Data Based Models For Deformable Objects
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Data Based Models For Deformable Objects
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Author : Philip Fong
language : en
Publisher:
Release Date : 2007
Data Based Models For Deformable Objects written by Philip Fong and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with categories.
Data Driven Robotic Manipulation Of Deformable Objects Using Tactile Feedback
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Author : Yi Zheng
language : en
Publisher:
Release Date : 2023
Data Driven Robotic Manipulation Of Deformable Objects Using Tactile Feedback written by Yi Zheng and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
Perceiving and manipulating deformable objects with the sense of touch are essential skills in everyday life. However, it remains difficult for robots to autonomously manipulate deformable objects using tactile sensing because of numerous perception, modeling, planning, and control challenges. We believe this is partially due to two fundamental challenges: (1) Establishing a physics-based model describing physical interactions between deformable tactile sensors and deformable objects is difficult; (2) Modern tactile sensors provide high-dimensional data, which is beneficial for perception but impedes the development of practical planning and control strategies. To address these challenges, we developed systematic frameworks for the tactile-driven manipulation of deformable objects that integrates state-of-the-art tactile sensing with well-established tools used by other robotics communities. In Study \#1, we showed how a robot can learn to manipulate a deformable, thin-shell object via tactile sensor feedback using model-free reinforcement learning methods. A page flipping task was learned on a real robot using a two-stage approach. First, we learned nominal page flipping trajectories by constructing a reward function that quantifies functional task performance from the perspective of tactile sensing. Second, we learned adapted trajectories using tactile-driven perceptual coupling, with an intuitive assumption that, while the functional page flipping trajectories for different task contexts (page sizes) might differ, similar tactile sensing feedback should be expected. In Study \#2, we showed how a robot can use tactile sensor feedback to control the pose and tension of a deformable linear object (elastic cable). For a cable manipulation task, low-dimensional latent space features were extracted from high-dimensional raw tactile sensor data using unsupervised learning methods, and a dynamics model was constructed in the latent space using supervised learning methods. The dynamics model was integrated with an optimization-based, model predictive controller for end-to-end, tactile-driven motion planning and control on a real robot. In summary, we developed frameworks for the tactile-driven manipulation of deformable objects that either circumvents sensor modeling difficulties or constructs a dynamics model directly from tactile feedback and uses the model for planning and control. This work provides a foundation for the further development of systematic frameworks that can address complex, tactile-driven manipulation problems.
Experimental Data Acquisition And Modeling Of Three Dimensional Deformable Objects Using Neural Networks
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Author : Ana-Maria Cretu
language : en
Publisher:
Release Date : 2009
Experimental Data Acquisition And Modeling Of Three Dimensional Deformable Objects Using Neural Networks written by Ana-Maria Cretu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.
Nowadays there are many technologies and design tools available to accurately obtain and model the geometric shape and the color of objects. However, these methods are not able to provide any information about the elasticity of the objects. This thesis presents a general-purpose scheme for measuring, constructing and representing geometric and elastic behavior of deformable objects without a priori knowledge on the shape and the material that the objects under study are made of. The proposed solution is based on an advantageous combination of neural network architectures and an original force-deformation measurement procedure. An innovative non-uniform selective data acquisition algorithm based on self-organizing neural architectures (namely neural gas and growing neural gas) is developed to selectively and iteratively identify regions of interest and guide the acquisition of data only on those points that are relevant for both the geometric model and the mapping of the elastic behavior, starting from a sparse point-cloud of an object. Multi-resolution object models are obtained using the initial sparse model or the (growing or) neural gas map if a more compressed model is desired, and augmenting it with the higher resolution measurements selectively collected over the regions of interest. A feedforward neural network is then employed to capture the complex relationship between an applied force, its magnitude, its angle of application and its point of interaction, the object pose and the deformation stage of the object on one side, and the object surface deformation for each region with similar geometric and elastic behavior on the other side. The proposed framework works directly from raw range data and obtains compact point-based models. It can deal with different types of materials, distinguishes between the different stages of deformation of an object and models homogeneous and non-homogeneous objects as well. It also offers the desired degree of control to the user.
