Realistic haptic rendering of hyper-elastic material via measurement-based FEM model identification and real-time simulation

Abdulali, Arsen; Atadjanov, Ibragim R.; Lee, Seungkyu; Jeon, Seokhee

doi:10.1016/j.cag.2020.04.004

Cited by 9 publications

(4 citation statements)

References 17 publications

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“…The JND curve is initially very large and then rapidly decreases as the reference force increases, finally plateauing to the constant Weber fraction (10%) [42]. The APEs for all the models lie below the JND curve for the reference force larger than 2 N for all the objects, which is generally acceptable [43,26]. Among the three models, the two FD methods show lower APEs than RBF-PV.…”

Section: B Model Trainingmentioning

confidence: 84%

“…Recently, Abdulali et al [26] proposed data-driven methods for hyper-viscoelastic material. In this work, deformation data are captured using external cameras.…”

Section: Related Workmentioning

confidence: 99%

“…Participants' task was to compare the similarity between real and virtual objects and then represent it using a number. This similarity rating paradigm has been frequently used in related studies to data-driven haptics [16,18,19,44,21,26].…”

Section: Perceptual Experimentsmentioning

confidence: 99%

“…We thank Arsen Abdulali and Seokhee Jeon, the authors of[26], for providing the working codes of virtual coupling for deformable objects.8 VOLUME 4, 2016…”

mentioning

confidence: 99%

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Data-Driven Haptic Modeling and Rendering of Viscoelastic Behavior Using Fractional Derivatives

2022

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Data-driven modeling and rendering is a general approach in haptics aiming to provide highly accurate haptic perceptual experiences simulating complex real physical dynamics, such as deformable or textured objects. A prevalent problem in the present methods for data-driven haptics is that the computational cost for modeling grows rapidly, even becoming intractable, as the interaction complexity or the number of data increases. This paper proposes one data-driven method featured with greatly improved computational efficiency for modeling viscoelastic deformable objects. This advantage is enabled by the use of fractional derivatives for modeling features and regression forests for data-interpolation models. For the benchmark of normal interaction on deformable objects, we describe a computational framework for data-driven haptic modeling and rendering. Its performance is validated by physical experiments for modeling accuracy and cost and a perceptual experiment for the similarity between real and virtual objects. The experiments demonstrate that our method offers highly realistic haptic perceptual experiences with markedly better modeling cost (at least ten times) than other state-of-the-art methods.

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Section: B Model Trainingmentioning

confidence: 84%

“…Recently, Abdulali et al [26] proposed data-driven methods for hyper-viscoelastic material. In this work, deformation data are captured using external cameras.…”

Section: Related Workmentioning

confidence: 99%

Section: Perceptual Experimentsmentioning

confidence: 99%

“…We thank Arsen Abdulali and Seokhee Jeon, the authors of[26], for providing the working codes of virtual coupling for deformable objects.8 VOLUME 4, 2016…”

mentioning

confidence: 99%

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Data-Driven Haptic Modeling and Rendering of Viscoelastic Behavior Using Fractional Derivatives

2022

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Haptic Software Design

Abdulali

Jeon

2022

Springer Series on Touch and Haptic Systems

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This chapter reviews design concepts of haptic modeling and rendering software. The main focus lies in realistic kinesthetic and tactile haptic models for virtual and augmented reality based on the data collected from physical objects. We consider both data-driven algorithms providing a black-box action-response mapping and measurement-based approaches identifying parameters of physics-based models. To show the research landscape and highlight ongoing research challenges, we introduce a series of state-of-the-art methods including data-driven models with deterministic and stochastic responses, physics-based simulation using optimization-based FEM solver, and hybrid approaches of combining the concepts of both data-driven and physics-based methods. These examples also cover a wide range of haptic properties, i.e., modeling and rendering of elasticity and plasticity, tool deformation, and haptic textures.

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Fast visualization of finite element analysis results using multiresolution meshes

Kim

2022

J Mech Sci Technol

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Realistic haptic rendering of hyper-elastic material via measurement-based FEM model identification and real-time simulation

Cited by 9 publications

References 17 publications

Data-Driven Haptic Modeling and Rendering of Viscoelastic Behavior Using Fractional Derivatives

Data-Driven Haptic Modeling and Rendering of Viscoelastic Behavior Using Fractional Derivatives

Haptic Software Design

Fast visualization of finite element analysis results using multiresolution meshes

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