Adaptive simulation of soft bodies in real-time

Debunne, Gilles; Desbrun, Mathieu; Cani, Marie-Paule; Barr, Alan H.

doi:10.1109/ca.2000.889022

Cited by 45 publications

(28 citation statements)

References 29 publications

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“…Most of the work on this type of motion has concentrated on finding accurate and fast numerical solvers [13,14], and on defining the appropriate M; C and K which result in realistic animation sequences [15].…”

Section: Physical-based Animationmentioning

confidence: 99%

Compression of soft-body animation sequences

Karni

Gotsman

2004

Computers & Graphics

192

170

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We describe a compression scheme for the geometry component of 3D animation sequences. This scheme is based on the principle component analysis (PCA) method, which represents the animation sequence using a small number of basis functions. Second-order linear prediction coding (LPC) is applied to the PCA coefficients in order to further reduce the code size by exploiting the temporal coherence present in the sequence. Our results show that applying LPC to the PCA scheme results in significant performance improvements relative to other coding methods. The use of these codes will make animated 3D data more accessible for graphics and visualization applications. r

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Section: Physical-based Animationmentioning

confidence: 99%

Compression of soft-body animation sequences

Karni

Gotsman

2004

Computers & Graphics

192

170

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“…The finite element method (FEM) [2], [6], [11], finite volume method (FVM) [1], [2], and long element method (LEM) [7], [8], [9], [10] have been used in physically based modeling including soft bodies tissue. To solve an equation, approximation of a continuous set of discrete points, usually a set of grid or mesh points, is used.…”

Section: Introductionmentioning

confidence: 99%

Simulation of Soft Bodies with Pressure Force and the Implicit Method

Mesit

Guha

2007

First Asia International Conference on Modelling &Amp; Simulation (AMS'07)

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“…Most other existing models for modeling softness are rather complex to implement and come with slow solving speed [16]. In principle, pressure is a force acting on incremental surface elements and is normal to the surface.…”

Section: A Pressure Based Model For Soft Cellsmentioning

confidence: 99%

Soft Cell Simulator: A tool to study soft multi-cellular robots

Germann

Maesani

Stockli

et al. 2013

2013 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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Abstract-Modular or multi-cellular robots hold the promise to adapt their morphology to task and environment. However, research in modular robotics has traditionally been limited to mechanically non-adaptive systems due to hard building blocks and rigid connection mechanisms. To improve adaptation and global flexibility, we suggest the use of modules made of soft materials. Thanks to recent advances in fabrication techniques the development of soft robots without spatial or material constraints is now possible. In order to exploit this vast design space, computer simulations are a time and cost-efficient tool. However, there is currently no framework available that allows studying the dynamics of soft multi-cellular systems. In this work, we present our simulation framework named Soft Cell Simulator (SCS) that enables to study both mechanical design parameters as well as control problems of soft multi-cellular systems in an time-efficient yet globally accurate manner. Its main features are: (i) high simulation speed to test systems with a large number of cells (real-time up to 100 cells), (ii) large non-linear deformations without module self-penetration, (iii) tunability of module softness (0-500 N/m), (iv) physicsbased module connectivity, (v) variability of module shape using internal actuators. We present results that validate the plausibility of the simulated soft cells, the scalability as well as the usability of the simulator. We suggest that this simulator helps to master and leverage the potential of the vast design space to generate novel soft multi-cellular robots.

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Adaptive simulation of soft bodies in real-time

Cited by 45 publications

References 29 publications

Compression of soft-body animation sequences

Compression of soft-body animation sequences

Simulation of Soft Bodies with Pressure Force and the Implicit Method

Soft Cell Simulator: A tool to study soft multi-cellular robots

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