinématique a également été exploitée pour la génération de trajectoires généralisées du second ordre pour des tâches nécessitant un mouvement simplifié, comme la translation, la rotation et la torsion autour d'un axe hélicoïdale arbitraire donné dans un repère connu. La méthode de génération de trajectoires a été étendue pour représenter les contraintes liées aux tâches impliquant un contact entre les objets en utilisant le concept de mécanisme virtuel
The classical approach for dual-arm cooperative task space control was revisited and the symmetric formulation of dual arm coordination using virtual sticks was implemented using screw-based kinematics with dual quaternion representation. The proposed coupled control of cooperative task space, i.e. simultaneous control of both position and orientation setpoints of relative and absolute task space was compared against the performance of a proportional decoupled controller treating position and orientation error separately. The coupled controller demonstrated better tracking of pose and orientation in terms of accuracy and stability compared to the decoupled controller for tasks requiring faster operation in the relative task space of dual-arm manipulators.The cooperative task space modelling and control approach using screw-based kinematics and dual quaternions were extended for the cooperation modelling of the fingers of an anthropomorphic robotic hand. Additionally, the coupling of joints in the underactuated fingers of the robotic hand was represented with a coupled finger Jacobian. The coupled Jacobian of the robotic finger was used for inverse kinematic control, while allowing easy integration with a robotic arm.The idea of coupled treatment of position and orientation variables was capitalized further with the design of a second-order trajectory tracker using dual quaternions. The trajectory controller hence designed was capable of tracking pose, velocity and acceleration setpoints for the end-effector using inverse dynamic model of the robot. The coupled resolved rate acceleration controller was found to be capable of tighter trajectory control, specially for error terms related to orientation, compared to the conventional decoupled controller that treated the position and orientation setpoints separately and ignored the inherent effect of rotation on translational motion. Additionally, it also led to lower oscillations in the joint torque command when implemented for the control of one of the arms of Baxter dual-arm robot.Finally, a complete framework for the coordination of bi-arm robotic systems was proposed with the addition of a cooperative task planner. The simplicity of screw theory was exploited additionally for parametrized generation of generalized second order trajectories for tasks requiring simplified motion, like translation, rotation and screw motion around an arbitrary 6D screw-axis given in a known reference frame. The trajectory generation method was extended to represent the constraints related to tasks involving contact between objects using the concept of virtual mechanism

APA, Harvard, Vancouver, ISO, and other styles

Books on the topic "Deformable Object Manipulation"

1

Henrich, Dominik. Robot Manipulation of Deformable Objects. London: Springer London, 2000.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

2

Henrich, Dominik, and Heinz Wörn, eds. Robot Manipulation of Deformable Objects. London: Springer London, 2000. http://dx.doi.org/10.1007/978-1-4471-0749-1.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

(Editor), Dominik Henrich, and Heinz Worn (Editor), eds. Robot Manipulation of Deformable Objects (Advanced Manufacturing). Springer, 2000.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

4

Siciliano, Bruno, and Fabio Ruggiero. Robot Dynamic Manipulation: Perception of Deformable Objects and Nonprehensile Manipulation Control. Springer International Publishing AG, 2022.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

Book chapters on the topic "Deformable Object Manipulation"

1

Hirota, Koichi, Yusuke Ujitoko, Kazuya Kiriyama, and Kazuyoshi Tagawa. "Object Manipulation by Deformable Hand." In Lecture Notes in Electrical Engineering, 145–48. Tokyo: Springer Japan, 2015. http://dx.doi.org/10.1007/978-4-431-55690-9_27.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Tanner, H. G., and K. J. Kyriakopoulos. "A Manipulated Deformable Object as an Underactuated Mechanical System." In Robot Manipulation of Deformable Objects, 175–96. London: Springer London, 2000. http://dx.doi.org/10.1007/978-1-4471-0749-1_11.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

McConachie, Dale, and Dmitry Berenson. "Bandit-Based Model Selection for Deformable Object Manipulation." In Springer Proceedings in Advanced Robotics, 704–19. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43089-4_45.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