Physics Based Deformable Models
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Author : Dimitris N. Metaxas
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Physics Based Deformable Models written by Dimitris N. Metaxas and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Science categories.
Physics-Based Deformable Models presents a systematic physics-based framework for modeling rigid, articulated, and deformable objects, their interactions with the physical world, and the estimate of their shape and motion from visual data. This book presents a large variety of methods and associated experiments in computer vision, graphics and medical imaging that help the reader better to understand the presented material. In addition, special emphasis has been given to the development of techniques with interactive or close to real-time performance. Physics-Based Deformable Models is suitable as a secondary text for graduate level courses in Computer Graphics, Computational Physics, Computer Vision, Medical Imaging, and Biomedical Engineering. In addition, this book is appropriate as a reference for researchers and practitioners in the above-mentioned fields.
Computer Vision Based Material Property Extraction And Data Driven Deformable Object Modeling
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Author : Steven C. Wilber
language : en
Publisher:
Release Date : 2012
Computer Vision Based Material Property Extraction And Data Driven Deformable Object Modeling written by Steven C. Wilber and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Computer animation categories.
Articulated Motion And Deformable Objects
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Author : Francisco José Perales
language : en
Publisher: Springer
Release Date : 2014-06-25
Articulated Motion And Deformable Objects written by Francisco José Perales and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-25 with Computers categories.
This book constitutes the refereed proceedings of the 8th International Conference on Articulated Motion and Deformable Objects, AMDO 2014, held in Palma de Mallorca, Spain, in July 2014. The 18 papers presented were carefully reviewed and selected from 37 submissions. The conference dealt with the following topics: geometric and physical deformable models; motion analysis; articulated models and animation; modeling and visualization of deformable models; deformable model applications; motion analysis applications; single or multiple human motion analysis and synthesis; face modeling, tracking, recovering and recognition models; virtual and augmented reality; haptics devices; biometric techniques.
Capturing And Modeling Of Deformable Objects
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Author :
language : en
Publisher:
Release Date : 2005
Capturing And Modeling Of Deformable Objects written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with categories.
Modeling the behavior of deformable virtual objects has important applications in computer graphics. There are two prevalent approaches for modeling deformable objects, an active one by deforming existing virtual models and a passive one by capturing the geometry and motion of real objects. This thesis explores the problem of modeling and acquisition of objects undergoing deformations, and proposes a set of practical deformation and capturing tools. The first contribution is a new approach to model deformation that incorporates non-uniform materials into the geometric deformation framework. This technique provides a simple and intuitive method to control the deformation using material properties that can be specified by the user with an intuitive interface or can be learned from a sequence of sample deformations facilitating realistic looking results. Some deformable objects such as garments exhibit a complex behavior under motion and thus are difficult to model or simulate, making them suitable target for capture methods. Methods for capturing garments usually use special markers printed on the fabric to establish temporally coherent correspondences between frames. Unfortunately, this approach is tedious and prevents the capture of interesting, off-the-shelf fabrics. A marker-free approach to capturing garment motion that avoids these problems is presented in chapter three. The method establishes temporally coherent parameterizations between incomplete geometries that are extracted at each time step using a multiview stereo algorithm, and the missing geometry is filled in using a template. Garment motion is characterized by dynamic high-frequency folds. However, these folds tend to be shallow, making them difficult to capture. A new method for reintroducing folds into the sequence using data-driven dynamic wrinkling is presented in chapter four. The method first estimates the folds in the video footage and then wrinkle the surface using space-time deformation. The.
Heterogeneous Deformable Object Modeling For Medical Surgical Simulation And Collaborative Product Development With Haptic Interfaces
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Author :
language : en
Publisher:
Release Date : 2004
Heterogeneous Deformable Object Modeling For Medical Surgical Simulation And Collaborative Product Development With Haptic Interfaces written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with categories.
