A Survey of Physically Based Simulation of Cuts in Deformable Bodies

Wu, Jun; Westermann, Rüdiger; Dick, Christian

doi:10.1111/cgf.12528

Cited by 85 publications

(57 citation statements)

References 119 publications

(201 reference statements)

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“…Indeed, the complexity of this interaction is due to the difficulty in predicting their motions, described by a high number of degrees of freedom, which makes grasp control and planning difficult. Handling deformable objects requires their deformation to be predicted using appropriate models [15] [16].…”

Section: Introductionmentioning

confidence: 99%

Model-based strategy for grasping3Ddeformable objects using a multi-fingered robotic hand

Zaidi

Ramón

Bouzgarrou

et al. 2017

Robotics and Autonomous Systems

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. Model-based strategy for grasping 3 D deformable objects using a multifingered robotic hand.Robotics and Autonomous Systems, Elsevier, 2017, 95, pp.196-206 AbstractThis paper presents a model-based strategy for 3D deformable object grasping using a multi-fingered robotic hand. The developed contact model is based on two force components (normal force and tangential friction force, including slipping and sticking effects) and uses a non-linear mass-spring system to describe the object deformations due the mechanical load applied by the fingers of the robotic hand. The object-finger interaction is simulated in order to compute the required contact forces and deformations to robustly grasp objects with large deformations. Our approach is able to achieve this by using a non-linear model that outperforms current techniques that are limited to using linear models. After the contact forces computed by the simulation of the contact model guarantee the equilibrium of the grasp, they will be used as set-points for forcecontrolling the closing of the real fingers, and thus, the proposed grasping strategy is implemented. Two different objects (cube and sphere) made from two soft materials (foam and rubber) are tested in order to verify that the proposed model can represent their non-linear deformations and that the proposed grasp strategy can implement a robust grasp of them with a multi-fingered robotic hand equipped with tactile sensors. Thereby, both the grasping strategy and the proposed contact model are validated experimentally.

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Section: Introductionmentioning

confidence: 99%

Model-based strategy for grasping3Ddeformable objects using a multi-fingered robotic hand

Zaidi

Ramón

Bouzgarrou

et al. 2017

Robotics and Autonomous Systems

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“…Real-time interactive cutting of deformable objects Wu et al [14] recently wrote an excellent survey on cutting methods of deformable objects. Therefore, we will only give brief descriptions of these methods.…”

Section: Real-time Deformation Of Deformable Objectsmentioning

confidence: 99%

CPU–GPU mixed implementation of virtual node method for real-time interactive cutting of deformable objects using OpenCL

Jia

Zhang

et al. 2015

Int J CARS

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Our cutting algorithm can produce continuous cut surfaces when traditional minimal element creation algorithm fails. Our GPU-accelerated deformation algorithm remains stable with constant time step under multiple arbitrary cuts and works on both NVIDIA and AMD GPUs. GPU-CPU speed ratio can be as high as 10 for models with 80,000 tetrahedrons. Forty to sixty percent real-time performance and 100-200 Hz simulation rate are achieved for the liver model with 3,101 tetrahedrons. Major bottlenecks for simulation efficiency are cutting, collision processing and CPU-GPU data transfer. Future work needs to improve on these areas.

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“…However, this type of model cannot be used in applications that need to represent both the exterior and the interior volumes of a 3D object [2]. This is the case for simulation applications, which require to represent the interior volumes of an object to associate material properties and perform computations for each internal element [3]. This is also the case in modeling applications of buildings that describe a building as an assembly of several 3D objects [4].…”

Section: Introductionmentioning

confidence: 99%

Distributed Combinatorial Maps for Parallel Mesh Processing

et al. 2018

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Abstract:We propose a new strategy for the parallelization of mesh processing algorithms. Our main contribution is the definition of distributed combinatorial maps (called n-dmaps), which allow us to represent the topology of big meshes by splitting them into independent parts. Our mathematical definition ensures the global consistency of the meshes at their interfaces. Thus, an n-dmap can be used to represent a mesh, to traverse it, or to modify it by using different mesh processing algorithms. Moreover, an nD mesh with a huge number of elements can be considered, which is not possible with a sequential approach and a regular data structure. We illustrate the interest of our solution by presenting a parallel adaptive subdivision method of a 3D hexahedral mesh, implemented in a distributed version. We report space and time performance results that show the interest of our approach for parallel processing of huge meshes.

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A Survey of Physically Based Simulation of Cuts in Deformable Bodies

Cited by 85 publications

References 119 publications

Model-based strategy for grasping3Ddeformable objects using a multi-fingered robotic hand

Model-based strategy for grasping3Ddeformable objects using a multi-fingered robotic hand

CPU–GPU mixed implementation of virtual node method for real-time interactive cutting of deformable objects using OpenCL

Distributed Combinatorial Maps for Parallel Mesh Processing

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