McConachie, Dale, Mengyao Ruan, and Dmitry Berenson. "Interleaving Planning and Control for Deformable Object Manipulation." In Springer Proceedings in Advanced Robotics, 1019–36. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-28619-4_68.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Ruggiero, Fabio, Jung-Tae Kim, Alejandro Gutierrez-Giles, Aykut C. Satici, Alejandro Donaire, Jonathan Cacace, Luca Rosario Buonocore, Giuseppe Andrea Fontanelli, Vincenzo Lippiello, and Bruno Siciliano. "Nonprehensile Manipulation Control and Task Planning for Deformable Object Manipulation: Results from the RoDyMan Project." In Informatics in Control, Automation and Robotics, 76–100. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31993-9_4.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Wörn, H. "Motivation." In Robot Manipulation of Deformable Objects, 3–5. London: Springer London, 2000. http://dx.doi.org/10.1007/978-1-4471-0749-1_1.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Yoshida, H., and K. Kosuge. "Manipulation of Sheet Metal by Dual Manipulators." In Robot Manipulation of Deformable Objects, 161–74. London: Springer London, 2000. http://dx.doi.org/10.1007/978-1-4471-0749-1_10.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Rizzi, C., M. Bordegoni, and G. Frugoli. "Simulation of Non-Rigid Materials Handling." In Robot Manipulation of Deformable Objects, 199–210. London: Springer London, 2000. http://dx.doi.org/10.1007/978-1-4471-0749-1_12.

Full text

APA, Harvard, Vancouver, ISO, and other styles

9

Buckingham, R., and A. Graham. "Robotics for Deheading White Fish." In Robot Manipulation of Deformable Objects, 211–35. London: Springer London, 2000. http://dx.doi.org/10.1007/978-1-4471-0749-1_13.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Maruyama, Y. "Application of LLW Robots to Distribution Lines." In Robot Manipulation of Deformable Objects, 237–53. London: Springer London, 2000. http://dx.doi.org/10.1007/978-1-4471-0749-1_14.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Deformable Object Manipulation"

1

Tagawa, Kazuyoshi, Koichi Hirota, and Michitaka Hirose. "Manipulation of dynamically deformable object." In 2008 Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems. IEEE, 2008. http://dx.doi.org/10.1109/haptics.2008.4479966.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

"CyberPhysical Systems for Deformable Object Manipulation." In 2021 4th IEEE International Conference on Industrial Cyber-Physical Systems (ICPS). IEEE, 2021. http://dx.doi.org/10.1109/icps49255.2021.9468159.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Hou, Yew Cheong, Khairul Salleh Mohamed Sahari, and Dickson Neoh Tze How. "Modeling of flexible deformable object for robotic manipulation." In 2016 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS). IEEE, 2016. http://dx.doi.org/10.1109/iris.2016.8066072.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Salleh, Khairul, Hiroaki Seki, Yoshitsugu Kamiya, and Masatoshi Hikizu. "Deformable Object Manipulation - Study on Passive Tracing by Robot." In 2007 5th Student Conference on Research and Development. IEEE, 2007. http://dx.doi.org/10.1109/scored.2007.4451375.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Khalil, F. F., P. Payeur, and A. M. Cretu. "Integrated Multisensory Robotic Hand System for Deformable Object Manipulation." In IASTED Technology Conferences 2010. Calgary,AB,Canada: ACTAPRESS, 2010. http://dx.doi.org/10.2316/p.2010.706-063.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Marchetti, Giovanni Luca, Marco Moletta, Gustaf Tegner, Peiyang Shi, Anastasiia Varava, Alexander Kravchenko, and Danica Kragic. "Learning Coarsened Dynamic Graph Representations for Deformable Object Manipulation." In 2021 20th International Conference on Advanced Robotics (ICAR). IEEE, 2021. http://dx.doi.org/10.1109/icar53236.2021.9659451.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Laezza, Rita, Robert Gieselmann, Florian T. Pokorny, and Yiannis Karayiannidis. "ReForm: A Robot Learning Sandbox for Deformable Linear Object Manipulation." In 2021 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2021. http://dx.doi.org/10.1109/icra48506.2021.9561766.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Han, Haifeng, Gavin Paul, and Takamitsu Matsubara. "Model-based reinforcement learning approach for deformable linear object manipulation." In 2017 13th IEEE Conference on Automation Science and Engineering (CASE 2017). IEEE, 2017. http://dx.doi.org/10.1109/coase.2017.8256194.

Full text

APA, Harvard, Vancouver, ISO, and other styles

9

Fanson, Richard, and Alexandru Patriciu. "Model based deformable object manipulation using linear robust output regulation." In 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010). IEEE, 2010. http://dx.doi.org/10.1109/iros.2010.5650163.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Shen, Bokui, Zhenyu Jiang, Christopher Choy, Silvio Savarese, Leonidas J. Guibas, Anima Anandkumar, and Yuke Zhu. "ACID: Action-Conditional Implicit Visual Dynamics for Deformable Object Manipulation." In Robotics: Science and Systems 2022. Robotics: Science and Systems Foundation, 2022. http://dx.doi.org/10.15607/rss.2022.xviii.001.

Full text

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!