Academic literature on the topic 'Deformable Object Manipulation'
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Journal articles on the topic "Deformable Object Manipulation"
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 textOno, 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 textHou, 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 textWakamatsu, 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 textFujiura, 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 textHigashimori, 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 textHisada, 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 textSalleh, 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 textZaidi, 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 textA.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 textDissertations / Theses on the topic "Deformable Object Manipulation"
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 textCaporali, Alessio. "Robotic manipulation of cloth-like deformable objects." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019.
Find full textZhu, Jihong. "Vision-based robotic manipulation of deformable linear objects." Thesis, Montpellier, 2020. http://www.theses.fr/2020MONTS008.
Full textIn 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
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 textDeformable 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
Wang, Zhifeng. "Robotic Manipulation of Deformable Linear Objects: Modelling and Simulation." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020.
Find full textRowlands, 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 textValencia, 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 textShah, 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 textCataloged 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.
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 textChandra, Rohit. "Application of Dual Quaternion for Bimanual Robotic Tasks." Thesis, Université Clermont Auvergne (2017-2020), 2019. http://www.theses.fr/2019CLFAC042.
Full textThe 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
Books on the topic "Deformable Object Manipulation"
Henrich, Dominik. Robot Manipulation of Deformable Objects. London: Springer London, 2000.
Find full textHenrich, 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(Editor), Dominik Henrich, and Heinz Worn (Editor), eds. Robot Manipulation of Deformable Objects (Advanced Manufacturing). Springer, 2000.
Find full textSiciliano, Bruno, and Fabio Ruggiero. Robot Dynamic Manipulation: Perception of Deformable Objects and Nonprehensile Manipulation Control. Springer International Publishing AG, 2022.
Find full textBook chapters on the topic "Deformable Object Manipulation"
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 textTanner, 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 textMcConachie, 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 textMcConachie, 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 textRuggiero, 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 textWörn, 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 textYoshida, 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 textRizzi, 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 textBuckingham, 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 textMaruyama, 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 textConference papers on the topic "Deformable Object Manipulation"
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"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 textHou, 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 textSalleh, 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 textKhalil, 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 textMarchetti, 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 textLaezza, 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 textHan, 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 textFanson, 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 textShen, 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.
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