This research focuses on the investigation of heterogeneous deformable object modeling, physically based simulation, haptic force rendering and collaborative techniques for medical surgical simulation, virtual prototyping and collaborative product development. Heterogeneous deformable models can be used to present internal geometric structures and different material properties of biological tissues and other soft-material objects for many Virtual Reality (VR) systems like surgical simulators. Cutting simulation is an important component of VR systems to modify the topology of deformable models. In this paper, a tri-ray node snapping algorithm is presented to generate volumetric heterogeneous mass spring models from a set of interface surfaces between different materials of deformable objects. A constrained local static integration method is proposed to quickly find the equilibrium solution of physically-based deformation behaviors. A 3D node snapping algorithm is developed to implement the topology modification on heterogeneous deformable models. Smooth cut is generated directly by duplicating and displacing mass points that are snapped along cutting planes. Sets of triangular surfaces representing different soft tissues are generated along the new cut to present internal geometric structures and corresponding material properties. A quasi-static algorithm is presented to refine the mesh in the vicinity of new cuts. A lab-built 6-DOF (degree of freedom) input and 5-DOF output haptic interface system is integrated with the developed system to provide force-torque feedback to users. The marriage of network collaborative technology and the proposed deformable object modeling and simulation techniques has a great potential for more extensive applications. Challenges such as heavy computation and data synchronization exist when integrating heterogeneous deformable object models and haptic interfaces with collaborative VR systems. To balance the computational burden of hap.
Graphical Simulation Of Deformable Models
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Author : Jianping Cai
language : en
Publisher: Springer
Release Date : 2018-07-07
Graphical Simulation Of Deformable Models written by Jianping Cai and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-07 with Computers categories.
This book covers dynamic simulation of deformable objects, which is one of the most challenging tasks in computer graphics and visualization. It focuses on the simulation of deformable models with anisotropic materials, one of the less common approaches in the existing research. Both physically-based and geometrically-based approaches are examined. The authors start with transversely isotropic materials for the simulation of deformable objects with fibrous structures. Next, they introduce a fiber-field incorporated corotational finite element model (CLFEM) that works directly with a constitutive model of transversely isotropic material. A smooth fiber-field is used to establish the local frames for each element. To introduce deformation simulation for orthotropic materials, an orthotropic deformation controlling frame-field is conceptualized and a frame construction tool is developed for users to define the desired material properties. The orthotropic frame-field is coupled with the CLFEM model to complete an orthotropic deformable model. Finally, the authors present an integrated real-time system for animation of skeletal characters with anisotropic tissues. To solve the problems of volume distortion and high computational costs, a strain-based PBD framework for skeletal animation is explained; natural secondary motion of soft tissues is another benefit. The book is written for those researchers who would like to develop their own algorithms. The key mathematical and computational concepts are presented together with illustrations and working examples. It can also be used as a reference book for graduate students and senior undergraduates in the areas of computer graphics, computer animation, and virtual reality. Academics, researchers, and professionals will find this to be an exceptional resource.
Articulated Motion And Deformable Objects
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Author : Francisco José Perales
language : en
Publisher: Springer
Release Date : 2016-07-06
Articulated Motion And Deformable Objects written by Francisco José Perales and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-06 with Computers categories.
This book constitutes the refereed proceedings of the 9th International Conference on Articulated Motion and Deformable Objects, AMDO 2016, held in Palma de Mallorca, Spain, in July 2016.The 20 papers presented were carefully reviewed and selected from 34 submissions. The conference dealt with the following topics: advanced computer graphics and immersive videogames; human modeling and animation; human motion analysis and tracking; 3D human reconstruction and recognition; multimodal user interaction and applications; ubiquitous and social computing; design tools; input technology; programming user interfaces; 3D medical deformable models and visualization; deep learning methods for computer vision and graphics; multibiometric.